Alfiansyah, Deden Moh
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Journal : Building of Informatics, Technology and Science

Prediksi Keterlambatan Pembayaran SPP Siswa dengan Pendekatan Metode Naive Bayes dan K-Nearest Neighbors Alfiansyah, Deden Moh; Soetanto, Hari
Building of Informatics, Technology and Science (BITS) Vol 5 No 4 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i4.4643

Abstract

Education in Indonesia faces cost challenges which have an impact on the provision of education, especially Education Development Contributions (SPP) in private schools. This research aims to improve the administrative efficiency of student tuition payments at Wirasaba Karawang Vocational School through a classification approach. 725 payment data for one semester in 2023 are used to predict payment delays. About 22% of students experience delays. By understanding delay patterns, this research proposes solutions to improve administrative efficiency with appropriate preventive measures. The hope is that the results of this research can provide benefits to Vocational School Wirasaba Karawang and contribute to the development of a more efficient education administration system, thereby improving education services in Indonesia as a whole. This research describes the problem of late SPP payments, applies a classification method to predict these delays, aims to increase the efficiency of payment administration, and has the potential to provide preventive solutions that can reduce late payments. The contribution of this research is the development of a more efficient education administration system through an information technology approach, with interim results in the form of analysis of late payment patterns based on 2023 data from Wirasaba Karawang Vocational School