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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">AJMA</journal-id>
      <journal-title-group>
        <journal-title>Asian Journal of Management Analytics</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2963-4547</issn>
      <publisher>
        <publisher-name>Formosa Publisher</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.55927/ajma.v4i3.15110</article-id>
      <title-group>
        <article-title>Factors Determining Purchasing Decisions: A Review of Social Media, E-WOM, and Product Quality</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Wahyuningsih</surname>
            <given-names>Septia Tri</given-names>
          </name>
          <aff>Universitas Muhammadiyah Purwokerto, Indonesia</aff>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Hidayah</surname>
            <given-names>Arini</given-names>
          </name>
          <aff>Universitas Muhammadiyah Purwokerto, Indonesia</aff>
          <email>arinihidayah77@gmail.com</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Agung</surname>
            <given-names>Muchammad</given-names>
          </name>
          <aff>Universitas Muhammadiyah Purwokerto, Indonesia</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Miftahuddin</surname>
            <given-names></given-names>
          </name>
          <aff>Universitas Muhammadiyah Purwokerto, Indonesia</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rahmawati</surname>
            <given-names>Ika Yustina</given-names>
          </name>
          <aff>Universitas Muhammadiyah Purwokerto, Indonesia</aff>
        </contrib>
      </contrib-group>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>07</month>
        <year>2025</year>
      </pub-date>
      <history>
        <date date-type="received">
          <day>10</day>
          <month>06</month>
          <year>2025</year>
        </date>
        <date date-type="rev-recd">
          <day>26</day>
          <month>06</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>28</day>
          <month>07</month>
          <year>2025</year>
        </date>
      </history>
      <volume>4</volume>
      <issue>3</issue>
      <fpage>1359</fpage>
      <lpage>1374</lpage>
      <abstract>
        <p>This study aims to analyse the influence of social media, e-WOM, and product quality on purchasing decisions among consumers of Donlight Donut Shop. This study uses a quantitative method with data collection through questionnaires distributed directly. Non-probability sampling was used with the accidental sampling method, involving 110 respondents. Data analysis was assisted by SPSS 20. The results of the study indicate that social media, e-WOM, and product quality have a significant positive influence on purchasing decisions. The findings of this study can assist Donlight in improving its operational strategies, particularly in social media, e-WOM, and product quality, to maintain consumer purchasing decisions and enhance competitiveness in the food business.</p>
      </abstract>
      <kwd-group>
        <kwd>Social Media</kwd>
        <kwd>E-WOM</kwd>
        <kwd>Product Quality</kwd>
        <kwd>Purchasing Decisions</kwd>
      </kwd-group>
      <permissions>
        <license>
          <ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">http://creativecommons.org/licenses/by/4.0/</ali:license_ref>
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
    </article-meta>
  </front>

  <body>

<sec>
  <title>INTRODUCTION</title>
  <p>The development of the creative economy (ekraf) is predicted by the
  majority of experts to experience growth compared to 2022. Experts
  predict that growth will be influenced by innovation and creativity
  from business/industry players (69.05%). When examining the
  sub-sectors, the culinary sub-sector is expected to grow rapidly,
  driven by the return of dine-in services, Ramadan, and the 2024
  Creative Economy Political Year. The culinary sector has seen
  innovation and creativity, as the culinary business in Indonesia
  offers unlimited opportunities, ranging from franchises, partnerships,
  to modern food and beverage innovations. Additionally, the consumerist
  lifestyle of Indonesian society is driving the growth of large
  culinary businesses, which in turn encourages consumers to purchase
  culinary products (Lukman et al., 2023).</p>
  <p><inline-graphic mimetype="image" mime-subtype="png" xlink:href="vertopal_df7efc736e064a4499c44e8e4b0d4055/media/image3.png" /><inline-graphic mimetype="image" mime-subtype="png" xlink:href="vertopal_df7efc736e064a4499c44e8e4b0d4055/media/image4.png" /><inline-graphic mimetype="image" mime-subtype="png" xlink:href="vertopal_df7efc736e064a4499c44e8e4b0d4055/media/image5.png" /><inline-graphic mimetype="image" mime-subtype="png" xlink:href="vertopal_df7efc736e064a4499c44e8e4b0d4055/media/image3.png" /><inline-graphic mimetype="image" mime-subtype="png" xlink:href="vertopal_df7efc736e064a4499c44e8e4b0d4055/media/image6.png" />The
  culinary scene in Banyumas Regency has grown rapidly over the years
  thanks to the large number of people starting culinary businesses and
  the high profit potential. The presence of SME centres has also
  contributed to the increasing number of culinary businesses and can
  help boost the local economy. These SMEs can also present business
  opportunities for the community. These SMEs can also present business
  opportunities for the community. According to data compiled by the
  Central Statistics Agency, the development of the number of Micro and
  Small Industries (MSI) in Indonesia over the past five years has shown
  an interesting fluctuation, as follows:</p>
  <p><italic>Source:</italic> Bps.go.id</p>
  <p>Figure 1. IMK</p>
  <p>In 2019, the number of IMKs was recorded at 4.38 million business
  units. However, due to the impact of the COVID-19 pandemic, this
  number decreased to 4.21 million units in 2020 and continued to
  decline in 2021 to 4.16 million units. Nevertheless, a recovery trend
  began to emerge in 2022, with the number of SMEs increasing again to
  4.34 million units, and continuing to show positive recovery, reaching
  4.5 million business units in 2023. This increase reflects the
  recovery of economic activity post-pandemic and the active role of the
  government in promoting entrepreneurship, empowering MSMEs, and
  digitising the small and micro industry sector (Central Statistics
  Agency, 2023). The food and beverage industry is now increasingly
  developing, with consumers prioritising their spending on food product
  purchases. As a result, food and beverage businesses are striving to
  attract consumers and meet their needs by offering the food or</p>
  <p>beverage products they desire. (Roibafi et al., 2022).</p>
  <p>Donlight is one of the most well-known and rapidly growing donut
  shops in Purwokerto. The shop is strategically located in the city
  centre, making it easily accessible to the public. With its modern
  store concept and interior design featuring attractive colours,
  Donlight has successfully captured the attention of consumers from
  various backgrounds. The business was founded by Arif and began
  operations in 2022 using a pre-order (PO) system. As time went on and
  consumer interest grew, Donlight opened its first outlet in September
  2023, located on Jl. Puteran, Purwokerto Timur. One of Donlight's
  unique features is its system allowing customers to choose donut
  toppings according to their preferences, providing a personalised
  experience for each consumer. Researchers selected Donlight as the
  subject of this study because it is a local product originating from
  Purwokerto. Through this research, it is hoped that contributions can
  be made to advancing and strengthening the competitiveness of local
  products in the region.</p>
  <p>Many factors can influence purchasing decisions, such as social
  media variables, e-wom, and product quality in today's digital age.
  Social media is used because it has become the main platform for
  businesses to market products and build interactions with consumers.
  Consumers today tend to search for information through social media
  platforms before making purchasing decisions. Then, the e-wom variable
  is digital word-of-mouth promotion. The influence of e-WOM on
  purchasing decisions is increasingly significant as consumer trust in
  other users' opinions grows compared to advertisements from
  manufacturers. Product quality remains the most critical factor in
  achieving success for a product. While social media promotions and
  positive reviews can attract consumer attention, product quality
  remains the primary determinant in creating satisfaction, loyalty, and
  repeat purchases.</p>
  <p>A purchasing decision is an evaluation of several alternative
  courses of action from a process in which a person decides on one of
  several options, and the result of the integration of attitudes and
  knowledge that ultimately determines their choice. This process
  involves the formation of preferences for certain products, which
  ultimately leads to the choice and desire to purchase those products,
  and finally the decision to purchase them.(Marlius &amp; Mutiara,
  2022).</p>
  <p>Social media is personal communication for sharing between
  individuals using public media that can be shared with anyone without
  being specific to a particular individual (Anggraeni &amp; Djuwita,
  2019). Technological advancements, such as those in the field of
  telecommunications, have become highly sophisticated, enabling
  communication without limitations imposed by distance or space, and
  offering greater freedom. The development of social media platforms
  like Instagram, TikTok, Facebook, and others continues to grow. These
  technological advancements can also be beneficial for entrepreneurs in
  conducting promotions. Previous studies conducted by Hm et al. (2020),
  Andhyka et al. (2024), dan Puirih et al. (2020), Shadrina &amp;
  Sulistyanto (2022),Prasetyo et al. (2021),Riskyady &amp; Sulistyowati
  (2021), danNingrum et al.</p>
  <p>(2023), shows that the existence of social media has a significant
  positive impact on purchasing decisions.</p>
  <p>As technology has developed, the use of Electronic Word of Mouth
  (E- WOM) is considered more effective than Word of Mouth (WOM), which
  is simply passed on from person to person Priansa (2016). E-WOM is a
  response or opinion from consumers, both positive and negative, about
  products they have purchased and used. It is distributed via the
  internet so that many people can see it. H &amp; P (2021). Previous
  studies, as shown in Rahmadani et al. (2024),Waringga et al. (2023),
  and others, indicating that E-WOM increases purchasing decisions.</p>
  <p>Product quality is a characteristic of a product or service that
  depends on its ability to meet the stated or implied needs of
  customers, Kotler and Armstrong (2015:253) Given the intense
  competition in the food industry today, companies or business owners
  must carefully consider and plan well-thought-out strategies to
  compete with other food businesses. Business operators are required to
  develop strategies to compete, such as innovating various unique food
  and beverage products, determining product quality that differs from
  competitors to establish a unique identity and distinctive
  characteristics.Juwita (2021). A number of previous studies, such as
  those conducted by Roibafi et al. (2022), Juwita (2021), Grandhis
  (2022), and other researchers, revealed that product quality has a
  positive and significant effect on purchasing decisions.</p>
  <p>Based on previous research by Hasan &amp; Sohail (2021), which
  found that social media influences consumer purchasing decisions, this
  study adds the variables of E-WOM and Product Quality based on
  previous research by Anggraeni &amp; Djuwita (2019) which found that
  E-WOM and Product Quality influence purchasing decisions. In addition,
  the distinctive feature of research compared to previous studies lies
  in its focus on Donlight customers.</p>
</sec>












<sec>
  <title>LITERATURE REVIEW</title>
  <sec id="s-o-r-theory-stimulus-organism-response">
    <title>S-O-R Theory (Stimulus, Organism, Response)</title>
    <p>In 1953, Carl Iver Hovland proposed the S-O-R (Stimulus,
    Organism, Response) theory, which was developed from communication
    and psychology. According to this theory, the content of a stimulus
    message influences a person's response. The message can be accepted
    or rejected depending on its appeal to the recipient. If the message
    is well understood, it will cause a change in attitude. The better
    the quality of the product being communicated, the easier it is for
    the stimulus to be accepted and build trust in the product. As a
    result, the organism or recipient will be more motivated to attract
    consumers' attention to the product or service being offered. This
    theory states that behavioural change is influenced by the
    interaction between the quality of the stimulus and the organism,
    where the quality of communication is the key to its
    success.(Suryadi et al., 2023)</p>
  </sec>
  <sec id="purchase-decision">
    <title>Purchase Decision</title>
    <p>A purchasing decision is an action that leads to a purchase and
    is ultimately followed by post-purchase behaviour. What is meant by
    action here is the process of recognising the need and desire for a
    product, assessing available resources, determining the purpose of
    the purchase, and considering various alternatives. In order for a
    purchasing decision to be made correctly, a person</p>
    <p>needs to have reasons and objectives that underlie that choice
    (Puirih et al., 2020).</p>
  </sec>
  <sec id="social-media">
    <title>Social Media</title>
    <p>Social media refers to websites or applications that allow users
    to create and share content while interacting with other users
    Hudson (2020). In the past, marketing products or services was
    mostly done through offline methods. On the other hand, in this era
    of rapid technological and internet development, sellers and
    companies are required to adapt by switching to online sales. Now,
    more and more people are realising that sales through social media
    or online methods are more effective and efficient than offline
    methods (Bate’, 2019).</p>
  </sec>
  <sec id="e-wom">
    <title>E-WOM</title>
    <p><italic>Elektronik Word of Mouth</italic> (E-WOM) is a form of
    online communication where consumers exchange opinions or reviews
    about products or services, both positive and negative. E-WOM is
    very important for marketing in today's technological era and can be
    conveyed through various internet platforms such as social media or
    product review sites. E-WOM has become very important and can even
    serve as a reference. Consumers are more motivated to buy goods or
    services if the reviews are more positive and favourable. (Amin et
    al., 2021).</p>
  </sec>
  <sec id="product-quality">
    <title>Product Quality</title>
    <p>There is another theory presented by Arianti et al. (2020),
    Product quality is related to the product's performance, which
    includes overall aspects, accuracy, durability, ease of repair,
    operational sustainability, and other aspects related to the
    product. Therefore, product quality is key to how good the product
    is and must be able to provide product satisfaction to consumers,
    and is expected to exceed competitors or at least be comparable to
    competing products.</p>
    <graphic mimetype="image" mime-subtype="png" xlink:href="vertopal_df7efc736e064a4499c44e8e4b0d4055/media/image7.png" />
  </sec>
</sec>
<sec id="figure-2.-conseptual-framework">
  <title>Figure 2. Conseptual Framework</title>
  <p>The hypothesis in this study is that:</p>
  <p>H1 : Social media has a significant positive influence on
  purchasing decisions. H2 : E-WOM has a significant positive influence
  on purchasing decisions.</p>
  <p>H3 : Product quality has a significant positive influence on
  purchasing decisions.</p>
</sec>














<sec>
  <title>METHODOLOGY</title>
  <p>This quantitative study uses non-probability sampling, in which not
  all members of the population have an equal chance of being selected
  as samples. Accidental sampling is used, which involves selecting
  samples based on chance, or anyone who happens to meet the researcher
  by chance and is suitable to be a data source (Sugiyono, 2017).
  Visitors who make purchases at the Donlight Donut Shop are included in
  the research sample.</p>
  <p>This study used 110 respondents. The data in this study was
  obtained through questionnaires distributed to visitors of Donlight
  Donut Shop. The study used a five-point Likert scale, ranging from (1)
  strongly disagree to (5) strongly agree.</p>
  <p>Data were collected and processed using SPSS 20 software. The data
  analysis stages consisted of validity testing, reliability testing,
  classical assumption testing, multiple linear regression analysis,
  descriptive statistics, as well as coefficient of determination (R²)
  testing, simultaneous testing (F), and partial testing (T). These are
  some of the data analysis methods used.</p>
</sec>













<sec>
  <title>RESEARCH RESULT</title>
  <sec id="respons-rate">
    <title>Respons Rate</title>
    <disp-quote>
      <p>Table 1. Respons Rate</p>
    </disp-quote>
    <table-wrap>
      <label>Table 1. Respons Rate</label>
      <caption>
        <title><italic>Source: processed data</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="center" valign="top">No</th>
            <th align="center" valign="top">Description</th>
            <th align="center" valign="top">Number of Questioner</th>
            <th align="center" valign="top">Percentage (%)</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="center" valign="top">1</td>
            <td align="left" valign="top">Questionnaires that were distributed</td>
            <td align="center" valign="top">110</td>
            <td align="center" valign="top">100</td>
          </tr>
          <tr>
            <td align="center" valign="top">2</td>
            <td align="left" valign="top">Completed questionnaire</td>
            <td align="center" valign="top">110</td>
            <td align="center" valign="top">100</td>
          </tr>
          <tr>
            <td align="center" valign="top">3</td>
            <td align="left" valign="top">Unreturned questionnaire</td>
            <td align="center" valign="top">0</td>
            <td align="center" valign="top">0</td>
          </tr>
          <tr>
            <td align="center" valign="top">4</td>
            <td align="left" valign="top">Questionnaires that are worth analyzing</td>
            <td align="center" valign="top">110</td>
            <td align="center" valign="top">100</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Individuals who have made purchases at Donlight Donut Shop are
    the respondents of this research. A non-probability sampling method
    was used in this research. In this study, questionnaires were
    distributed over a period of three weeks, with the aim of obtaining
    110 respondents. During that time, 110 respondents completed the
    questionnaire. Therefore, 110 respondents were eligible for
    analysis.</p>
  </sec>
  <sec id="responden-description">
    <title>Responden Description</title>
    <disp-quote>
      <p>Table 2. Deskripsi Responden</p>
    </disp-quote>
    <table-wrap>
      <label>Table 2. Deskripsi Responden</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="center" valign="top">No</th>
            <th align="center" valign="top">Description</th>
            <th align="center" valign="top">F</th>
            <th align="center" valign="top">Percentage (%)</th>
            <th align="center" valign="top">No</th>
            <th align="center" valign="top">Description</th>
            <th align="center" valign="top">F</th>
            <th align="center" valign="top">Prosentase (%)</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="center" valign="top">1.</td>
            <td align="left" valign="top">Gender</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top">3.</td>
            <td align="left" valign="top">Job</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Male</td>
            <td align="center" valign="top">54</td>
            <td align="center" valign="top">49</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Student</td>
            <td align="center" valign="top">52</td>
            <td align="center" valign="top">47</td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Female</td>
            <td align="center" valign="top">56</td>
            <td align="center" valign="top">51</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Private Employee</td>
            <td align="center" valign="top">22</td>
            <td align="center" valign="top">20</td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Total</td>
            <td align="center" valign="top">110</td>
            <td align="center" valign="top">100</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Civil Servant</td>
            <td align="center" valign="top">10</td>
            <td align="center" valign="top">9</td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Self Employed</td>
            <td align="center" valign="top">21</td>
            <td align="center" valign="top">19</td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Etc.</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">5</td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Total</td>
            <td align="center" valign="top">110</td>
            <td align="center" valign="top">100</td>
          </tr>
          <tr>
            <td align="center" valign="top">2.</td>
            <td align="left" valign="top">Age</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">18-25 years old</td>
            <td align="center" valign="top">85</td>
            <td align="center" valign="top">77</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">26-33 years old</td>
            <td align="center" valign="top">21</td>
            <td align="center" valign="top">19</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">34-41 years old</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">&gt;41</td>
            <td align="center" valign="top">1</td>
            <td align="center" valign="top">1</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="center" valign="top"></td>
            <td align="left" valign="top">Total</td>
            <td align="center" valign="top">110</td>
            <td align="center" valign="top">100</td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Based on the results of the respondent description analysis, the
    dominant factors in visiting and making purchases at Donlight based
    on gender, age, and occupation were 56 people (51%) women, then 85
    people (77%) in the 18-25 age group, and 52 people (47%) were
    students.</p>
  </sec>
  <sec id="descriptive-statistical-analytics">
    <title>Descriptive Statistical Analytics</title>
    <disp-quote>
      <p>Table 3. Analisis Statistik Deskriptif</p>
    </disp-quote>
    <table-wrap>
      <label>Table 3. Analisis Statistik Deskriptif</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top">Variabel</th>
            <th align="left" valign="top">Questions Item</th>
            <th align="center" valign="top">Min</th>
            <th align="center" valign="top">Max</th>
            <th align="center" valign="top">Mean</th>
            <th align="center" valign="top">St.Dev</th>
            <th align="left" valign="top">Definition Mean</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top">Social Media</td>
            <td align="left" valign="top">X1.1</td>
            <td align="center" valign="top">2</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.74</td>
            <td align="center" valign="top">0.463</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X1.2</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.58</td>
            <td align="center" valign="top">0.565</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X1.3</td>
            <td align="center" valign="top">2</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.26</td>
            <td align="center" valign="top">0.519</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X1.4</td>
            <td align="center" valign="top">2</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.41</td>
            <td align="center" valign="top">0.547</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X1.5</td>
            <td align="center" valign="top">1</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.66</td>
            <td align="center" valign="top">0.475</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X1.6</td>
            <td align="center" valign="top">2</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.31</td>
            <td align="center" valign="top">0.538</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top">E-WOM</td>
            <td align="left" valign="top">X2.1</td>
            <td align="center" valign="top">2</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.91</td>
            <td align="center" valign="top">0.289</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X2.2</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.60</td>
            <td align="center" valign="top">0.510</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X2.3</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.80</td>
            <td align="center" valign="top">0.424</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X2.4</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.68</td>
            <td align="center" valign="top">0.487</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X2.5</td>
            <td align="center" valign="top">4</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.61</td>
            <td align="center" valign="top">0.490</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top">Product Quality</td>
            <td align="left" valign="top">X3.1</td>
            <td align="center" valign="top">4</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.70</td>
            <td align="center" valign="top">0.460</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X3.2</td>
            <td align="center" valign="top">4</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.70</td>
            <td align="center" valign="top">0.460</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X3.3</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.64</td>
            <td align="center" valign="top">0.520</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X3.4</td>
            <td align="center" valign="top">4</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.62</td>
            <td align="center" valign="top">0.488</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X3.5</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.23</td>
            <td align="center" valign="top">0.616</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">X3.6</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.25</td>
            <td align="center" valign="top">0.612</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top">Purchasing Decisions</td>
            <td align="left" valign="top">Y.1</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.79</td>
            <td align="center" valign="top">0.430</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">Y.2</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.20</td>
            <td align="center" valign="top">0.571</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">Y.3</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.51</td>
            <td align="center" valign="top">0.520</td>
            <td align="left" valign="top">Agree</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="left" valign="top">Y.4</td>
            <td align="center" valign="top">4</td>
            <td align="center" valign="top">5</td>
            <td align="center" valign="top">4.55</td>
            <td align="center" valign="top">0.499</td>
            <td align="left" valign="top">Agree</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>The results of the descriptive analysis show that the highest
    respondent responses were for the social media variable, with an
    average value of 4.74 and a lowest value of 4.26. followed by the
    highest score for the e-WOM variable at 4.91 and the lowest at 4.60,
    the highest score for the product quality variable at 4.70 and the
    lowest at 4.23, and the highest average score was shown by the
    purchase decision variable, with a value of 4.79 and the lowest at
    4.20.</p>
  </sec>
  <sec id="validity-test">
    <title>Validity Test</title>
    <disp-quote>
      <p>Table 4.Validity test</p>
    </disp-quote>
    <table-wrap id="T4">
      <label>Table 4. Validity test</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top">Indicator</th>
            <th align="center" valign="top">R count</th>
            <th align="center" valign="top">R table</th>
            <th align="left" valign="top">Descripts</th>
            <th align="left" valign="top">Indicator</th>
            <th align="center" valign="top">R count</th>
            <th align="center" valign="top">R table</th>
            <th align="left" valign="top">Descripts</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top"></td>
            <td align="center" valign="top" colspan="3">Social Media</td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top" colspan="3">Product Quality</td>
          </tr>
          <tr>
            <td align="left" valign="top">X1.1</td>
            <td align="center" valign="top">0.601</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">X3.1</td>
            <td align="center" valign="top">0.465</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X1.2</td>
            <td align="center" valign="top">0.611</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">X3.2</td>
            <td align="center" valign="top">0.454</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X1.3</td>
            <td align="center" valign="top">0.591</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">X3.3</td>
            <td align="center" valign="top">0.553</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X1.4</td>
            <td align="center" valign="top">0.718</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">X3.4</td>
            <td align="center" valign="top">0.521</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X1.5</td>
            <td align="center" valign="top">0.583</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">X3.5</td>
            <td align="center" valign="top">0.724</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X1.6</td>
            <td align="center" valign="top">0.701</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">X3.6</td>
            <td align="center" valign="top">0.741</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top"></td>
            <td align="center" valign="top" colspan="3">E-WOM</td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top" colspan="3">Purchasing Decisions</td>
          </tr>
          <tr>
            <td align="left" valign="top">X2.1</td>
            <td align="center" valign="top">0.640</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">Y1</td>
            <td align="center" valign="top">0.470</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X2.2</td>
            <td align="center" valign="top">0.740</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">Y2</td>
            <td align="center" valign="top">0.798</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X2.3</td>
            <td align="center" valign="top">0.607</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">Y3</td>
            <td align="center" valign="top">0.794</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X2.4</td>
            <td align="center" valign="top">0.722</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top">Y4</td>
            <td align="center" valign="top">0.787</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
          </tr>
          <tr>
            <td align="left" valign="top">X2.5</td>
            <td align="center" valign="top">0.751</td>
            <td align="center" valign="top">0.190</td>
            <td align="left" valign="top">VALID</td>
            <td align="left" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="left" valign="top"></td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>According to Ghozali (2018), all items were declared valid in the
    validity test because the calculated r value for each item was
    higher than the table r value for each item. Therefore, the validity
    test requirements were met, and the data could be analysed
    further.</p>
  </sec>
  <sec id="reliability-test">
    <title>Reliability Test</title>
    <disp-quote>
      <p>Table 5. Reliability test</p>
    </disp-quote>
    <table-wrap>
      <label>Table 5. Reliability test</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top">Variabel</th>
            <th align="center" valign="top">Cronbach's Alpha</th>
            <th align="center" valign="top">Nilai Sig</th>
            <th align="left" valign="top">Information</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top">Social Media (X1)</td>
            <td align="center" valign="top">0,704</td>
            <td align="center" valign="top">&gt; 0.6</td>
            <td align="left" valign="top">Reliable</td>
          </tr>
          <tr>
            <td align="left" valign="top">E-WOM (X2)</td>
            <td align="center" valign="top">0,733</td>
            <td align="center" valign="top">&gt; 0.6</td>
            <td align="left" valign="top">Reliable</td>
          </tr>
          <tr>
            <td align="left" valign="top">Product Quality (X3)</td>
            <td align="center" valign="top">0,604</td>
            <td align="center" valign="top">&gt; 0.6</td>
            <td align="left" valign="top">Reliable</td>
          </tr>
          <tr>
            <td align="left" valign="top">Purchasing Decisions (Y)</td>
            <td align="center" valign="top">0,679</td>
            <td align="center" valign="top">&gt; 0.6</td>
            <td align="left" valign="top">Reliable</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Based on the reliability test, each variable has a Cronbach's
    Alpha value above 0.60, so it is considered reliable. This means
    that the variables have met the reliability requirements and can be
    used in this study. (Ghozali, 2018).</p>
  </sec>
  <sec id="normality-test">
    <title>Normality Test</title>
    <disp-quote>
      <p>Table 6. Normality test</p>
    </disp-quote>
<table-wrap id="T6">
  <label>Table 6.</label>
  <caption>
    <title><italic>Source: processed data by SPSS 20</italic></title>
    <label>a</label><p>Test distribution is Normal.</p>
    <label>b</label><p>Calculated from data.</p>
  </caption>
  <table>
    <thead>
      <tr>
        <th align="left" valign="top" rowspan="2"></th>
        <th align="center" valign="top" colspan="2">Unstandardized Residual</th>
      </tr>
      <tr>
        <th align="left" valign="top"></th>
        <th align="center" valign="top"></th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td align="left" valign="top">N</td>
        <td align="left" valign="top"></td>
        <td align="center" valign="top">110</td>
      </tr>
      <tr>
        <td align="left" valign="top">Normal Parameters<xref ref-type="fn" rid="tfn1">a</xref>,<xref ref-type="fn" rid="tfn2">b</xref></td>
        <td align="left" valign="top">Mean</td>
        <td align="center" valign="top">0E-7</td>
      </tr>
      <tr>
        <td align="left" valign="top"></td>
        <td align="left" valign="top">Std. Deviation</td>
        <td align="center" valign="top">.26582580</td>
      </tr>
      <tr>
        <td align="left" valign="top">Most Extreme Differences</td>
        <td align="left" valign="top">Absolute</td>
        <td align="center" valign="top">.080</td>
      </tr>
      <tr>
        <td align="left" valign="top"></td>
        <td align="left" valign="top">Positive</td>
        <td align="center" valign="top">.080</td>
      </tr>
      <tr>
        <td align="left" valign="top"></td>
        <td align="left" valign="top">Negative</td>
        <td align="center" valign="top">-.063</td>
      </tr>
      <tr>
        <td align="left" valign="top" colspan="2">Kolmogorov-Smirnov Z</td>
        <td align="center" valign="top">.835</td>
      </tr>
      <tr>
        <td align="left" valign="top" colspan="2">Asymp. Sig. (2-tailed)</td>
        <td align="center" valign="top">.489</td>
      </tr>
    </tbody>
  </table>
</table-wrap>
    <p>The Kolmogorov-Smirnov normality test using SPSS produced a
    significance level of 0.489. Since this value exceeds 0.05, the data
    from 110 respondents can be declared normally distributed.
    (Ghozali,2018)</p>
  </sec>
  <sec id="multicollinearity-test">
    <title>Multicollinearity Test</title>
    <disp-quote>
      <p>Table 7. Multicollinearity Test</p>
    </disp-quote>
    <table-wrap>
      <label>Table 7. Multicollinearity Test</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top" rowspan="3">Model</th>
            <th align="center" valign="top" colspan="2">Unstandardized Coefficients</th>
            <th align="center" valign="top" rowspan="2">Standardized Coefficients</th>
            <th align="center" valign="top" rowspan="2">t</th>
            <th align="center" valign="top" rowspan="2">Sig.</th>
            <th align="center" valign="top" colspan="2">Collinearity Statistics</th>
          </tr>
          <tr>
            <th align="center" valign="top">B</th>
            <th align="center" valign="top">Std. Error</th>
            <th align="center" valign="top">Tolerance</th>
            <th align="center" valign="top">VIF</th>
          </tr>
          <tr>
            <th align="center" valign="top"></th>
            <th align="center" valign="top"></th>
            <th align="center" valign="top">Beta</th>
            <th align="center" valign="top"></th>
            <th align="center" valign="top"></th>
            <th align="center" valign="top"></th>
            <th align="center" valign="top"></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top">(Constant)</td>
            <td align="center" valign="top">.267</td>
            <td align="center" valign="top">.473</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top">.565</td>
            <td align="center" valign="top">.573</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="left" valign="top">1 Social Media</td>
            <td align="center" valign="top">.431</td>
            <td align="center" valign="top">.097</td>
            <td align="center" valign="top">.397</td>
            <td align="center" valign="top">4.455</td>
            <td align="center" valign="top">.000</td>
            <td align="center" valign="top">.640</td>
            <td align="center" valign="top">1.562</td>
          </tr>
          <tr>
            <td align="left" valign="top">E-WOM</td>
            <td align="center" valign="top">.199</td>
            <td align="center" valign="top">.099</td>
            <td align="center" valign="top">.169</td>
            <td align="center" valign="top">2.011</td>
            <td align="center" valign="top">.047</td>
            <td align="center" valign="top">.721</td>
            <td align="center" valign="top">1.386</td>
          </tr>
          <tr>
            <td align="left" valign="top">Product Quality</td>
            <td align="center" valign="top">.308</td>
            <td align="center" valign="top">.094</td>
            <td align="center" valign="top">.269</td>
            <td align="center" valign="top">3.261</td>
            <td align="center" valign="top">.001</td>
            <td align="center" valign="top">.749</td>
            <td align="center" valign="top">1.335</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>The above research results conclude that multicollinearity
    symptoms were not found because the tolerance values of each
    variable were greater than 0.10 and the VIF values were less than
    10. (Ghozali, 2018).</p>
  </sec>
  <sec id="heterocedastisity-test">
    <title>Heterocedastisity Test</title>
    <disp-quote>
      <p>Table 8. Heterocedastisity Test</p>
    </disp-quote>
    <table-wrap>
      <label>Table 8. Heterocedastity Test</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
        <p>a. Dependent Variable: ABRESID</p>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top" rowspan="2">Model</th>
            <th align="center" valign="top" colspan="2">Unstandardized Coefficients</th>
            <th align="center" valign="top" rowspan="2">Standardized Coefficients</th>
            <th align="center" valign="top" rowspan="2">t</th>
            <th align="center" valign="top" rowspan="2">Sig.</th>
          </tr>
          <tr>
            <th align="center" valign="top">B</th>
            <th align="center" valign="top">Std. Error</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top">(Constant)</td>
            <td align="center" valign="top">.863</td>
            <td align="center" valign="top">.291</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top">2.969</td>
            <td align="center" valign="top">.004</td>
          </tr>
          <tr>
            <td align="left" valign="top">1 Social Media</td>
            <td align="center" valign="top">-.075</td>
            <td align="center" valign="top">.060</td>
            <td align="center" valign="top">-.149</td>
            <td align="center" valign="top">-1.258</td>
            <td align="center" valign="top">.211</td>
          </tr>
          <tr>
            <td align="left" valign="top">E-WOM</td>
            <td align="center" valign="top">-.031</td>
            <td align="center" valign="top">.061</td>
            <td align="center" valign="top">-.056</td>
            <td align="center" valign="top">-.503</td>
            <td align="center" valign="top">.616</td>
          </tr>
          <tr>
            <td align="left" valign="top">Product Quality</td>
            <td align="center" valign="top">-.039</td>
            <td align="center" valign="top">.058</td>
            <td align="center" valign="top">-.074</td>
            <td align="center" valign="top">-.673</td>
            <td align="center" valign="top">.502</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>From the test results, it is known that each variable has a
    significance value above 0.05, which means that no
    heteroscedasticity was found. Therefore, the research can proceed to
    the next analysis process. (Ghozali, 2018)</p>
  </sec>
  <sec id="multiple-regression-analysis-test">
    <title>Multiple Regression Analysis Test</title>
    <disp-quote>
      <p>Table 9. Multiple Regression Analysis Test Coefficients<xref ref-type="fn" rid="tfn1">a</xref></p>
    </disp-quote>
    <table-wrap>
      <label>Table 9. Multiple Regression Analysis Test Coefficients<xref ref-type="fn" rid="tfn1">a</xref></label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
        <label>a.</label><p>Dependent Variable: KEPUTUSAN PEMBELIAN</p>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top" rowspan="2">Model</th>
            <th align="center" valign="top" colspan="2">Unstandardized Coefficients</th>
            <th align="center" valign="top" rowspan="2">Standardized Coefficients Beta</th>
            <th align="center" valign="top" rowspan="2">t</th>
            <th align="center" valign="top" rowspan="2">Sig.</th>
          </tr>
          <tr>
            <th align="center" valign="top">B</th>
            <th align="center" valign="top">Std. Error</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top">(Constant)</td>
            <td align="center" valign="top">.267</td>
            <td align="center" valign="top">.473</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top">.565</td>
            <td align="center" valign="top">.573</td>
          </tr>
          <tr>
            <td align="left" valign="top">1 Social Media</td>
            <td align="center" valign="top">.431</td>
            <td align="center" valign="top">.097</td>
            <td align="center" valign="top">.397</td>
            <td align="center" valign="top">4.455</td>
            <td align="center" valign="top">.000</td>
          </tr>
          <tr>
            <td align="left" valign="top">E-WOM</td>
            <td align="center" valign="top">.199</td>
            <td align="center" valign="top">.099</td>
            <td align="center" valign="top">.169</td>
            <td align="center" valign="top">2.011</td>
            <td align="center" valign="top">.047</td>
          </tr>
          <tr>
            <td align="left" valign="top">Product Quality</td>
            <td align="center" valign="top">.308</td>
            <td align="center" valign="top">.094</td>
            <td align="center" valign="top">.269</td>
            <td align="center" valign="top">3.261</td>
            <td align="center" valign="top">.001</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Y = 0.267 + 0.431X1 + 0.199X2 + 0.308X3</p>
    <p>The constant value (α) of 0.267 indicates that if the variables
    of social media, e- wom, and product quality are 0 or unchanged,
    then the purchase decision is 0.267.</p>
    <p>The explanation of the regression equation is as follows:</p>
    <p>β₁ = 0.431, which means that every 1-unit increase in social
    media will increase purchasing decisions by 0.431 units, assuming
    other independent variables remain constant.</p>
    <p>β₂ = 0.199, which indicates that every 1-unit increase in e-WOM
    will result in a 0.199-unit increase in purchase decisions if other
    variables remain unchanged.</p>
    <p>β₃ = 0.308, which indicates that a 1-unit increase in product
    quality will increase the purchase decision by 0.308 units if other
    independent variables remain constant.</p>
  </sec>
  <sec id="coefficient-of-determination-test-rU00B2">
    <title>Coefficient of Determination Test (R²)</title>
    <disp-quote>
      <p>Table 10. Coefficient of Determination Test (R²)</p>
    </disp-quote>
    <table-wrap>
      <label>Table 10.Coefficient of Determination Test (R<sup>2</sup>)</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
        <p>Model Summary</p>
        <label>a.</label><p>Predictors: (Constant), KUALITAS PRODUK, E-WOM, MEDIA SOSIAL</p>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="center" valign="top">Model</th>
            <th align="center" valign="top">R</th>
            <th align="center" valign="top">R Square</th>
            <th align="center" valign="top">Adjusted R Square</th>
            <th align="center" valign="top">Std. Error of the Estimate</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="center" valign="top">1</td>
            <td align="center" valign="top">.679<xref ref-type="fn" rid="tfn1">a</xref></td>
            <td align="center" valign="top">.462</td>
            <td align="center" valign="top">.446</td>
            <td align="center" valign="top">.26956</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>The adjusted R² value is 0.446 or 44.6%, indicating that 44.6% of
    the changes in the dependent variable (purchase decision) are
    influenced by the independent variables used in this study, namely
    Social Media, E-WOM, and Product Quality. In other words, this
    equation model can explain 44.6% of the variation in purchase
    decisions, while the remaining 55.4% is explained by external
    factors outside the variables used in this study. Additionally,
    based on the R-Square value of 0.462, the coefficient of
    determination is 46.2%. The R value of 0.679 indicates a
    relationship or correlation of 67.9% between the independent and
    dependent variables.</p>
  </sec>
  <sec id="f-test-goodness-of-fit">
    <title>F Test( Goodness of Fit)</title>
    <disp-quote>
      <p>Table 11. F test</p>
    </disp-quote>
    <table-wrap>
      <label>Table 11. F test</label>
      <caption>
        <title><italic>Source: processed data by SPSS 20</italic></title>
        <p>ANOVA<xref ref-type="fn" rid="tfn1">a</xref></p>
        <label>a.</label><p>Dependent Variable: KEPUTUSAN PEMBELIAN</p>
        <label>b.</label><p>Predictors: (Constant), KUALITAS PRODUK, E-WOM, MEDIA SOSIAL</p>
      </caption>
      <table>
        <thead>
          <tr>
            <th align="left" valign="top">Model</th>
            <th align="center" valign="top">Sum of Squares</th>
            <th align="center" valign="top">df</th>
            <th align="center" valign="top">Mean Square</th>
            <th align="center" valign="top">F</th>
            <th align="center" valign="top">Sig.</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td align="left" valign="top">1 Regression</td>
            <td align="center" valign="top">6.606</td>
            <td align="center" valign="top">3</td>
            <td align="center" valign="top">2.202</td>
            <td align="center" valign="top">30.306</td>
            <td align="center" valign="top">.000<xref ref-type="fn" rid="tfn2">b</xref></td>
          </tr>
          <tr>
            <td align="left" valign="top">Residual</td>
            <td align="center" valign="top">7.702</td>
            <td align="center" valign="top">106</td>
            <td align="center" valign="top">.073</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
          <tr>
            <td align="left" valign="top">Total</td>
            <td align="center" valign="top">14.309</td>
            <td align="center" valign="top">109</td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
            <td align="center" valign="top"></td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>From the results of the Goodness of Fit test using the F test
    referring to the ANOVA value, it is known that the model can be
    considered feasible if the significance value is less than 0.05.
    Based on the ANOVA results, a significance value of 0.000 indicates
    that this model is significant and can be used in research.</p>
  </sec>
  <sec id="t-test-hypothesis-test">
    <title>T Test (Hypothesis Test)</title>
    <p>This test is used to determine the effect of each independent
    variable (X) on the dependent variable (Y) (Ghozali, 2018). Based on
    the regression test results, the regression coefficient (β1) for the
    social media variable was 0.431 with a positive direction because β1
    &gt; 0. The calculated t-value is 4.455, which is greater than the
    table t-value of 1.658, and the significance level is 0.000, which
    is less than the significance level of 0.05 (α &lt; 0.05). Thus, the
    results indicate that social media has a positive and significant
    influence on purchasing decisions. Therefore, the first hypothesis
    (H1), which states that social media influences purchasing
    decisions, can be accepted.</p>
    <p>The regression test results show that the regression coefficient
    (β2) value for the electronic word of mouth (e-WOM) variable is
    0.199 with a positive direction because β2 &gt; 0. The calculated
    t-value of 2.011 is greater than the table t-value of 1.658, and the
    significance level is 0.047, which is smaller than the significance
    level of 0.05 (α &lt; 0.05). Thus, the positive coefficient value
    and the significant t-test result indicate that e-WOM has a positive
    and significant effect on purchasing decisions. Therefore, the
    second hypothesis (H2) is accepted.</p>
    <p>The regression analysis results show that the regression
    coefficient (β3) for the product quality variable is 0.308 with a
    positive direction because β3 &gt; 0. The calculated t-value of
    3.261 is greater than the table t-value of 1.658, and the
    significance value is 0.001, which is less than the significance
    level of 0.05 (α &lt; 0.05). Thus, these results indicate that
    product quality has a positive and significant effect on purchasing
    decisions. Therefore, the third hypothesis (H3) can be accepted.</p>
  </sec>
</sec>









<sec>
  <title>DISCUSSION</title>
  <sec id="the-influence-of-social-media-on-purchasing-decisions">
    <title>The Influence of Social Media on Purchasing Decisions</title>
    <p>Statistical analysis results show that social media has a
    positive and significant effect on Donlight customers' purchasing
    decisions. This is supported by findings that the better Donlight's
    social media management, the higher the</p>
    <p>tendency for customers to make purchases. This finding aligns
    with the Stimulus- Organism-Response (S-O-R) concept, where social
    media acts as a stimulus that influences consumers (organism) in
    making purchasing decisions.</p>
    <p>In addition to being a promotional tool, social media also serves
    to build interaction between companies and customers. Satisfaction
    with a product encourages consumers to provide testimonials or
    recommendations through social media, strengthening the role of
    social media in the purchasing decision- making process. In its
    implementation, Donlight leverages social media to connect with
    potential customers through the presentation of engaging,
    educational, and interactive content. Social media serves as an
    effective communication tool as it can evoke emotions and spark
    consumer interest in products. With the right social media strategy,
    consumer interest in purchasing products will continue to grow.</p>
    <p>These results are consistent with previous research by Andhyka et
    al. (2024), Puirih et al. (2020), Shadrina &amp; Sulistyanto (2022),
    Prasetyo et al. (2021), Riskyady &amp; Sulistyowati (2021), as well
    as Ningrum et al. (2023), which states that social media has a
    positive and significant influence on purchasing decisions. Thus, it
    can be concluded that social media is one of the main factors that
    positively and significantly influences Donlight consumers'
    purchasing decisions.</p>
  </sec>
  <sec id="the-influence-of-e-wom-on-purchasing-decisions">
    <title>The Influence of E-WOM on Purchasing Decisions</title>
    <p>The results of statistical analysis indicate that the second
    hypothesis (H2) is accepted, which means that E-WOM has a positive
    and significant effect on Donlight customers' purchasing decisions.
    This finding is reinforced by the analysis results showing that
    E-WOM is more effective than conventional word- of-mouth (WOM)
    communication. Through advancements in digital technology, E-WOM can
    disseminate product information more quickly and widely. This
    finding aligns with the Stimulus-Organism-Response (S-O-R) theory,
    where E- WOM acts as a stimulus influencing consumers in making
    purchasing decisions. With E-WOM, consumers not only obtain
    information from their surroundings but can also access other users'
    experiences from various sources, thereby increasing trust and
    encouraging purchasing decisions.</p>
    <p>The results of this study are in line with the findings of
    previous studies by Rahmadani et al. (2024), Waringga et al. (2023),
    Nyoko &amp; Semuel (2021),Abdurrahman &amp; Ayuningsih (2020), as
    well as Inayati et al. (2022), which also states that E-WOM has a
    positive and significant effect on purchasing decisions. Thus, it
    can be concluded that E-WOM is one of the effective marketing
    communication strategies for Donlight in increasing consumer
    purchasing decisions.</p>
  </sec>
  <sec id="the-influence-of-product-quality-on-purchasing-decisions">
    <title>The Influence of Product Quality on Purchasing
    Decisions</title>
    <p>Based on statistical results, the third hypothesis (H3) was
    accepted, which means that product quality has a positive and
    significant effect on Donlight consumers' purchasing decisions. This
    finding is supported by an analysis showing that product quality is
    closely related to its ability to meet good quality standards.
    Factors such as product performance, functional accuracy,
    durability,</p>
    <p>ease of maintenance, and consistency are the main determinants of
    product quality. Product quality is an important element in shaping
    customer satisfaction levels. High-quality products are expected not
    only to meet customer expectations but also to compete with or even
    surpass the quality of competitors' products. Satisfaction with
    high-quality products encourages customers to make repeat purchases
    or recommend them to others. This finding aligns with the
    Stimulus-Organism-Response (S-O-R) theory, where product quality
    acts as a stimulus that influences customer response. When customers
    receive products that meet their expectations, it evokes feelings of
    satisfaction and joy, and encourages the desire to make repeat
    purchases. In the long term, customers may become loyal or recommend
    the product to others.</p>
    <p>The results of this study are consistent with previous studies
    conducted by Lutfila Roibafi et al. (2022), Juwita (2021),Grandhis
    (2022),Mulia &amp; Risnawati (2020), Shah et al. (2023), Sunarsi
    (2020), as well as Mappatompo &amp; Rizal (2023), which also shows
    that product quality has a positive and significant effect on
    purchasing decisions. However, there are other research results by
    Sintya et al. (2024) dan Wijiastuti et al. (2024) which showed
    different results. Thus, it can be concluded that product quality
    plays an important role in influencing Donlight consumers'
    purchasing decisions, particularly in building customer satisfaction
    and loyalty.</p>
  </sec>
</sec>






<sec>
  <title>CONCLUSIONS AND RECOMMENDATIONS</title>
  <p>According to the research and discussion, this study concludes that
  social media, electronic word of mouth (E-WOM), and product quality
  positively and significantly influence consumer purchasing decisions.
  This study has limitations in terms of the relatively short time frame
  of its implementation, so data collection was only carried out during
  a specific period and was unable to capture the dynamics or changes in
  consumer behaviour in the long term.</p>
</sec>







<sec>
  <title>ADVANCED RESEARCH</title>
  <p>Social media, electronic word of mouth (E-WOM) and product quality
  are three factors discussed in this study in relation to purchasing
  decisions. With 110 respondents, the results of the study are not
  sufficient to describe the actual situation. Therefore, further
  studies are recommended to increase the sample size to obtain more
  optimal, relevant, and representative results. Additionally, future
  researchers are encouraged to include other variables such as
  promotional prices and other factors that may influence purchasing
  decisions to enrich the analysis results. Donlight should continue to
  strategically utilise platforms like Instagram and TikTok through
  engaging content to increase product interaction and visibility.
  Furthermore, Donlight should manage consumer reviews effectively,
  encourage positive feedback, and respond promptly to criticism to
  build customer trust. In addition to digital promotions, maintaining
  consistent product quality is crucial for enhancing customer
  satisfaction and loyalty, while also strengthening positive electronic
  word of mouth (E-WOM).</p>
</sec>







<sec>
  <title>ACKNOWLEDGMENT</title>
  <p>The author expresses his sincere gratitude to all parties who have
  contributed to the writing of this article. The author also thanks his
  supervisor and examiners, as well as the Faculty of Economics and
  Business, Muhammadiyah University Purwokerto, for their guidance and
  advice.</p>
</sec>









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