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<article xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" article-type="research-article"><front><journal-meta><journal-id journal-id-type="issn">2808-0718</journal-id><journal-title-group><journal-title>Indonesian Journal of Business Analytics (IJBA)</journal-title><abbrev-journal-title>Indonesian Journal of Business Analytics (IJBA)</abbrev-journal-title></journal-title-group><issn pub-type="epub">2808-0718</issn><issn pub-type="ppub">2808-0718</issn><publisher><publisher-name>Formosa Publisher</publisher-name><publisher-loc>Jl. Sutomo Ujung No.28 D, Durian, Kecamatan Medan Timur, Kota Medan, Sumatera Utara 20235, Indonesia.</publisher-loc></publisher></journal-meta><article-meta><article-categories><subj-group><subject>10.55927/ijba.v5i3.14602</subject></subj-group></article-categories><title-group><article-title>The  Influence  of  Brand  Image,  Packaging  Blister  and  Product  Placement  in 
 Korean Dramas on Kopiko Candy Purchase Decisions</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Suestri</surname></name></contrib><contrib contrib-type="author"><name><surname>Riyanti</surname><given-names>Sri</given-names></name></contrib><contrib contrib-type="author"><name><surname>Astuti</surname><given-names>amlah Puji</given-names></name></contrib></contrib-group><pub-date date-type="collection" iso-8601-date="2025-6-12"><day>12</day><month>6</month><year>2025</year></pub-date><volume>5</volume><issue>3</issue><issue-title>The  Influence  of  Brand  Image,  Packaging  Blister  and  Product  Placement  in  Korean Dramas on Kopiko Candy Purchase Decisions</issue-title><fpage>2601</fpage><lpage>2747</lpage><history><date date-type="received" iso-8601-date="2025-4-21"><day>21</day><month>4</month><year>2025</year></date><date date-type="rev-recd" iso-8601-date="2025-5-16"><day>16</day><month>5</month><year>2025</year></date><date date-type="accepted" iso-8601-date="2025-6-21"><day>21</day><month>6</month><year>2025</year></date></history><permissions><copyright-holder>Formosa Publisher</copyright-holder><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://journal.formosapublisher.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 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><self-uri xlink:href="https://journal.formosapublisher.org/index.php/ijba" xlink:title="The  Influence  of  Brand  Image,  Packaging  Blister  and  Product  Placement  in   Korean Dramas on Kopiko Candy Purchase Decisions">The  Influence  of  Brand  Image,  Packaging  Blister  and  Product  Placement  in 
 Korean Dramas on Kopiko Candy Purchase Decisions</self-uri><abstract><p>One of the many strategies implemented by Kopiko candy to expand its market reach is product placement  in  Korean  dramas.  This  study  aims  to investigate  and  examine  the  influence  of  brand image, blister packaging, and product placement in Korean dramas on  the purchasing decisions of Kopiko  candy.  This  is  an  associative  study  using quantitative  data.  The  population  in  this  study consists of Indonesian individuals who have purchased Kopiko candy and have watched Korean dramas. The sample size is 100 individuals, selected using purposive sampling with the following  criteria:  Indonesian  citizens  who  have bought Kopiko at least once and have watched one or more of the following Korean dramas: Vincenzo, Hometown  Cha-Cha-Cha,  Yumi's  Cells,  Mine,  Little Women, Today's Webtoon, and Taxi Driver. The analysis method used is multiple linear regression analysis.  The  findings  of  the  study  indicate  that overall, brand image, blister packaging, and product placement in Korean dramas have a significant and positive influence on Kopiko candy purchasing decisions. When analyzed partially, each variable—brand image, blister packaging, and product  placement—also  shows  a  significant  and positive impact on purchasing decisions.</p></abstract><kwd-group><kwd>Brand Image</kwd><kwd>Packaging Blister</kwd><kwd>Product Placement</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>File created by JATS Editor</meta-name><meta-value><ext-link ext-link-type="uri" xlink:href="https://jatseditor.com" xlink:title="JATS Editor">JATS Editor</ext-link></meta-value></custom-meta><custom-meta><meta-name>issue-created-year</meta-name><meta-value>2025</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec><title>INTRODUCTION</title><p>In the era of globalization, marketing strategies have undergone significant transformations, one of which is the utilization of entertainment media such as Korean dramas, which have a considerable influence on popular culture. According to research by Putri et al. (2023), when consumers perceive product placements more positively, their brand awareness tends to increase. This finding emphasizes that product placement strategies in dramas can strengthen brand presence, especially in global markets.</p><p>This phenomenon is further reinforced by the popularity of the Hallyu Wave (Korean Wave), which influences consumer preferences not only in South Korea but also internationally, including in Indonesia. Consumers perceive brands featured in dramas as having added value, as they are associated with high quality, global trends, and celebrity lifestyles. In the context of Korean dramas, brands consistently shown in positive scenarios can create strong emotional associations, thereby influencing consumer purchasing decisions.</p><p>Kopiko's blister packaging, as a modern packaging form, not only serves to protect the product but also to attract consumer attention. Visually appealing designs can enhance a product's attractiveness and influence consumer preferences. In Korean dramas, products with attractive packaging are often highlighted, providing an aesthetic appeal that can shape perceptions and purchase decisions.</p><p>Kopiko's blister packaging, as a modern packaging form, not only serves to protect the product but also to attract consumer attention. Visually appealing designs can enhance a product's attractiveness and influence consumer preferences. In Korean dramas, products with attractive packaging are often highlighted, providing an aesthetic appeal that can shape perceptions and purchase decisions.</p><p>Product placement has become one of the most effective marketing methods for introducing brands to a wider audience through product integration into Korean drama scenes.</p><p>This phenomenon can be observed in the case of the Indonesian local product Kopiko, produced by PT Mayora Tbk, which successfully entered the international market and appeared in several widely viewed Korean dramas, such as Vincenzo, Hometown Cha-Cha-Cha, and others. Before the implementation of the product placement strategy, Kopiko was known mainly as a local candy brand. However, after its appearance in globally popular Korean dramas, there have been reports of a significant increase in sales.</p><p>Referring to PT Mayora Tbk’s financial performance, as accessed from the website databoks.katadata.co.id, in 2020 the company experienced a sales decline to IDR 24.5 trillion from IDR 25 trillion in 2019. However, in 2021, sales rose to approximately IDR 27.9 trillion.</p><sec><title>Table 1. PT Mayora Financial Performance Data</title><table-wrap id="table-pd2zyu"><label>Table 1. PT Mayora Financial Performance Data</label><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Year</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Sales Volume</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2019</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>IDR 25 Trillion</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2020</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>IDR 24.5 Trillion</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2021</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>IDR 27.9 Trillion</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Source: databoks.katadata.co.id</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/></tr></tbody></table></table-wrap><p>Although product placement in Korean dramas has become an increasingly popular marketing strategy, there is still limited research that specifically analyzes how consumer perceptions of Kopiko change after seeing the product in Korean dramas. Kopiko, as an Indonesian candy brand, has appeared in several popular Korean dramas, potentially increasing its brand image and appeal in the global market.</p><p>However, there are still few studies exploring to what extent Kopiko’s appearance in Korean dramas influences consumer perception. It also remains unclear whether such product placement creates a lasting brand image change or merely influences short-term purchasing decisions. Further in-depth research is needed to determine whether the impact of product placement is more significant among certain segments, such as teenagers or K-drama fans, compared to the general public.</p><p>Understanding these perception changes can help Kopiko optimize its marketing strategy and evaluate the effectiveness of product placement compared to other marketing methods in building brand image.</p><p>This study aims to analyze the influence of brand image, blister packaging, and product placement in Korean dramas on Kopiko candy purchasing decisions. The core of this research focuses on the relationship between consumer brand perception, popular culture influence, and the effectiveness of marketing strategies through Korean dramas. Understanding these factors is expected to provide valuable insights for industry players in designing innovative and relevant marketing strategies.</p></sec></sec><sec><title>LITERATURE REVIEW</title><sec><title>Brand Image</title><p>Brand image is defined as the perceptions and beliefs of customers reflected in the associations formed in their memory (Kotler &amp; Keller, 2023; Megar Damanik et al., 2023). This collection of information enables consumers to choose between competing brands that offer similar products. By providing information, convincing consumers, and indirectly reminding them about the product brand being marketed, marketing communication helps build brand image and ultimately boosts sales.</p><p>Brand image is also defined as “the consumer’s reinterpretation of the overall brand image formed through information and past experiences with the brand” (Coaker, Thrape, Simonson, Schmitt, &amp; Sudirman, 2022). At the same time, a product’s image in a person’s mind represents the overall mental representation of that product (Kotler &amp; Fox, as cited in Duad, 2021).</p><p>A strong brand image offers various benefits, such as strengthening customer loyalty, building trust, and creating competitive advantage in the market. Conversely, a weak or inconsistent brand image can hinder business development and reduce consumer interest in the products or services offered. Blister Packaging</p><p>Blister packaging is a type of packaging that uses transparent plastic sheets, which are heated and formed into cavities according to the shape of the product. According to Czerwinski <xref ref-type="bibr" rid="">(Ropikoh et al., 2024)</xref>, packaging functions to protect and wrap the product to prevent it from being damaged. To ensure product quality is maintained and safe delivery to customers, the packaging must be compatible with the type of product.</p></sec><sec><title>Product Placement</title><p>According to George E. Belch and Michael A. Belch <xref ref-type="bibr" rid="">(Nadeak &amp;</xref> <xref ref-type="bibr" rid="">Setiawan, 2024)</xref>, product placement is a marketing strategy that involves inserting a product into a scene or storyline of a film, so that the audience unconsciously becomes aware of the product’s presence. This method aims to introduce the product subtly to consumers without appearing as explicit advertising, thus creating a strong emotional connection between the product and the audience, since the product is associated with the storyline.</p></sec><sec><title>Purchase Decision</title><p>According to Arif &amp; Yani (2023), a purchase decision is one of the stages in the decision-making process prior to the post-purchase phase. At this stage, consumers are faced with various alternatives and must decide whether to purchase the product based on the considered options. Meanwhile, according to Kastori <xref ref-type="bibr" rid="">(Dewi, 2017)</xref>, a purchase decision is the process involving an individual in deciding and choosing to buy the product offered by the seller.</p></sec></sec><sec><title>RESEARCH METHODOLOGY</title><p>This study utilizes a quantitative model, employing both population and sample, and uses a questionnaire as a research tool. The data is then analyzed for the purpose of hypothesis testing. The population in this study consists of Indonesian individuals who have watched Korean dramas and purchased Kopiko candy.</p><sec><title>Research Design</title><p>The influence of Brand Image and Product Placement on the purchase decision of Kopiko candy can be illustrated as follows:</p></sec><sec><title>Data Collection Techniques</title><p>This study uses a quantitative approach to collect data through surveys distributed to participants who have watched Korean dramas and purchased Kopiko candy. According to Creswell <xref ref-type="bibr" rid="">(Kusumastuti et al., 2020)</xref>, the quantitative research model is used to test specific theories by analyzing the relationships between different variables.</p><p>In non-probability sampling, researchers do not assume that every individual in the population has an equal chance of being selected as a sample. This study employs a purposive sampling technique. This method involves selecting samples based on predefined criteria or judgment that aligns with the research requirements.</p><p>The sample criteria in this study include:</p><list list-type="bullet"><list-item><p>Individuals who have watched Korean dramas</p></list-item><list-item><p>Consumers of Kopiko candy</p></list-item><list-item><p>Age range between 15 and 30 years old</p></list-item></list><p>The respondents' level of agreement is measured using a Likert scale, ranging from 1 to 5. Since the exact percentage of people who watch Korean dramas is unknown, the Lemeshow formula (1997) is used to determine the sample size for this study.</p><p>Below is the method used by the researcher to determine the sample size:</p><p>n = z2 p q / d2</p><p>Information :</p><p>n : Total sample</p><p>z : Standard score = 1.96</p><p>p : Maximun Estimate = 50% = 0.5</p><p>d : Alpha = 0,10 or Sampling error = 10% Known :</p><p>n =</p><p>0,1<sup>2</sup></p><p>3,8416 . 0,5 (1-0,5)</p><p>n =</p><p>0,1<sup>2</sup></p><p>n = 0,9604</p><p>0,01</p><p>n = 96</p><p>Then the researcher obtained the minimum total sample needed in this study, which was 96 respondents and would be rounded up to 100 participants by the researcher. The researcher used the lemeshow formula (1997) considering that the population of Korean drama viewers is very large and has a diverse age range.</p></sec><sec><title>Analytical Tools Validity Test</title><p>This is a measurement that describes the level of accuracy of an instrument. Therefore, validity testing is related to how well an instrument can perform its function optimally (S &amp; Sumartik, 2022).</p></sec><sec><title>Reliability Test</title><p>Reliability refers to the extent to which a test can consistently measure an object. Reliability is expressed in numerical values, typically in the form of a coefficient. The higher the coefficient, the greater the reliability. Additionally, reliability also refers to the consistency of findings during repeated observations and calculations of a fact or phenomenon over different time periods (S &amp; Sumartik, 2022).</p></sec><sec><title>Classical Assumption Test</title><p>Prior to doing hypothesis testing, the acceptability of a regression model from an econometric standpoint is assessed using traditional assumption tests. Autocorrelation, heteroscedasticity, multicollinearity, and normalcy tests are some of these tests.</p></sec><sec><title>Normality Test</title><p>For the traditional assumption tests to produce accurate findings, it is essential to make sure the data has a normal distribution. Several methods, including probability plots, histogram analysis, and the Kolmogorov–Smirnov test, can be used to confirm normality.</p><p>According to the Kolmogorov–Smirnov test, the data is deemed normally distributed if the Asymp. Sig. (2-tailed) score is higher than 0.05. On the other hand, if a histogram test produces a symmetrical bell-shaped curve, it implies a normal distribution. The data is also regarded as normal if the points in the probability plot are evenly spaced around the diagonal line.</p></sec><sec><title>Multicollinearity Test</title><p>To find correlations between independent variables, the multicollinearity test is used. If the test results indicate a Variance Inflation Factor (VIF) &lt; 10 and a Tolerance score &gt; 0.10, the regression model is free of multicollinearity.</p></sec><sec><title>Heteroscedasticity Test</title><p>In a regression model, the heteroscedasticity test establishes whether the variance of the residuals changes among observations. This test can be carried out using a scatter plot and the Glejser test.</p><p>It is possible to conclude that the model is heteroscedastic if the scatter plot's points do not exhibit any discernible patterns. The Glejser test states that if the independent variables' significance value is more than 0.05, the model is said to be heteroscedastic.</p></sec><sec><title>Multiple Linear Regression Test</title><p>The Multiple Linear Regression Test is used in this investigation. The link between one dependent variable (Y) and multiple independent variables (X1, X2, X3) is investigated using this statistical method, which is called multiple linear regression analysis.</p><p>Determining the degree to which independent factors impact the dependent variable is the primary goal of the multiple linear regression test. A multiple linear regression model can be created by applying the following formula:</p><p>Y = a + β1X1 +β 2X2 + β3X3 + e</p><p>a : Constant (Value Y when all X = 0)</p><p>Regression coefficients β1, β2, and β3 indicate how much each independent variable</p><p>influences the dependent.</p><p>e : Error or interference, namely other variables that are not included in the model.</p><p>Hypothesis Testing</p></sec><sec><title>The F-test (simultaneous test), t-test (partial test), and coefficient of determination test are examples of hypothesis testing.</title><p>Coefficient of Determination Test</p><p>Researchers utilize the coefficient of determination, sometimes referred to as Adjusted R Square, to assess how well the independent factors in a model explain the dependent variable. This test's results are given as a percentage, which can be anywhere from more than 0% to less than 100%.</p><sec><title>F-Test (Simultaneous Test)</title><p>To ascertain if two or more independent variables have a simultaneous impact on the dependent variable, the F-test is utilized. If the estimated F-value is higher than the F-table value and the significance level is less than 0.05, independent variables are generally regarded as having a substantial impact on the dependent variable.</p></sec><sec><title>t-Test (Partial Test)</title><p>A t-test should be used to investigate the effects of each independent variable separately on the dependent variable. If the estimated t-value is higher than the t-table value and the significance level is less than 0.05, the independent variable is said to have a substantial impact on the dependent variable.</p></sec></sec></sec><sec><title>RESULTS AND DISCUSSION</title><sec><title>Respondent Description</title><p>The respondents are individuals who consume Kopiko candy and have watched Korean dramas. The study is titled The Influence of Brand Image, Blister Packaging, and Product Placement in Korean Dramas on the Purchase Decision of Kopiko Candy. A total of 100 participants completed the questionnaire, which was distributed online.</p></sec><sec><title>Table 2. Respondents’ Age</title><table-wrap id="table-w29fsl"><label>Table 2. Respondents’ Age</label><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Age Group</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Percentage of Respondents</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>15 – 18 Years</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>3.2%</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>19 – 25 Years</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>96%</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>26 – 30 Years</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.8%</p></td></tr></tbody></table></table-wrap><p>Source: Research Results (2025)</p></sec><sec><title>Table 3. Respondents’ Gender</title><table-wrap id="table-8omxgh"><label>Table 3. Respondents’ Gender</label><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Gender</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Percentage of Respondents</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Female</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>81.6%</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Male</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>18.4%</p></td></tr></tbody></table></table-wrap><p>Source: Research Results (2025)</p><p>Validity test</p></sec><sec><title>Table 4. Validity Test</title><table-wrap id="table-2kevw2"><label>Table 4. Validity Test</label><table frame="box" rules="all"><thead><tr><th colspan="7" rowspan="1" style="" align="left" valign="top">Correlations</th></tr></thead><tbody><tr><td colspan="2" rowspan="1" style="" align="left" valign="top"><p/></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X1</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X2</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X3</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Y</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Total</td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">X1</td><td colspan="1" rowspan="1" style="" align="left" valign="top">The Pearson Correlation</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,430**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,010</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,233*</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,606**</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Sig. (2-tailed)</td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,919</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,020</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">N</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">X2</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pearson</p><p>Correlation</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,430**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,234*</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,401**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,750**</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Sig. (2-tailed)</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,019</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">N</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">X3</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pearson</p><p>Correlation</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,010</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,234*</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,674**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,684**</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Sig. (2-tailed)</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,919</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,019</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">N</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">Y</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pearson</p><p>Correlation</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,233*</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,401**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,674**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,774**</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Sig. (2-tailed)</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,020</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">N</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">Total</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pearson</p><p>Correlation</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,606**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,750**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,684**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,774**</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Sig. (2-tailed)</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">N</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100</p></td></tr><tr><td colspan="7" rowspan="1" style="" align="left" valign="top">**. Correlation is significant at the 0.01 level (2-tailed).</td></tr><tr><td colspan="7" rowspan="1" style="" align="left" valign="top">*. Correlation is significant at the 0.05 level (2-tailed).</td></tr></tbody></table></table-wrap><p>Source: Research Results (2025)</p><p>If you look at the table above, the significance score (Sig) ≤ 0.05 means it is valid.</p><p>Reliability Test.</p></sec><sec><title>Table 2. Reliability Test</title><table-wrap id="table-f1krjd"><label>Table 2. Reliability Test</label><table frame="box" rules="all"><thead><tr><th colspan="2" rowspan="1" style="" align="left" valign="top">Reliability Statistics</th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Cronbach's</p><p>Alpha</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><break/><p>N of Items</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">,621</td><td colspan="1" rowspan="1" style="" align="left" valign="top">4</td></tr></tbody></table></table-wrap><p>Source 1: Research Results (2025)</p><p>If you look at the table above, the Cronbach's Alpha score ≥ 0.6 can be said to be</p><p>reliable.</p></sec><sec><title>Classical Assumption Test</title><p>Normality Test</p></sec><sec><title>Table 3 Normality Test Results</title><table-wrap id="table-jw2tm3"><label>Table 3 Normality Test Results</label><table frame="box" rules="all"><thead><tr><th colspan="3" rowspan="1" style="" align="left" valign="top">One-Sample Kolmogorov-Smirnov Test</th></tr></thead><tbody><tr><td colspan="2" rowspan="1" style="" align="left" valign="top"><p/></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Unstandardized Residual</td></tr><tr><td colspan="2" rowspan="1" style="" align="left" valign="top">N</td><td colspan="1" rowspan="1" style="" align="left" valign="top">100</td></tr><tr><td colspan="1" rowspan="2" style="" align="left" valign="top">Normal Parameters<sup>a,b</sup></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Mean</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,0000000</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Std.</p><p>Deviation</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">1,05393571</td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">Most Extreme Differences</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Absolute</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,086</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Positive</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,048</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Negative</td><td colspan="1" rowspan="1" style="" align="left" valign="top">-,086</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Test Statistic</td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top">,086</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Asymp. Sig. (2-tailed)</td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top">,063c</td></tr><tr><td colspan="3" rowspan="1" style="" align="left" valign="top">a. Test distribution is Normal.</td></tr><tr><td colspan="3" rowspan="1" style="" align="left" valign="top">b. Calculated from data.</td></tr><tr><td colspan="3" rowspan="1" style="" align="left" valign="top">c. Lilliefors Significance Correction.</td></tr></tbody></table></table-wrap><p>Source: Research Results (2025)</p><p>Asymp. Sig. (2-tailed) and the probability score (p) are shown in the above table at 0.063 &gt; 0.05. The Kolmogorov-Smirnov test indicates that the residual data is normally distributed since the value is greater than the 5% significance threshold (0.005). Furthermore, the residual data is said to have a normal distribution.</p><p>Multicollinearity Test</p></sec><sec><title>Table 4. Multicollinearity Test Results</title><table-wrap id="table-z8s7sy"><label>Table 4. Multicollinearity Test Results</label><table frame="box" rules="all"><thead><tr><th colspan="9" rowspan="1" style="" align="left" valign="top">Coefficientsa</th></tr></thead><tbody><tr><td colspan="2" rowspan="2" style="" align="left" valign="top"><p>Model</p><break/><break/><break/></td><td colspan="2" rowspan="1" style="" align="left" valign="top"><p>Unstandardized Coefficients</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Standardized Coefficients</td><td colspan="1" rowspan="2" style="" align="left" valign="top"><p>t</p></td><td colspan="1" rowspan="2" style="" align="left" valign="top"><p>Sig.</p></td><td colspan="2" rowspan="1" style="" align="left" valign="top">Collinearity Statistics</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>B</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Std. Error</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Beta</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Tolerance</td><td colspan="1" rowspan="1" style="" align="left" valign="top">VIF</td></tr><tr><td colspan="1" rowspan="4" style="" align="left" valign="top">1</td><td colspan="1" rowspan="1" style="" align="left" valign="top">(Constant)</td><td colspan="1" rowspan="1" style="" align="left" valign="top">14,582</td><td colspan="1" rowspan="1" style="" align="left" valign="top">2,116</td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>6,890</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Brand Image</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,092</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,050</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,144</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1,850</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,067</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">,806</td><td colspan="1" rowspan="1" style="" align="left" valign="top">1,240</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Packaging</p><p>Blister</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">,119</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,049</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,193</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2,417</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,018</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">,762</td><td colspan="1" rowspan="1" style="" align="left" valign="top">1,312</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Product</p><p>Placement</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">,358</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,041</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,628</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>8,711</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">,935</td><td colspan="1" rowspan="1" style="" align="left" valign="top">1,069</td></tr><tr><td colspan="9" rowspan="1" style="" align="left" valign="top">a. Dependent Variable: Purchase Decision</td></tr></tbody></table></table-wrap><p>Source: Research Results (2025)</p><p>It can be concluded that:</p><p>Tolerance value X1 0.806 ≥ 0.100, X2 0.762 ≥ 0.100 and X3 0.935 ≥ 0.100</p><p>VIF value X1 1.240 ≤ 10.00, X2 1.312 ≤ 10.00 and X3 1.069 ≤ 10.00</p><p>So it can be said that there is no Multicollinearity.</p><p>Heteroscedasticity Test</p></sec><sec><title>Table 5. Heteroscedasticity Test Results</title><table-wrap id="table-de8j5h"><label>Std. Error</label><table frame="box" rules="all"><thead><tr><th colspan="7" rowspan="1" style="" align="left" valign="top">Coefficientsa</th></tr></thead><tbody><tr><td colspan="2" rowspan="2" style="" align="left" valign="top"><break/><break/><p>Model</p><break/></td><td colspan="2" rowspan="1" style="" align="left" valign="top"><p>Unstandardized Coefficients</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Standardized Coefficients</td><td colspan="1" rowspan="2" style="" align="left" valign="top">t</td><td colspan="1" rowspan="2" style="" align="left" valign="top">Sig.</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">B</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Std. Error</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Beta</td></tr><tr><td colspan="1" rowspan="4" style="" align="left" valign="top">1</td><td colspan="1" rowspan="1" style="" align="left" valign="top">(Constant)</td><td colspan="1" rowspan="1" style="" align="left" valign="top">1,259</td><td colspan="1" rowspan="1" style="" align="left" valign="top">1,385</td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,909</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,366</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Brand Image</td><td colspan="1" rowspan="1" style="" align="left" valign="top">-,013</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,033</td><td colspan="1" rowspan="1" style="" align="left" valign="top">-,046</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>-,405</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,687</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Packaging Blister</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,022</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,032</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,079</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,680</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,498</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Product</p><p>Placement</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">-,023</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,027</td><td colspan="1" rowspan="1" style="" align="left" valign="top">-,088</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>-,838</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,404</p></td></tr><tr><td colspan="7" rowspan="1" style="" align="left" valign="top">a. Dependent Variable: ABS_RES</td></tr></tbody></table></table-wrap><p>Source: Research Results (2025)</p><p>If we look at the table above, the Sig value ≥ 0.05, so it can be concluded that the</p><p>data does not show any symptoms of heteroscedasticity.</p><p>Hypothesis Testing</p></sec><sec><title>Coefficient of Determination Test</title><p>Table 6. Results of the Determination Coefficient Test</p><table-wrap id="table-6"><label>Table 6. Results of the Determination Coefficient Test</label><table frame="box" rules="all"><thead><tr><th colspan="5" rowspan="1" style="" align="left" valign="top">Model Summary</th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><break/><p>Model</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><break/><p>R</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>R Square</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Adjusted R Square</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Std. Error of</p><p>the Estimate</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">1</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,731a</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,534</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,519</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1,070</p></td></tr><tr><td colspan="5" rowspan="1" style="" align="left" valign="top"><p>a. Predictors: (Constant), Product Placement, Brand</p><p>Image, Packaging Blister</p></td></tr></tbody></table></table-wrap><p>Source 2: Research Results (2025)</p><p>It is known that the Adjusted R Square score of 0.534 (53.4%) assumes that the purchasing decision variable can be influenced by Brand Image, Packaging Blister, and Product Placement by 53.4%. Meanwhile, (46.6%) others are influenced by other causes besides there is this study.</p><p>Uji F</p></sec><sec><title>Table 7. F Test Results</title><table-wrap id="table-4pw95e"><label>Table 7. F Test Results</label><table frame="box" rules="all"><thead><tr><th colspan="7" rowspan="1" style="" align="left" valign="top">ANOVAa</th></tr></thead><tbody><tr><td colspan="2" rowspan="1" style="" align="left" valign="top"><p>Model</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Sum of Squares</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>df</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Mean Square</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">F</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Sig.</td></tr><tr><td colspan="1" rowspan="3" style="" align="left" valign="top">1</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Regression</td><td colspan="1" rowspan="1" style="" align="left" valign="top">125,993</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>3</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>41,998</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>36,663</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000b</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Residual</td><td colspan="1" rowspan="1" style="" align="left" valign="top">109,967</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>96</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1,145</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Total</td><td colspan="1" rowspan="1" style="" align="left" valign="top">235,960</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>99</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/></tr><tr><td colspan="7" rowspan="1" style="" align="left" valign="top">a. Dependent Variable: Keputusan Pembelian</td></tr><tr><td colspan="7" rowspan="1" style="" align="left" valign="top"><p>b. Predictors: (Constant), Product Placement, Brand Image, Packaging</p><p>Blister</p></td></tr></tbody></table></table-wrap><p>Source 3: Research Results (2025)</p><p>If we look at the table above, we can conclude that the significance value (sig) is 0.00 ≤ 0.05, so simultaneously there is an influence of variable X on variable Y.</p></sec><sec><title>Uji T</title><table-wrap id="table-8"><label>Table 8. T-Test Results</label><table frame="box" rules="all"><thead><tr><th colspan="7" rowspan="1" style="" align="left" valign="top">Coefficientsa</th></tr></thead><tbody><tr><td colspan="2" rowspan="2" style="" align="left" valign="top"><p>Model</p><break/></td><td colspan="2" rowspan="1" style="" align="left" valign="top"><p>Unstandardized Coefficients</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Standardized Coefficients</td><td colspan="1" rowspan="2" style="" align="left" valign="top">t</td><td colspan="1" rowspan="2" style="" align="left" valign="top">Sig.</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">B</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Std. Error</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Beta</td></tr><tr><td colspan="1" rowspan="4" style="" align="left" valign="top">1</td><td colspan="1" rowspan="1" style="" align="left" valign="top">(Constant)</td><td colspan="1" rowspan="1" style="" align="left" valign="top">14,582</td><td colspan="1" rowspan="1" style="" align="left" valign="top">2,116</td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>6,890</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Brand Image</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,092</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,050</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,144</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1,850</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,067</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top">Packaging Blister</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,119</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,049</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,193</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2,417</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,018</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Product</p><p>Placement</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">,358</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,041</td><td colspan="1" rowspan="1" style="" align="left" valign="top">,628</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>8,711</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>,000</p></td></tr><tr><td colspan="7" rowspan="1" style="" align="left" valign="top">a. Dependent Variable: Purchase Decision</td></tr></tbody></table></table-wrap><p>Source 4: Research Results (2025)</p><p>If we look at the table above, it shows a significance score (sig) of 0.00 ≤</p><p>0.05, indicating that variable X has a significant influence on variable Y.</p></sec></sec><sec><title>DISCUSSION</title><sec><title>The Influence of Brand Image (X1) on Purchase Decision (Y)</title><p>According to the study's results, the Brand Image variable's regression coefficient is positive at 0.092, with a significance threshold of 0.067 &lt; α (0.05) and a computed t-value (1.850) ≥ t-table (1.9864). This suggests that, in part, brand image has a favorable and noteworthy impact on Indonesian consumers' decisions to buy Kopiko candies. That is, a purchase choice is more likely to be made if the brand image is stronger.</p><p>It may be inferred that improving a product's brand image and making the most of all auxiliary components that help create a favorable brand perception can lead to more people buying Kopiko sweets.</p></sec><sec><title>The Influence of Blister Packaging (X2) on Purchase Decision (Y)</title><p>The results of the analysis indicate that the Blister Packaging variable has a positive regression coefficient of 0.358, a t-value of 2.417 ≥ t-table of 1.9864, and a significance level of 0.018 ≤ α (0.05). This suggests that blister packaging influences Kopiko candy purchases in a favorable and noteworthy way. Stated otherwise, the higher the blister package quality, the more likely the buyer is to make a purchase.</p><p>It may be inferred that enhancing the blister packaging's quality and making the most of all of its auxiliary components can encourage more people to buy Kopiko sweets.</p></sec><sec><title>The Influence of Product Placement (X3) on Purchase Decision (Y)</title><p>According to the study's results, the Product Placement variable's regression coefficient is positive at 0.358, with a significance threshold of 0.000 ≤ α (0.05) and a t-value of 8.711 ≥ t-table (1.9864). This demonstrates that, in part, Kopiko candy purchasing decisions are strongly and favorably influenced by product placement. In other words, a purchase choice is more likely to be made if the product placement is more interesting.</p><p>Moreover, this indicates that customers are more inclined to buy Kopiko candy when the product is presented in an appealing way. Effective product placement not only increases brand visibility but also builds a positive impression in the minds of consumers. Thus, purchase decisions are influenced not only by needs but also by the visual appeal and psychological impact of the product placement strategy.</p><p>It can be concluded that Kopiko’s product placement in Korean dramas can significantly influence consumer purchase decisions. An effective product placement strategy—especially when featured in engaging and relevant scenes— makes the brand more recognizable and memorable to viewers. Furthermore, associations with characters or scenes in the drama can foster a positive image of the product, stimulate curiosity, and ultimately influence consumer decisions. Therefore, this strategy becomes one of the most effective marketing methods for attracting consumer interest and increasing sales.</p></sec></sec><sec><title>CONCLUSION</title><p>The study's results allow for the following deductions to be made:</p><list list-type="order"><list-item><p>The variables Brand Image, Packaging Blister, and Product Placement in Korean dramas all significantly influence Kopiko Candy's purchase decision at the same time, according to the Simultaneous test (F).</p></list-item><list-item><p>Kopiko Candy's purchase decision is positively and significantly impacted by the brand image variable.</p></list-item><list-item><p>The Packaging Blister variable has a positive and large effect on the Purchase Decision of Kopiko Candy.</p></list-item><list-item><p>The Product Placement variable in Korean Dramas has a positive and large effect on the Purchase Decision of Kopiko Candy.</p></list-item><list-item><p>Based on the findings of the Coefficient of Determination (R2) test, the independent variables can describe and influence the dependent variables</p></list-item></list></sec></body><back><ack><title>References</title><p><ref-list/></p></ack></back></article>
