IMPLEMENTASI REGRESI LINIER BERGANDA DALAM PREDIKSI PENDAPATAN PADA SISTEM INFORMASI KEUANGAN PRAKTIK MANDIRI - ANAS NASRULLAH; Mundirin; Deden Hedin Purnama Binaefsa (Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, 2026)
Manual financial record-keeping in Praktik Mandiri results in ineffective financial management and revenue prediction. This study aims to develop a web-based Financial Information System by implementing the Multiple Linear Regression method to predict monthly revenue. The system was developed using the Agile methodology. The research dataset consists of 49 months of historical financial data (June 2022–June 2026). The predictor variables include the number of patient visits, total operational expenses, and the number of practice days, while net revenue is used as the target variable. Functional testing was conducted using Black Box Testing, user evaluation was carried out using a Likert scale, and model validation was performed using RapidMiner Studio. The prediction model achieved a MAPE of 7.88% and an RMSE of IDR 3,969,764, while the RapidMiner validation produced identical results. These findings indicate that the implemented model is consistent with the validation results and is capable of supporting financial management and monthly revenue prediction.