Algoritma Regresi Linier Dalam Prediksi Jumlah Pendaftar Program Pendidikan Di Lingkungan Pesantren : Studi Kasus : Yayasan Al-Mustofa Tambakbaya - Agustin, Yoga Handoko; Satria, Eri; Nasrulloh, Anas (Jurnal Algoritma, 2025)
Al-Mustofa Tambakbaya Foundation manages an Islamic boarding school as well as a Madrasah Aliyah (MA) and Madrasah Tsanawiyah (MTS). Over the past five years, the foundation has experienced fluctuations in the number of new students. This study aims to predict the number of applicants using a linear regression algorithm. The challenge of fluctuating enrollment affects resource planning and curriculum development. The data used includes the number of MA and MTS students from the 2019 to 2023 academic years. This research follows the CRISP-DM stages, starting from business understanding, data collection and preparation, to modeling using linear regression. Model evaluation is done with MAPE, MAE, RMSE, and R-squared. The results show that the model for Regional Domicile and Outside the Region has a MAPE of 8.44% and 12.76%, respectively. The model for MTS students has a MAPE of 6.26% and an R-squared of 91.27%, while the MA student model shows the lowest performance with a MAPE of 20.56% and an R-squared of 21.20%. Predictions for the 2024 academic year show significant growth, especially in regional domicile and MA students. This research offers a practical solution to address fluctuations in enrollment and educational planning at Al-Mustofa Tambakbaya Foundation, as well as highlighting the need for model improvements to increase accuracy in the future.