Teacher Salary Projections Based on Student Tuition Fees and Teacher Assessments Using Linear Regression Algorithms at the Al-Husna Foundation TPA - Saputra, Ikbal Eka; Pamungkas, R. Wisnu Prio; Hendharsetiawan, Andy Achmad (International Journal of Education, Information Technology, and Others, 2025)
Managing teacher salaries at non-formal educational institutions like Taman Pendidikan Al-Qur'an (TPA) is often done manually, leading to inefficiency, a high potential for calculation errors, and a lack of transparency. This research aims to design and build a web-based teacher payroll information system at TPA Yayasan Al-Husna that is integrated with a Linear Regression Algorithm to solve these issues. Using the Waterfall system development method, the system was built with the PHP language, the CodeIgniter framework, and a MySQL database. The result of this research is a functional system that can automate the salary calculation process based on variables such as teaching hours, attendance, and years of service, thereby significantly increasing efficiency, accuracy, and transparency. A key feature of this system is the implementation of the Linear Regression Algorithm, which was successfully used for three predictive functions: projecting the number of students, analyzing the feasibility of a teacher's salary increase based on performance evaluations, and forecasting future salary budgets. System testing using the Blackbox Testing method showed that all 30 functionality scenarios performed as expected. In conclusion, the developed system not only offers a practical solution for payroll administration at TPA Yayasan Al-Husna but also serves as a strategic decision-making tool for management through its predictive capabilities, which fills a research gap in the application of predictive models in non-formal educational institutions.