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This study aims to analyze how financial literacy and the frequency of use of financial technology (fintech) services affect the financial management patterns of students in the Economics Education Study Program at Universitas PGRI Wiranegara. The digitalization era has changed the way students manage their finances, which now combine traditional financial understanding with the implementation of digital technology innovations. This research uses a quantitative method with an explanatory approach, involving respondents selected through random stratification to ensure balanced representation. Data collection uses a Likert scale questionnaire instrument, while data analysis applies a multiple linear regression model. Empirical results prove that financial literacy and fintech utilization both have a significant and positive impact on students' financial management patterns. Together, these two factors can explain most of the variation in respondents' financial behavior. These findings emphasize the importance of integrating fundamental financial knowledge with the ability to adapt to digital technology as a foundation for forming effective financial management competencies in the modern era. In terms of implementation, the results of this study suggest strengthening the economics education curriculum that includes learning digital financial literacy and the use of fintech services that are wise and ethical.

Employment insurance is an important instrument in the social protection of workers. In Indonesia, BPJS Ketenagakerjaan has launched various insurance programs, including JKK, JKM, JHT, and JKP. However, the effectiveness of these programs in improving the welfare of workers, especially the informal sector which accounts for more than 59% of the workforce, remains a question. This study uses a quantitative approach with descriptive and linear regression methods on secondary data from BPJS and BPS for the last five years. The results show that there is an imbalance in participation between the formal and informal sectors due to low literacy and limited regulations. This research produces a databased participatory recommendation model to improve the effectiveness of the BPJS Ketenagakerjaan program and encourage social inclusion for all workers.

This study aims to examine the influence of brand awareness (X1) and brand image (X2) on the purchase intention (Y) of iPhone among students of the Economic Education program at Universitas Sebelas Maret. The background of this study is based on the increasing preference of students towards the iPhone, which holds high exclusivity value and strong brand image, despite being positioned in a premium price segment. This research employs a quantitative approach using a survey method through questionnaires distributed to 83 respondents selected randomly by simple random sampling technique. The research instruments were tested for validity and reliability, and the data were analyzed using multiple linear regression analysis. The results indicate that both X1 and X2 have a significant effect on Y. The implications of these findings suggest that marketing strategies emphasizing the development of a strong and exclusive brand image can enhance consumers’ purchase intention, particularly among students. This study is expected to serve as a reference for marketers in designing effective and targeted promotional strategies for the higher education market segment.

This research aims to study how the use of digital technology and artificial intelligence affects the productivity level of accounting students. This is based on the importance of the application of technology in the educational process, especially in accounting, which requires accuracy and efficiency. This research uses a quantitative approach by conducting a survey of 32 accounting students from several universities in Indonesia. They were selected through snowball sampling method. A Likert scale questionnaire was used to collect data and then analyzed using multiple linear regression using the SPSS program. The results showed that the use of digital technology and artificial intelligence is both positive and significant to the level of student productivity. The technology utilization variable contributed 36.7% to productivity, while the artificial intelligence variable contributed 34.9%. The results of this study indicate that the use of current technology in accounting learning not only improves the efficiency of tasks, but also improves the quality of results and students' analytical skills. Therefore, educational institutions should adopt a technology-based learning approach in order for accounting students to achieve an optimal level of academic performance.     

Scheduling and resource allocation are two crucial aspects in various fields, including manufacturing, transportation, education, and information systems. The complexity of decision making is often increased by integer constraints, such as the number of workers, machines, or indivisible working hours. Therefore, the Integer Linear Programming (ILP) approach is one of the methods widely used in solving optimization problems involving discrete variables. This literature study aims to review previous studies that apply ILP in the context of scheduling and resource allocation optimization. This study reviews model approaches, solution techniques such as the branch and bound method and cutting plane, and their implementation in various real cases. The results of the study show that ILP is able to provide optimal or near-optimal solutions in scenarios with complex constraints and integer variables. This study also identifies challenges in implementing ILP models, such as the scale of the problem and high computational requirements, as well as opportunities for further research that includes hybridizing the ILP method with a heuristic approach. Thus, ILP remains a very relevant and effective tool in supporting optimization-based decision making in various sectors.

This study aims to determine the Influence of Service Attributes, Power, Attraction and Excellence on Consumer Satisfaction at CV Eko Auto Service Workshop in Harjosari II Village, Medan Amplas District. In this study, the data collection technique used the random sampling method, the sample used was 65 respondents. All analyses in this study were assisted by the SPSS 25.0 program. The data analysis technique was carried out through classical assumption tests, multiple linear regression analysis, and hypothesis testing. Based on the t-test that has been carried out, the results obtained were that the Sig. value of the Service Attribute variable was obtained at 0.001 <0.05 and the t count value (2.716)> t table (1.670). So it can be concluded that the Service Attribute variable has a positive and significant effect on the Consumer Satisfaction variable. Furthermore, the Sig. value of the Attractiveness variable obtained was 0.004 <0.05 and the t count value (3.154)> t table (1.670). So it can be concluded that the Attractiveness variable has a significant effect on the Consumer Satisfaction variable. Furthermore, the Sig. value of the Excellence variable obtained is 0.000 <0.05 which has a significant effect on the Consumer Satisfaction variable. From these data, the calculated t value is (10.882)> t table (1.670). So it can be stated that the Excellence variable has a positive and significant effect on the Consumer Satisfaction variable.

Linear programming is one of several methods for finding combinations of numbers to maximize or minimize the objective function in order to produce an optimal solution. However, manual calculations take a long time due to the complexity of the Linear Programming formula. In this paper, the author designs an application to solve web-based Two-Phase Simplex Linear Programming problems using the Angular JavaScript Framework. The application can solve Linear Program problems accurately after the mathematical model is entered. Because the method used is the Simplex Method, the application is also able to solve problems that have more than 3 decision variables. The results obtained are a combination of numbers in the decision variables along with their optimal solutions.

Efficient resource allocation is a major challenge in various sectors, especially when faced with limitations in quantity, time, and cost. This study aims to examine the application of linear programming as an optimization method in solving assignment problems, where a number of resources must be optimally allocated to a number of specific tasks. Through a literature study approach, this study examines various relevant previous study results, especially in the Indonesian context. The results of the study indicate that linear programming is able to improve operational efficiency, reduce costs, and produce a more balanced task distribution. However, this model has limitations in dealing with non-linear conditions and data uncertainty, so integration with other methods such as fuzzy logic or genetic algorithms is needed. This study is expected to broaden the understanding of the benefits of linear programming and encourage its wider application in quantitative-based decision making.

This study aims to determine the influence of company size, sales growth, independent operating costs on financial performance as measured byreturn on asset(ROA) in cosmetic companies listed on the Indonesia Stock Exchange (IDX) in 2019-2024. This research is a quantitative research, namely data in the form of numbers. The data source in this study is secondary data, namely data that is not obtained indirectly, data obtained from annual reports obtained from the company's website or from the official website of the Indonesia Stock Exchange. The population in this study is all cosmetic companies listed on the Indonesia Stock Exchange totaling 7 companies. The sample of this study uses saturated sampling where all members of the population are used as samples and the sample in this study is 42 samples. The analysis method in this study uses multiple linear regression analysis which is processed using the programSPSS versi 26.0 for windows. The results of this study indicate that company size significantly affects financial performance (ROA), sales growth does not affect financial performance (ROA), while operational costs significantly affect financial performance (ROA).

Sensitivity analysis is an important method in linear programming used to evaluate the impact of parameter changes on optimal solutions in production optimization. This study aims to identify and analyze various sensitivity analysis methods applied in previous studies. Through a systematic literature review approach, the research finds that sensitivity analysis provides valuable insights into solution stability and the effects of parameter changes on optimal outcomes. The findings indicate that this method can support better strategic decision-making in industrial contexts. The results of this research are expected to offer practical recommendations for practitioners to enhance production efficiency and effectiveness.

This study uses a qualitative method with a literature review approach to examine the effectiveness of the two-phase method in solving linear programming problems. The two-phase method is one of the techniques in linear programming used when the objective function does not have a feasible initial solution directly. Through the exploration and analysis of various scientific literature sources from 2019 onwards, this study finds that the two-phase method can systematically provide optimal solutions, especially in complex problems with multiple constraints. Previous research has shown that this method is effective in accelerating the identification of basic feasible solutions and minimizing unnecessary iterations compared to the standard simplex method. Additionally, the two-phase method offers better numerical stability and high reliability in both industrial and educational applications. However, its effectiveness largely depends on the understanding of the algorithm and the ability to design an appropriate mathematical model. The results of this study are expected to contribute theoretically to the development of efficient solution techniques for linear optimization problems.

This research employs a Systematic Literature Review (SLR) approach to analyze the application of the simplex method as a tool for solving real-world optimization problems. Mathematics education plays a crucial role in developing critical thinking and achieving accurate results. Linear programming, with its highly effective simplex method, is a branch of mathematics proven to solve various optimization challenges such as cost minimization, profit maximization, distribution, and scheduling. In practice, the simplex method is an alternative algorithm that systematically searches for the optimal solution to problems by moving from one feasible solution to another until the best result is achieved. This study identifies, examines, evaluates, and interprets relevant studies on the simplex method's application in real-world contexts. Our review of 20 journals reveals that the simplex method is highly effective in solving a wide range of optimization problems, from large-scale industries to Micro, Small, and Medium Enterprises (MSMEs). Examples of its application include optimizing fish feed costs at PT. Indojaya Agrinusa, maximizing profits for Seblak MSMEs, determining optimal sales quantities for areca nuts, and optimizing the production of tofu and pottery crafts, among others. The simplex method's ability to consider various limiting factors has proven to be extremely helpful.

This study presents a Systematic Literature Review (SLR) focusing on the application of the Branch and Bound (B&B) method in production optimization. In modern industry, achieving operational efficiency and profitability is essential, yet optimization often yields fractional solutions that are unrealistic for indivisible entities. The Branch and Bound method, as part of Integer Programming, has proven effective in addressing these constraints by converting fractional solutions into optimal integer values. This SLR analyzed 12 scientific articles published between 2016 and 2024, sourced from databases such as Google Scholar, Scopus, and SINTA. The analysis reveals that B&B is widely utilized to maximize production profit across various sectors, including spring beds, woven fabrics, bread, and furniture, often formulated as Integer Linear Programming (ILP) problems. Furthermore, this method is also applied to minimize production time and determine the shortest routes. Overall, B&B is a flexible and efficient tool that assists companies in managing resources and achieving maximum profit with realistic integer solutions.

This study aims to systematically review the application of sensitivity analysis in operational decision-making based on linear programming. The research method used is a Systematic Literature Review (SLR), analyzing scientific articles published between 2018 and 2024 from databases such as Scopus, ScienceDirect, SpringerLink, and Google Scholar. The review focuses on how sensitivity analysis is employed to evaluate the stability of linear programming solutions in the face of parameter changes, such as objective function coefficients, constraint bounds, and resource availability. The results indicate that local sensitivity analysis approaches are the most commonly used due to their simplicity and ease of interpretation. However, they fall short in capturing parameter interactions and complex uncertainty. Therefore, recent studies have started to explore global sensitivity methods, such as Morris and Sobol techniques, as well as geometric visualization approaches to provide a more holistic understanding. This study recommends integrating both local and global approaches and utilizing computational tools to enhance the robustness of operational decisions. The findings are expected to serve as a reference for more adaptive, efficient, and resilient decision-making under uncertainty.

This study aims to determine the contribution of industrial work practice (Prakerin) experience to the learning motivation of 12th-grade students in the Mechanical Engineering Department at SMKS Dhuafa Padang. A quantitative correlational research approach was employed, using a questionnaire distributed to 30 students who had participated in the Prakerin program. The results indicate a strong and significant relationship between Prakerin experience and learning motivation, with a Pearson correlation coefficient of 0.763 (Sig. < 0.001). Simple linear regression analysis shows that industrial practice experience contributes 58.3% to students' learning motivation. These findings suggest that relevant and meaningful implementation of Prakerin can encourage students to become more motivated in their academic activities at school.

This study aims to analyze the relationship between marketing strategies and customer satisfaction on e-commerce platforms in Indonesia. Effective marketing strategies are essential in facing intense competition in the digital world, especially in enhancing customer satisfaction, which influences loyalty and business sustainability. This research uses a quantitative survey approach involving 100 active users of Shopee and Tokopedia platforms. Data were collected through questionnaires and analyzed using descriptive statistics, Pearson correlation, and simple linear regression. The results indicate a positive and significant relationship between marketing strategies and customer satisfaction, with a correlation value of 0.673 and a contribution of 45.3%. Digital promotions, personalized services, and loyalty programs are key factors in improving customer satisfaction. However, customer service aspects require more attention to support overall satisfaction. This study implies that e-commerce platforms must continuously develop integrated marketing strategies alongside quality service improvements to maintain and enhance customer satisfaction.

This study aims to analyze the effect of education level, occupation, income and product price on the level of cigarette consumption in Sukolilo District, Surabaya City. The type of research used is quantitative method. The data sources used are primary data obtained from distributing questionnaires to respondents of people who actively smoke in Sukolilo District and secondary data obtained from the Central Statistics Agency (BPS) and related agencies. The method of analysis used in this study is multiple linear regression analysis with the help of the SPSS for windows program version 25.0. The population and sample in this study were 81 respondents selected using non probability sampling technique, namely accidental sampling using Isac Michel formula with 10% margin of error. Data analysis was carried out using multiple linear regression, F test, T test, and coefficient of determination (R Square). The results showed that partially education, employment, income and product prices had a positive and significant effect on the level of cigarette consumption and the coefficient of determination was 89.2%. It is hoped that this information can provide benefits to the community in Sukolilo Subdistrict or can be input for local governments and policy makers in efforts to control cigarette consumption.

This study aims to determine the influence of Profitability, Liquidity, Sales Growth, and Operating Capacity on Financial Distribution on the clothing and luxury goods sub-sector listed on the Indonesia Stock Exchange for the 2019-2023 period. The sampling technique used is  Non Probability Sampling with a sample of 9 companies in the clothing and luxury goods sub-sector listed on the Indonesia Stock Exchange for the 2019-2023 period. In this study, a multiple linear regression method was carried out assisted by the SPSS version 29 program and Microsoft Excel 2010. The results showed that (1) Profitability had no effect on Financial Distress, (2) Liquidity had an effect on Financial Distress, (3) Sales Growth had no effect on Financial Distress, (4) Operating Capacity had an effect on Financial Distress.

This study investigates the effect of environmental costs on the level of environmental information transparency in manufacturing companies in the basic materials subsector, while providing empirical evidence regarding the relationship. Environmental costs are calculated through the ratio of corporate social responsibility (CSR) burden to the organization's net profit. Meanwhile, the company's environmental performance is evaluated using the PROPER rating on an ordinal scale. The level of environmental coverage is measured comprehensively through the Clarkson index which covers various dimensions of existing reporting. A quantitative approach with multiple linear regression analysis is applied to test the relationship between variables. In selecting the sample, a purposive sampling technique was used by considering the completeness of the data and certain sector criteria, resulting in 35 companies as the final sample that met the analysis requirements. The results of the study revealed that an increase in environmental costs is directly proportional to a significant increase in environmental coverage. This indicates that company investment in environmental programs encourages more transparent reporting practices. In addition, environmental performance as reflected in the PROPER rating is also proven to have a positive and significant effect on the extent of environmental coverage.

The home industry "Eka Jaya" is a small business engaged in the production of snacks. In an effort to increase efficiency and daily profits, an optimal production planning method is needed. This study aims to maximize daily profits through the application of the simplex method in compiling the right production strategy. The simplex method is used to solve linear programming problems by maximizing the objective function in the form of profit and considering resource constraints such as raw materials, labor, and production time. The results of the study indicate that the application of the simplex method is able to provide an optimal production combination that produces maximum profit compared to the conventional method that has been used so far. Thus, this method can be used as a reference in making production decisions in the home industry "Eka Jaya".