Implementation of Simdiklat and User Satisfaction Among Employees of BBPPMPV BOE Malang

ABSTRACT

This research was conducted at BBPPMPV BOE Malang, a government institution that provides education and training to vocational high school teachers in the field of technology in the eastern region of Indonesia. Since 1986, they have developed the simdiklat application to manage administrative data using the Single Entry Multi Output concept. The objective is to enhance effectiveness, efficiency, service quality, and user satisfaction. The research population consisted of 40 simdiklat users, and the entire population was taken as the sample. The analysis was conducted using SPSS (Statistical Package for the Social Sciences). The findings indicate that the implementation of simdiklat plays a significant role in improving user satisfaction among employees of BBPPMPV BOE Malang.

INTRODUCTION
In the era of the fourth industrial revolution, information technology (IT) and the internet have become an integral part of societal culture and play a crucial role in the services provided by public organizations. The utilization of information technology in the form of management information systems (MIS) is key in delivering the best services to users (Schwab, 2016). Information technology has a strategic impact on organizations, particularly in supporting and achieving overall organizational strategies (Romney & Steinbart, 2006). By harnessing information technology, quick access to business processes can be achieved, enabling faster and more accurate decision-making, ultimately aiding in the organization's goals.
The use of information technology also has an impact on employee performance. Proper utilization of information technology can provide a competitive advantage for companies and enhance employee performance (Adams et al., 1992). Thomson et al. (in Wijana, 2007) explain that the use of information technology is expected to improve employee performance in carrying out their tasks. Employee performance measurement is based on the intensity and frequency of information technology utilization, as well as the number of applications or software used (Thomson et al., in Wijana, 2007).
In the context of a public organization, the Balai Besar Pengembangan Penjaminan Mutu Pendidikan Vokasi (Center for Development and Empowerment of Vocational Education Quality) in the field of Automotive and Electronics, Malang, is an institution that provides education and training to vocational school teachers in the technology field for the eastern region of Indonesia. To enhance the effectiveness and efficiency of training management, the BBPPMPV BOE Malang has developed the Education and Training Management Information System (Simdiklat) as a tool for managing administrative and secretarial data related to training programs (Hendri Murti Susanto, personal interview, 2023). The simdiklat application aims to improve service quality, facilitate training implementation, and enhance user satisfaction.
Several previous studies have also been conducted on the utilization of information systems in the context of education and training. M. Kibtiyah (2019), in her research on the effectiveness of the Implementation of Information Systems in the Balai Diklat Keagamaan Denpasar, found that system quality, information quality, and top management support influence system usefulness and user satisfaction. Another study conducted by M. Usman Fadillah (2020) on the Influence of Information Technology Implementation and User Capabilities on Job Satisfaction showed that the implementation of information technology and user capabilities positively affect employee job satisfaction.
Measuring the effectiveness of information systems should consider six key factors: system performance, information quality, user satisfaction, business impact, technological innovation, and cost. This approach provides a holistic and comprehensive view of information system effectiveness, as emphasized by Jerry Luftman (2000). Measuring the effectiveness of the information system (IS) is essential to avoid the productivity paradox, where significant investments in IS yield low returns. The effectiveness of the IS lies in how well the intended IS is implemented and contributes to achieving organizational goals. The measurement of its success aligns with the dimensions of (1) the quality of the simdiklat system used to assess user satisfaction, (2) the quality of simdiklat information used to measure user satisfaction, and (3) the user's capabilities in utilizing simdiklat to evaluate user satisfaction.

LITERATURE REVIEW 1. Satisfaction Theory
Several experts have proposed theories related to satisfaction. For instance, Maslow (1943) introduced the Hierarchy of Needs theory, which states that satisfaction depends on an individual's hierarchical needs. Vroom (1964) developed the Expectancy Theory, which suggests that satisfaction is influenced by an individual's expectations of the outcomes of their actions. Adams (1965) presented the Equity Theory, emphasizing individuals' perception of the balance between their efforts and outcomes. Herzberg (1959) proposed the Two-Factor Theory, differentiating between hygiene factors and motivators in job satisfaction. Locke (1976) introduced the Discrepancy Theory, stating that satisfaction is influenced by changes in individual work conditions. Experts agree that satisfaction plays a crucial role in organizations, including employee performance and retention.
Experts also have diverse opinions on customer satisfaction. Parasuraman, Zeithaml, and Berry (1988) developed the SERVQUAL model to measure customer satisfaction by comparing customer perceptions of service quality with their expectations. Experts such as Kotler (2003) and Tjiptono (2014) emphasize that customer satisfaction is crucial for maintaining and enhancing loyalty, as well as influencing a company's image and customer trust. Oliver (1997) argues that satisfaction alone is not sufficient, but factors such as emotional attachment and perceived value from the company are also essential. The success of a company relies on customer satisfaction, which needs to be measured and understood to improve product or service quality and maintain customer loyalty.

Social Cognitive Theory (SCT)
The Social Cognitive Theory (SCT), developed by Albert Bandura (1986), emphasizes that individual behavior is influenced by the interaction between social, cognitive, and personal factors. Bandura proposed that an individual's behavior is influenced by three main factors. Firstly, personal factors encompass individual characteristics such as beliefs, values, motivations, cognitions, and emotions. Individuals have the ability to influence and modify their personal factors, which ultimately affect their behavior. Secondly, behavioral factors include observed or performed behaviors by individuals, including direct and indirect experiences such as observation, imitation, or behavioral rehearsal. Lastly, environmental factors refer to external factors beyond the individual, including social influences, policies, and social norms. Environmental factors can also influence individual behavior through social influence, norms, and incentives (Bandura, 1986).

Technology Acceptance Model (TAM)
The Technology Acceptance Model (TAM), developed by Davis, is an adaptation of the Theory of Reasoned Action (TRA) by Fishbein and Ajzen in 1980. TAM recognizes that individuals' reactions and perceptions of technology will influence their attitudes and behaviors (Davis, 1989). This model focuses on two main factors that affect technology acceptance: perceived usefulness and perceived ease of use. TAM emphasizes that users' rational assessments of technology, including the influence of perceived usefulness and ease of use, affect their decisions to adopt or reject the technology. By considering factors such as prior experience, TAM can predict the level of technology adoption by users (Davis, 1989).
Although TAM has proven effective in predicting user behavior and is widely used in research on technology adoption, it has also received some criticism. One criticism is that TAM inadequately considers social and cultural factors that influence technology acceptance. Additionally, the model overlooks collective decision-making in technology adoption (Venkatesh et al., 2003). However, overall, TAM remains a valuable model for understanding and predicting technology acceptance by users and can be applied in various contexts such as business, education, and social settings (Davis, 1989).

Simdiklat Implementation Theory
The implementation of the Education Management Information System (Simdiklat) in the education environment involves various factors that influence the adoption of new technology. Theories such as Diffusion of Innovation by Rogers (1962), Institutional Change by Meyer and Rowan (1977), and the Technology Acceptance Model by Davis (1989) provide insights into the factors that need to be considered in the implementation of Simdiklat. Experts agree that comprehensive analysis prior to Simdiklat implementation is crucial for achieving desired goals effectively and efficiently. By understanding the characteristics of the innovation, individual factors, communication, social structure, successful practices, perceived usefulness, perceived ease of use, individual attitudes, and user intentions, the implementation of Simdiklat in the education environment can be successful and well-received by users.

Simdiklat System Theory
Experts have expressed their opinions on system theory in the context of Education Management Information Systems (Simdiklat). Yusuf (2012) states that an educational information system is a system consisting of interconnected components. Santoso (2015) emphasizes that system theory helps in designing effective and efficient educational information systems. Widodo (2012) suggests that system theory enables understanding of the functions and performance improvement of educational systems. Sugiyono (2015) highlights that system theory allows a holistic view of educational information systems. These expert opinions provide important insights into the role of system theory in developing and enhancing Simdiklat.

System Quality
According to Herlambang et al. (2018), the quality of Simdiklat system encompasses several important aspects. System reliability, system performance, system security, user-friendliness, system availability, and system capacity are quality indicators that need to be considered in the development of this educational information system. Regular evaluation and development are necessary to ensure that the Simdiklat system continues to meet the desired needs and quality standards (Herlambang et al., 2018).
In creating a high-quality Simdiklat system, the focus is on end-user satisfaction. The quality of the Simdiklat system is related to the capabilities of hardware, software, policies, and procedures in providing the required information to users. System reliability, system performance, system security, user-friendliness, system availability, and system capacity are important aspects that need to be considered to ensure that the Simdiklat system functions well and provides benefits to its users (Herlambang et al., 2018). This research aligns with the study by M. Kibtiyah (2019) which states that system quality has no positive effect on user satisfaction with the Simdiklat application.

Information Quality
Information quality refers to the output of an information system, encompassing the value, benefits, relevance, and timeliness of the generated information (Pitt and Watson, 1997). High-quality information indicates that the presented information aligns with the expectations and needs of the users based on the dimensions of information quality. This research is consistent with the study by M. Kibtiyah (2019) stating that information quality has a positive effect on user satisfaction with the Simdiklat application.

User Capability
Users play a crucial role in the operation of technology within an information system. Doyle (2005) defines computer user expertise as an individual's assessment of their ability to use computers or information systems. Bandura (1986) suggests that user expertise is influenced by motivation and behavior and is an individual's belief in their ability to operate a computer. Indriantoro (2000) states that user expertise in accounting information systems includes the ability to use computer applications, operating systems, handle files and hardware, data storage, and keyboard usage.
Furthermore, Compeau and Higgins (1995) mention indicators of user expertise in computer usage, including magnitude, strength, and generability. Magnitude refers to the expected level of computer usage capability, where individuals with high magnitude computer expertise can perform more complex computational tasks. Strength refers to an individual's confidence in computer usage and their ability to overcome obstacles. Generability refers to an individual's ability to use different software packages and computer systems. Previous research by M. Usman Fadillah (2019), Faridah and Noviyanti (2017), Wahyuni (2018), and Acintiawan and Astika (2019) has found that user expertise has a positive impact on user satisfaction with Simdiklat applications.

User Satisfaction
Measurement of satisfaction has a long history in the field of information systems. User satisfaction with an information system is crucial for improving productivity, efficiency, and the effectiveness of organizational reporting. According to Kotler (2005), satisfaction is the level of contentment an individual feels after comparing their perceived product performance (outcome) with their expectations. In both research literature and practice, user satisfaction is often used as a surrogate measure of IS effectiveness (Melone, 1990). Research findings by M. Kibtiyah (2019), M. Usman Fadillah (2020), and Wahyuni (2018) demonstrate that the quality of information systems has a positive influence on user satisfaction.

Prior Research
Several interesting studies have shown the relationship between the implementation of information technology and employee performance satisfaction, including: a. Wahyuni (2018) found that the implementation of information technology has a positive and significant influence on employee performance. b. Acintiawan and Astika (2019) found that user's technical ability also has a significant positive influence on individual performance. c. M. Kitbiyah (2019) showed that the quality of the system and information, as well as top management support, do not have a positive influence on user satisfaction with the Simdiklat application. d. Faridah and Noviyanti (2017) found that the personal abilities of information system users have a positive and significant influence on the performance of the accounting information system. e. M. Usman Fadillah (2020) found that the implementation of information technology and user capabilities have a significant influence in improving job satisfaction. Thus, the implementation of information technology that considers user capabilities can enhance employee performance and job satisfaction.

Conceptual Framework
Picture 1. Conceptual Framework

Research Scope
The subjects of this study are employees who are users of Simdiklat at the Balai Besar Pengembangan Penjaminan Mutu Pendidikan Vokasi Bidang Otomotif dan Elektronika (BBPPMPV BOE Malang). The research will be conducted from January 2023 to April 2023. The data used to support this research is quantitative and obtained from the questionnaire responses distributed via WhatsApp, which will be collected using a Likert scale ranging from 1 to 5. The data collection is primary. The sampling technique used is probability sampling with a saturation sampling method, meaning that the entire sample population is included. The selection criteria for the sample are administrators or users of Simdiklat, totaling 40 people. This selection is based on the fact that administrators or users are directly involved in and understand the field conditions. The independent variables in this study are system quality, information quality, and user capability, while the dependent variable is user satisfaction with Simdiklat.
According to Lufri et al. (2015), satisfaction is the level of an individual's feelings after comparing the perceived performance of a product (outcome) with their expectations. The indicators used to measure user satisfaction with the system are adopted from the studies by M. Kibtiyah (2019) and M. Usman Fadillah (2020), namely (1) availability of access, (2) speed of access, (3) ease of access, (4) information quality, and (5) technical support.
Good information quality provides users with accurate, relevant, and reliable information for decision making or utilization, according to Prabowo et al. (2019). The indicators used to measure user satisfaction are adopted from the study by M. Kibtiyah (2019), namely (1) accuracy, (2) clarity, (3) relevance, and (4) timeliness.
User capability is also important. According to Compeau and Higgins (1995), user capability in using a computer can be assessed/measured based on its indicators. The indicators used to measure user satisfaction are adopted from the study by Acintiawan and Astika (2019), namely (1) magnitude, (2) strength, and (3) generability.
The research instrument will be measured using a Likert scale. Each variable will use a 5-point Likert scale, with a score of 1 = Strongly Disagree (SD), 2 = Disagree (D), 3 = Neutral (N), 4 = Agree (A), and 5 = Strongly Agree (SA). The five-point Likert scale is the most commonly used scale in research and has good validity, reliability, discriminant power, and stability (Preston and Colman, 2000;Dawes, 2008;Budiaji, 2013). Cooper and Schindler (2006: 46) state that measurement with the Likert scale produces interval data. The instrument needs to be tested for its quality by distributing the questionnaire to be used, followed by validity and reliability tests.

Data analysis technique
Descriptive statistics are intended to provide a concise summary of information from a large dataset, including measures of central tendency (range, variance, standard deviation, and trend) (Sugiyono, 2013:112). Classical assumption tests aim to determine whether there are violations of classical assumptions in multiple regression models, so that the analysis results can be interpreted more accurately and efficiently. These classical assumption tests include tests for normality, multicollinearity, and heteroscedasticity.
The problem-solving model used in this study is multiple regression analysis. Multiple regression analysis is an analysis that explains the effects and magnitude of the effects caused by one or more independent variables on a dependent variable (Sudarmanto, 2005:1). The multiple linear regression test in this study is used to calculate the influence of system quality, information quality, and top management support on user satisfaction with Simdiklat. The processing of multiple linear regression analysis is done using the Statistical Package for Social Sciences (SPSS) for Windows, following the formula according to Sugiyono (2013).
Note: In the last sentence, the formula for multiple linear regression analysis should be included to provide a complete translation. However, since the formula is not provided in the original text, I cannot provide an accurate translation without it.Y = a + b1X1 + b2X2 + b3X3 + e Information : Y = User Satisfaction A = Constant value b1.b2.b3 = Regression coefficients X1 = System Quality X2 = Information Quality X3 = User Ability e = Error After obtaining the results of multiple regression analysis, further testing can be conducted: Coefficient of Determination (R2): Essentially, it measures the extent to which the independent variables collectively explain the variance in the dependent variable (Sugiyono, 2013). Regression Coefficient Test (t-test):

RESEARCH RESULT AND DISCUSSION 1. Research Result
The respondents in this study are administrators or users of the BBPPMPV BOE Malang's Simdiklat system, who serve as the primary source of information using a census sampling method. The selection of Simdiklat administrators aligns with the research's purpose of gathering information regarding the implementation of Simdiklat and its impact on user satisfaction among BBPPMPV BOE Malang employees. The distribution of questionnaires took place from January to April 2023. The questionnaires were sent to each administrator or user via WhatsApp. The researcher distributed 40 questionnaires to the respondents, and all 40 questionnaires were filled out. Therefore, the study processed a total of 40 samples.

Testing Stage
Several stages are conducted to test Data Quality, namely: a. Validity Test The correlation coefficient value in this study is 0.304. Therefore, if a statement has a correlation coefficient value less than 0.304, it is considered invalid and will be excluded from the instrument. The User Satisfaction variable has a correlation coefficient value ranging from 0.733 to 0.843, as observed in Pearson correlation. The System Quality variable (X1) has a correlation coefficient value ranging from 0.579 to 0.735. The Information Quality variable (X2) has a correlation coefficient value ranging from 0.570 to 0.843. The Top Management Support variable (X3) has a correlation coefficient value ranging from 0.570 to 0.733. b. Reliability Test Reliability test is conducted to assess the consistency of respondents' answers to all questionnaire items used. The statistical technique used for this testing is Cronbach's alpha. Based on the reliability test results, the Cronbach's alpha coefficient values for all questionnaire items are greater than 0.80, indicating that all research instruments are reliable.

Data analysis
After analyzing the data, the minimum total score obtained from respondents' answers regarding user satisfaction is 25, while the maximum score is 17. The average total score of respondents is 22.5, which falls under the satisfied classification. Regarding the variable of system quality, the average total score of respondents' answers is 27.80, which falls under the flexible classification. The respondents' answers indicate that they are flexible in responding to system constraints, performance, security, ease of use, system availability, capacity, and the output format generated by the Simdiklat application is good.
As for the variable of information quality, the average total score of respondents' answers is 18.5, which falls under the comprehensive classification. The respondents' answers indicate that the information generated by the Simdiklat application is clear, relevant, accurate, up-to-date, and the output format of the information is good. Regarding the variable of user abilities, the average total score of respondents' answers is 25.13, which falls under the proficient classification. The respondents' answers indicate that they have proficient user abilities, confidence, and the ability to adapt to the system, and the output format of user abilities is good.

Classical Assumption Tests
Before conducting hypothesis testing, classical assumption tests are performed. Classical assumption tests are statistical requirements that must be met in Ordinary Least Square (OLS) regression analysis. This testing aims to determine and test the validity of the regression model used in the study to ensure that the results are Best Linear Unbiased Estimators (BLUE). The classical assumption tests in this study include tests for normality, multicollinearity, and heteroscedasticity.
The normality test is conducted using the Kolmogorov-Smirnov test. The Kolmogorov-Smirnov test yields a value of 0.098 with a significance level of 0.200 > 0.05. Therefore, the research data is normally distributed and suitable for predicting the dependent variable. The results of the multicollinearity test show that the independent variables have tolerance values of 0.422, 0.428, and 0.629, which are all greater than 0.10, and VIF values of 2.370, 2.355, and 1.614, which are all less than 10.
The heteroscedasticity test is conducted using scatterplot diagrams and the Glejser test. The significance probabilities for each independent variable are 0.700, 0.392, and 0.212, which are all greater than the significance level of 0.05. Therefore, it can be concluded that there is no heteroscedasticity.
Multiple Linear Regression Analysis After conducting the classical assumption tests, the test results are presented in Table 1. It is revealed that:: a. The value of the constant (α) is -0.779, which means that when the variables quality of the system, quality of information, and user ability are zero, the user satisfaction will have a negative value (-0.779).
b. The coefficient value of the quality of the system (X1) is 0.118 with a significance level of 0.250. This means that when the quality of the system variable increases, the user satisfaction variable will increase by 0.118, assuming that the other variables are constant. The quality of the system does not have a significant effect on user satisfaction in the Simdiklat application. This implies that the quality of the system cannot improve user satisfaction in each unit that uses the application. c. The coefficient value of the quality of information (X2) is 0.704 with a significance level of 0.000. This means that when the quality of information variable increases, the user satisfaction variable will increase by 0.704, assuming that the other variables are constant. d. The coefficient value of user ability (X3) is 0.287 with a significance level of 0.001. This means that when the user ability variable increases, the user satisfaction variable will increase by 0.287, assuming that the other variables are constant. Mathematically, the regression equation is as follows: Y= -0,779+0,118X1+0,704X2+0,287X3+e Based on the results of the regression analysis, the following information is known regarding the coefficient of determination test, model fit test (goodness of fit), and hypothesis testing. a. he coefficient of determination test results describe how well the independent variables in the model can explain the dependent variable (Ghozali, 2012). The coefficient of determination indicator used in this study is the Adjusted R-squared of 0.812, which means that 81.2% of the user satisfaction variable can be explained by the variables quality of the system, quality of information, and user ability, while the remaining 18.8% is explained by other variables not included in the model. Hypothesis testing results (t-test): The calculated t-value probability for the independent variable quality of the system is 0.250, which is greater than 0.05. This indicates that the quality of the system does not have a significant effect on user satisfaction at a 95% confidence level. Similarly, for the variable quality of information, the calculated t-value probability is 0.000, which is smaller than 0.05. This indicates that the quality of information has a significant effect on user satisfaction at a 95% confidence level. This shows that the quality of information significantly influences user satisfaction. As for the user ability variable, the calculated t-value probability for the independent variable is 0.001, which is greater than 0.05. This indicates that user ability significantly affects user satisfaction at a 95% confide.

CONCLUSIONS AND RECOMMENDATIONS Conclusion
Based on the research, the following conclusions are drawn: 1. The System Quality of Simdiklat does not have a significant influence on User Satisfaction partially. Other factors outside of this variable may have a greater influence on user satisfaction. 2. The Information Quality of Simdiklat has a significant influence on User Satisfaction partially. Users are highly influenced by the quality of information provided by Simdiklat. 3. The User Ability of Simdiklat has a significant influence on User Satisfaction partially. The higher the user's ability, the higher the level of satisfaction experienced. Therefore, attention to information quality and user ability is crucial to enhance user satisfaction in utilizing Simdiklat.