The Impact of Learning Innovation and Service Quality on Learner Satisfaction in Non-Formal Education Units in Ambon City

 Corresponding author: Abednego Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. The Impact of Learning Innovation and Service Quality on Learner Satisfaction in Non-Formal Education Units in Ambon City Abednego * Non-Formal Education Study Program, Faculty of Teacher Education and Training, Pattimura University, Ambon, Indonesia. World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 Publication history: Received on 03 October 2025; revised on 10 November 2025; accepted on 13 November 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.28.2.3806 Abstract The level of student satisfaction during training is a crucial factor in non-formal education, particularly in Non-Formal Education Units in Ambon City. One of the main challenges in this context is the innovation in learning and service quality, which significantly affects student satisfaction. This study used a descriptive quantitative approach to examine the effect of learning innovation and service quality on student satisfaction in Non-Formal Education Units in Ambon City. Data were collected through questionnaires distributed to 45 students in Non-Formal Education Units in Ambon City. Hypothesis testing was conducted using a significance level of 5% or α = 0.05. The results showed that: (1) there was a partial effect of learning innovation on student satisfaction in Non-Formal Education Units in Ambon City, with a t-count value > t-table (3.079 > 1.681071); (2) there was a partial effect of service quality on student satisfaction in NonFormal Education Units in Ambon City, with a t-count value > t-table (5.295 > 1.681071). (3) There was a simultaneous effect of learning innovation and service quality on student satisfaction in Non-Formal Education Units in Ambon City, with a calculated F-value > F-table (75.465 > 3.22). These findings highlight the importance of implementing innovative learning models that prioritize collaboration, creativity, critical thinking, and problem-solving. Additionally, they emphasize the importance of quality service in the form of curriculum management, starting from planning, implementation, and evaluation, supported by adequate resources. Future interventions should prioritize learning innovations that synergize with quality services. Keywords: Innovation; Service; Student Satisfaction; Non-Formal Education; Community Learning Center 1. Introduction The Community Learning Center (PKBM) and Non-Formal Education Unit were established in Indonesia in 1998, amidst a national socio-economic crisis. As a result, there are still people who are illiterate. In fact, in 2019, illiteracy rates remained relatively high, at 1.78 percent or around 3,081,136 people. However, this number decreased in 2020 to 1.71 percent or around 2,961,060 people; this was stated by the Director General of Early Childhood Education, Basic Education, and Secondary Education (Dirjen PAUD Dikdasmen). Based on this data, the role of institutions like PKBM is crucial in addressing this issue. In general, PKBM is an institution that focuses on non-formal education development, aiming to be a center that accommodates community learning (Rapanta et al., 2020). The primary function of PKBM is to focus on two main aspects: community activity center and a place to find solutions to social problems in the community (Mutiara, 2020). In its implementation, PKBM functions as a social organization that attempts to reduce important problems such as community mindset backwardness and plays a significant role in other problems that require practical handling (Shyiramunda & Bersselaar, 2024). For example, PKBM in Sumedang Regency addresses poverty through non-formal education in the form of valuable and practical programs, while other activities in community development and empowerment are present but still not optimal (Chotim, 2021). Additionally, a study by World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1188 Sahalessy et al. (2025) on the package C program in one of the PKBM in Ambon highlights the double importance of increasing tutor effectiveness and fostering student motivation to improve educational outcomes in non-formal environments. Tutor performance is shaped by internal factors such as professional competence and motivation, which in turn impact student academic success. Tutor performance and student learning motivation are key predictors of student achievement in Package C programs. Such innovative learning models typically encompass a range of practices, technologies, and pedagogies that prioritize collaboration, creativity, critical thinking, and problem-solving (Sander et al., 2024; Mariyono, 2025). As stated by Tveitnes et al. (2025), innovative learning models can help bridge the gap between theory and practice. Zhang & Chen (2018) observe that innovative learning models "stand out as a means that can help advance education transformation and improve learning outcomes". Innovative learning models can "improve the quality and relevance of education by making teaching and learning more effective, accessible, and sustainable" (Çelik & Baturay, 2024). Innovative learning models contribute to education transformation by promoting more holistic and integrated teaching and learning approaches (Kirkwood & Price, 2013). The use of learning media in innovative learning will greatly help learners to be able to solve problems in the learning process (Kwangmuang et al., 2021), connect learning resources, and ultimately lead to better communication in learning and behavioral change because learning objectives can be achieved, increasing the effectiveness of learner outcomes (Serdyukov, 2025). The use of learning media is the most effective way to achieve all learning objectives (Abdulrahaman et al., 2020). The head of a school that implements effective school management has the potential to produce high-achieving young generations because the school environment can optimize its function as an educational institution that carries out economic, humanitarian, social, political, cultural, and educational functions. One aspect that can support the implementation of effective school management is the leadership of the head of the school in decision-making, communication, direction, and staff development, problem-solving, and evaluation of school activities (Sunaengsih et al., 2019). The success of non-formal educational institutions such as PKBM is largely determined by the quality of services provided (Rahabav & Souisa, 2021). To support this, good quality management is needed, starting from careful planning, adequate facilities, and supporting human resources (Abednego et al., 2023). Human resource management is mediated by leaders in their leadership and educators in education, training, and learning. The quality of service from an educational leader is characterized by effective leadership (Sebastien, 2017), transformative leadership (Cranton, 2006), ethical leadership (Harris et al., 2017) instructional leadership that prioritizes teaching and learning and promotes scholarship (Harris et al., 2017), and leaders who maintain school culture and climate (Karatas et al., 2024). Additionally, educational leadership requires leaders who are skilled in managing the organization's vision and goals (Persson et al., 2025), monitoring student progress (Rice et al., 2020), communication skills (Oetjen et al., 2025), professionalism, and self-reflection (Taylor et al., 2018). School management is one of the determining factors of education quality (Lessa et al., 2018), as it indirectly determines the effectiveness of the curriculum, learning facilities, time, and process (Donkoh et al., 2023). From a management perspective, an effective school strives to utilize all school components optimally (Granger & Chow, 2025). As a formal educational institution, schools are expected to produce graduates with academic abilities, skills, attitudes, and mentalities, as well as competent personalities, so that students have competitiveness after graduating from an institution (Wanti et al., 2022). Schools with strong head leadership are predicted to be able to develop effective school management, supported by various aspects such as technology application, school culture, information systems, and developing organizations. However, in reality, not all headmasters are able to run schools based on strong leadership (Ikram & Kenayathulla, 2023) The leadership of the head of the school in implementing school management is considered important because it can facilitate the division of work activities. A well-organized school environment involves several elements, including the head of the school, teachers, employees, and students. Furthermore, a good organization creates an equal division of tasks and responsibilities to facilitate the work process in achieving common goals (Mincu, 2022). An educational leadership service initiative has been launched in Hong Kong to meet the growing demand for service leaders and improve student well-being by not only developing competencies but also good character and caring attitudes. A curriculum-based leadership course can be a promising way to improve the quality of service leadership and student well-being (Zhu & Shek, 2021). The quality of service from educators is characterized by their ability to manage the curriculum (Dematthews, 2014). Haque & David, (2022) state that curriculum management relates to the management of learning experiences that require specific strategies to produce learning productivity for students. These strategies start from planning, implementation, and evaluation, which need to be supported by adequate resources. Some previous research findings include: 1) innovative learning models are very effective in promoting student-centered learning, increasing student learning satisfaction (Sharma et al., 2023); 2) teaching innovation has a positive effect on student learning effectiveness and a significant positive effect on learning satisfaction (Lee, 2011); 3) the positive impact of innovative teaching approaches and the effectiveness of developing material delivery on student World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1189 satisfaction in online courses (Muthuswamy & Pavithra, 2024); 4) the influence of school services and the quality of the teaching and learning process on student satisfaction (Tupari et al., 2023). 2. Methods The research approach used in this study is a quantitative research approach. The quantitative approach is a research method that focuses on numerical data and testing previously formulated hypotheses. This approach is based on the postpositivist paradigm, which emphasizes the importance of objectivity and measurement in understanding social phenomena. In this context, the researcher seeks to identify the causal relationship between the variables studied through statistically measurable data. Thus, this study aims to obtain results that can be generalized and have high validity based on quantitative data processing. This study will be conducted at the Non-Formal Education Unit (SPNF) in Sirimau District, Ambon City. The selection of this location is based on the consideration that SPNF is an educational institution that plays an important role in improving the skills and competencies of the community outside the formal education system. The study is planned to take place over six months, providing the researcher with sufficient time to collect data, process, and analyze the research results in-depth. The research process is carried out systematically, starting from the preparation stage, data collection, and analysis, and concluding with the drawing of conclusions. The population in this study is all learners registered at SPNF Ambon City, totaling 80 people. From this population, the researcher uses the Slovin formula to determine the number of representative research samples. Based on the calculation results, a sample of 45 learners will be used as respondents. The sample selection is done randomly so that each member of the population has an equal opportunity to be selected, allowing the research results to reflect the overall population condition. By doing so, the researcher hopes to obtain valid and scientifically accountable data. The variables in this study consist of two independent variables and one dependent variable. The independent variables in this study are learning innovation (X1) and service quality (X2), while the dependent variable is the satisfaction level of learners (Y). To measure these three variables, the researcher uses instruments in the form of questionnaires and observations. Before use, these research instruments will be tested for validity and reliability to ensure that the measuring instruments used are truly capable of consistently and accurately measuring the intended variables. The data analysis technique used in this study is multiple linear regression analysis. According to Khaing & Cho (2019), multiple linear regression analysis is used to determine the relationship between two or more independent variables and one dependent variable. This analysis helps the researcher understand the extent to which learning innovation and service quality affect the satisfaction level of learners. Before conducting regression analysis, the researcher will also perform descriptive analysis, classical assumption testing, and hypothesis testing with a significance level of 5% (α = 0.05). The entire statistical analysis process is carried out with the help of SPSS 20 for Windows to ensure that the results obtained are more accurate and efficient. 3. Results 3.1. Descriptive Statistics This section presents the data obtained from the research conducted in the field. The data to be described include innovation in learning, service quality, and learner satisfaction. The descriptive results of the research can be seen in Table 1. Table 1 Descriptive Statistics of Research Data Statistics Innovation in Learning Service Quality Learner Satisfaction Sample Size 45 45 45 Mean 27,53 27,27 28,00 Median 27,00 27,00 29,00 Std.deviation 5,181 4,868 4,782 Variance 26,845 23,700 22,864 Minimum 19 19 19 Maximum 40 39 38 World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1190 From the data in Table 1, it can be seen that the minimum value of the innovation in learning variable (X1) is 19, the maximum value is 40, the variance is 26.845, the standard deviation is 5.181, the median is 27.00, and the mean is 27.53. For the service quality variable (X2), the minimum value is 19, the maximum value is 39, the variance is 23.700, the standard deviation is 4.868, the median is 27.00, and the mean is 27.27. Meanwhile, for the learner satisfaction variable (Y), the minimum value is 19, the maximum value is 38, the variance is 22.864, the standard deviation is 4.782, the median is 29.00, and the mean is 28.00. 3.2. Normality Test The normality assumption test was conducted using the one-sample Kolmogorov-Smirnov test. The normality assumption is said to be normally distributed if the test yields a significance value greater than 0.05. Conversely, if the significance value is less than 0.05, the normality assumption is not normally distributed. The results of the normality test can be seen in Table 2, using SPSS 20 software. Table 2 Results of Normality Test One-Sample Kolmogorov-Smirnov Test Innovation in Learning Service Quality Learner Satisfaction N 45 45 45 Normal Parametersa,b Mean 27.53 27.27 28.00 Std. Deviation 5.181 4.868 4.782 Most Extreme Differences Absolute 0.110 0.092 0.097 Positive 0.110 0.092 0.097 Negative -0.061 -0.090 -0.094 Test Statistic 0.110 0.092 0.097 Asymp. Sig. (2-tailed) 0.200c,d 0.200c,d 0.200c,d a. Test distribution is Normal. b. Calculated from data. c. Lilliefors Significance Correction. d. This is a lower bound of the true significance. From the output of the normality test using SPSS in Table 2, the significance values (Asymp. Sig. (2-tailed)) for the innovation in learning variable (X1), service quality variable (X2), and learner satisfaction variable (Y) are 0.200, 0.200, and 0.200, respectively. Based on the results of the processing, it can be concluded that the data is normally distributed because the significance values for each variable are greater than 0.05, meaning that the data for variables X1, X2, and Y are normally distributed. 3.3. Classical Assumption Test 3.3.1. Multicollinearity Test The multicollinearity test is conducted to examine whether the regression model finds any correlation between independent variables. A regression model is considered free from multicollinearity if the Variance Inflation Factor (VIF) value is < 10 and the tolerance value is > 0.10. The results of the multicollinearity test can be seen in Table 3. World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1191 Table 3 Multicollinearity Test Results Coefficientsa Model Unstandardized Coefficients Standardized Coefficients T Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1 (Constant) 3.378 2.033 1.661 0.104 Innovation 0.318 0.103 0.345 3.079 0.004 0.414 2.416 Service Quality 0.582 0.110 0.593 5.295 0.000 0.414 2.416 a. Dependent Variable: Satisfaction Level From Table 3, it can be seen that the tolerance value of the innovation variable is 0.414 > 0.1, and the service quality variable is 0.414 > 0.1. Therefore, it can be concluded that the tolerance values of both variables are greater than 0.1 (tolerance > 0.1), indicating that they are free from multicollinearity. Furthermore, based on the VIF value, the innovation variable is 2.416 < 10, and the service quality variable is 2.416 < 10, indicating that they are free from multicollinearity. 3.3.2. Heteroscedasticity Test The heteroscedasticity test aims to examine whether the regression model occurs inequality of variance from residual one observation to another observation. If the variance from residual one observation to another observation is constant, it is called homoscedasticity, and if it is different, it is called heteroscedasticity. One way to detect the presence or absence of heteroscedasticity is to perform the Glejser test. The Glejser test proposes to regress the absolute residual value against the independent variables. The probability result is said to be significant if the significance value is above the 5% confidence level. The results of the heteroscedasticity test can be seen in Table 4. Table 4 Heteroscedasticity Test Results Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.824 1.288 2.970 0.005 Innovation 0.019 0.065 0.066 0.287 0.776 Service Quality -0.098 0.070 -0.326 -1.413 0.165 a. Dependent Variable: Abs_RES From the results of the heteroscedasticity test in Table 4, it can be seen that the Sig. value of each variable is 0.776 for the innovation variable (X1) and 0.165 for the service quality variable. From these results, it can be concluded that the regression equation model does not experience heteroscedasticity. This is because the values of each variable are not significant, or the Sig. value is greater than 0.05. 3.3.3. Multiple Linear Regression Test The multiple linear regression analysis is used to examine the simultaneous effect of several independent variables, namely innovation (X1) and service quality (X2), on one dependent variable, namely satisfaction level (Y). The aim is to determine the effect of independent and dependent variables. The results of the regression test are as follows: World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1192 Table 5 Multiple Linear Regression Test Results Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.378 2.033 1.661 0.104 Innovation 0.318 0.103 0.345 3.079 0.004 Service Quality 0.582 0.110 0.593 5.295 0.000 a. Dependent Variable: Satisfaction Level Based on Table 5, the equation of the multiple linear regression analysis in this study is: KK = α + b1I + b2KP + e KK = 3,378 + 0,318I + 0,582KP + 2,033 The regression equation can be explained as follows: The constant value of 3.378 means that if the innovation (X1) and service quality (X2) variables are considered constant or 0, then the satisfaction level of learners (Y) is 3.378 units. The regression coefficient value of the innovation variable (X1) is 0.318, meaning that if the innovation variable (X1) increases by 1 unit, then the satisfaction level of learners (Y) will increase by 0.318 units, assuming the other variables remain constant. The positive coefficient value indicates a positive relationship between innovation (X1) and satisfaction level (Y). The regression coefficient value of the service quality variable (X2) is 0.582, meaning that if the service quality variable (X2) increases by 1 unit, then the satisfaction level of learners (Y) will increase by 0.582 units, assuming the other variables remain constant. The positive coefficient value indicates a positive relationship between service quality (X2) and satisfaction level (Y). 3.4. t-test The partial test (t-test) is used to determine whether the regression model of innovation and service quality variables partially has a significant effect on the satisfaction level of learners. The results of the t-test can be seen in Table 6. Table 6 t-test Results Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.378 2.033 1.661 0.104 Innovation 0.318 0.103 0.345 3.079 0.004 Service Quality 0.582 0.110 0.593 5.295 0.000 a. Dependent Variable: Satisfaction Level From the partial test results, it can be seen that the effect of each variable, where the table value obtained and the formula df = n-2, so 45-2 = 43, and the ttable value is 1.681071. Therefore, it can be concluded that: tcount > ttable (3.079 > 1.681071), then Ha is accepted, meaning that there is a partial effect of innovation on the satisfaction level of learners in non-formal education units in Ambon city. World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1193 tcount > ttable (5.295 > 1.681071), then Ha is accepted, meaning that there is a partial effect of service quality on the satisfaction level of learners in non-formal education units in Ambon city. 3.4.1. F-test The simultaneous test (F-test) is used to examine the effect of innovation and service quality variables simultaneously on the satisfaction level of learners. The results of the F-test are as follows: Table 7 F Test ANOVAa Model Sum of Squares Df Mean Square F Sig. 1 Regression 786.998 2 393.499 75.465 0.000b Residual 219.002 42 5.214 Total 1006.000 44 a. Dependent Variable: Satisfaction Level b. Predictors: (Constant), Service Quality, Innovation From the test results in Table 7, it can be seen that the Fcount value is 75.465, while the Ftable value is obtained from the formula df (N1) = k-1 or 3-1 = 2 and df (N2) = n-k = 45-3 = 42, which is 3.22. Since Fcount > Ftable (75.465 > 3.22), it means that H0 is rejected, and Ha is accepted, indicating that there is a simultaneous effect of innovation and service quality on the satisfaction level of learners in non-formal education units in Ambon city. 3.4.2. R-Square Test (Coefficient of Determination) (R2) The coefficient of determination serves to determine the percentage of the influence of the independent variable on the dependent variable, namely by squaring the coefficient found. In its usage, this coefficient of determination is expressed as a percentage. To find out the extent of the contribution or percentage of the influence of learning innovation and service quality on the level of learner satisfaction, it can be determined through a determination test. Table 8 Results of the Determination Coefficient Test (R-Square) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 0.884a 0.782 0.772 2.283 a. Predictors: (Constant), Service Quality, Innovation From the table above, the correlation coefficient (R) value is 0.884 or 88.4%. The R value essentially measures the strength of the relationship between innovation and service quality (independent variables), which has a very strong relationship level of D = R2 x 100% D = 0,884 x 100% D = 88,4% The very strong relationship is concluded based on the guidelines for interpreting correlation coefficients, which can be seen in Table 9. World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1194 Table 9 Interpretation Guidelines for Correlation Coefficients Interval Coefficient Relationship Level 0.000 – 0.199 Very Low 0.200 – 0.339 Low 0.400 – 0.599 Moderate 0.600 – 0.799 Strong 0.800 – 0.1000 Very Strong Source : Sugiyono (2008) The R-squared (R2) value, also known as the coefficient of determination, is 0.782. This value indicates that 78.2% of the variation in the dependent variable, namely the level of learner satisfaction, can be explained by the independent variables (innovation and service quality). Conversely, 21.8% of the variation in learner satisfaction is attributed to other factors not examined in this study. 4. Discussion The study titled 'The Influence of Learning Innovation and Service Quality on the Satisfaction Level of Non-Formal Education Participants in Ambon City' with a total of 45 respondents showed that: There is a partial influence of learning innovation on the satisfaction level of non-formal education participants in Ambon City. This is evident from the test results using SPSS 24 program, which showed that t-count > t-table (3.079 > 1.681071). Consistent with this, Xavier et al. (2025) found that educational innovation has a positive and significant effect on student satisfaction. Innovation in learning is necessary as a form of teacher professionalism in creating engaging and varied learning. In the learning process, innovation is required, which must be done by teachers so that the delivery of material becomes easily understandable by students (Gemnafle et al., 2018). With continuous learning innovation, students will be interested in following the learning process, as there will be new things applied in learning, thus increasing student satisfaction. This innovation is important not only for effective learning transfer but also for promoting continuous professional development among faculty members, leading to updated knowledge in each academic discipline (Chapman et al., 2021). Consequently, innovation in the educational process is positioned as a strategic mechanism for institutional transformation, academic relevance, and sustainable student satisfaction in contemporary educational institutions. Brew & Saunders, (2020) emphasize that effective management of these processes depends on setting clear goals that drive systemic balance. This perspective requires all institutional areas to be fully engaged in designing, implementing, and evaluating organizational pedagogical strategies (Alenezi, 2023). At a deeper level, it can propose integrating variables related to ideology, values, attitudes, and motivation adopted by academic and administrative staff into institutional goals. Describing the changes that must be applied within an organization to implement the type of innovation that suits the problem, such as open innovation, which uses a holistic methodology, resulting in the institution strengthening internal actions as a starting point before implementing innovation with external characteristics (Ebabu & Abebe, 2023). The results of this study indicate that there is a significant influence between service quality and the level of satisfaction of learners partially in non-formal education units in Ambon City. Based on the results of data analysis using SPSS version 24, a t-count value of 5.295 was obtained, which is greater than the t-table value of 1.681071, indicating that the service quality variable has a real effect on the level of learner satisfaction. These findings support the view that the better the service quality provided by non-formal education institutions, the higher the level of satisfaction felt by learners.These results are also in line with research conducted by Dugenio-nadela et al., (2023), which concluded that optimal school service quality can foster a sense of satisfaction and comfort in learners. Similarly, good service aspects, such as speed, accuracy, friendliness, and attention to students' needs, are important factors in creating learning satisfaction (Limbu et al., 2023). Additionally, the results of other studies show a significant partial effect between service quality and student satisfaction (Hasan & Hosen, 2022). In other words, both in formal and non-formal education institutions, service quality is an important indicator that determines learner satisfaction. Learner satisfaction is a reflection of the success of educational institutions in providing services that meet their expectations and needs. If the services received by learners are adequate - for example, in terms of infrastructure, educator professionalism, responsiveness of educational staff, and clarity of information - learners will feel valued and comfortable in the learning process. Conversely, if the services provided are poor, such as delays in service, lack of attention to students, or inadequate facilities, it can lead to dissatisfaction and decreased motivation to learn. Thus, this study emphasizes that World Journal of Advanced Research and Reviews, 2025, 28(02), 1187-1199 1195 improving service quality is an important strategy that must be implemented by non-formal education institutions in Ambon City to create a conducive learning atmosphere, increase learner loyalty, and strengthen the positive image of the institution in the eyes of the community. This study indicates a significant influence between learning innovation and service quality on the satisfaction level of learners in non-formal education units in Ambon City. Based on the test results using SPSS version 24, an F-count of 75.465 was obtained, which is greater than the F-table of 3.22. This leads to the conclusion that simultaneously, both variables have an impact on learner satisfaction. These findings affirm that the higher the level of learning innovation and the better the service quality provided by educational institutions, the higher the learner satisfaction with the educational services they receive. These results align with Rahman (2019) findings, which state that service quality and innovation simultaneously influence customer satisfaction at PT PLN (Persero) Area Manado. Rahman’s study reinforces the perspective that in both profit and non-profit organizations, innovation and quality service are crucial factors that can enhance customer satisfaction. This is also consistent with Parasuraman et al. (1988), who developed the SERVQUAL model, where the five dimensions of service quality—tangibles, reliability, responsiveness, assurance, and empathy—directly affect customer perception and satisfaction. In the context of education, similar findings were reported by Quiachon (2025), emphasizing that educational institutions can be regarded as service organizations that prioritize learner satisfaction as their primary customers. Therefore, innovation in learning processes, such as the implementation of digital learning methods, personalized learning, and project-based approaches, are essential to enhance learners’ experiences. According to Fullan (2008), learning innovation is not solely related to technology use but also involves a paradigm shift in how educators interact with and guide learners to achieve optimal learning outcomes. This study also reveals a coefficient of determination (R²) of 0.782, indicating that 78.2% of the variation in learner satisfaction can be explained by learning innovation and service quality, while the remaining 21.8% is influenced by other factors not examined, such as internal motivation, learning environment, or family support. These findings are consistent with those of Asfar & Suripto (2021) , which state that in the service sector, customer satisfaction is not solely dependent on one factor but is the result of interactions among various interrelated variables. Thus, it can be concluded that enhancing learning innovation and service quality is an effective strategy to increase learner satisfaction in non-formal education institutions in Ambon City. Educational institutions need to continuously promote innovation in learning methods, media, and approaches, as well as strengthen responsive, friendly, and learner-centered service systems, to create more meaningful and satisfying learning experiences. 5. Conclusion Based on the findings, it can be concluded that learning innovation and service quality play a crucial role in enhancing learner satisfaction in non-formal education units in Ambon City. The learning innovations implemented by educators, such as the use of creative methods, technology integration, and collaborative and contextual approaches, create a more engaging and meaningful learning atmosphere. Learners feel more motivated and enthusiastic as the learning process not only focuses on delivering material but also actively involves them in learning activities that promote creativity and critical thinking skills. Meanwhile, good service quality from educational institutions, particularly in terms of educator professionalism, clear information, punctuality, friendliness, and adequate facilities, also increases learner satisfaction. Student-centered services create a sense of being valued and comfortable, fostering loyalty to the educational institution. The combination of innovative learning and quality services enables non-formal education institutions to compete and provide positive learning experiences for the community. As a recommendation, non-formal education institutions in Ambon City need to strengthen educators' capacity to implement innovative and adaptive learning models in response to technological advancements. Continuous training, inter-institutional collaboration, and support from local governments are essential to encourage relevant learning. Additionally, educational services must be managed professionally, paying attention to curriculum management, effective communication, and the availability of facilities that support learning comfort. Through synergy between learning innovation and service quality improvement, non-formal education institutions are expected to become inclusive, competitive, and learner-centered learning hubs that prioritize learner satisfaction and success. Here is a minor edit to make the text more polished: Based on the findings, it can be concluded that learning innovation and service quality are crucial in enhancing learner satisfaction in non-formal education units in Ambon City. Educators' implementation of learning innovations, such as creative methods, technology integration, and collaborative and contextual approaches, creates a more engaging and meaningful learning atmosphere. This approach not only delivers material but also actively involves learners in activities that promote creativity and critical thinking skills, resulting in increased motivation and enthusiasm. Furthermore, good service quality from educational institutions, particularly in terms of educator professionalism, clear information, punctuality, friendliness, and adequate facilities, also contributes to learner satisfaction. By providing student-centered services, learners feel valued and comfortable, fostering loyalty to the educational institution. The combination of innovative learning and quality services enables non-formal education institutions to compete and provide positive learning experiences for the community. To achieve this, non-formal education institutions in Ambon