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All Journal Jurnal Ilmiah Sinus
Muqorobin Muqorobin
Program Pascasarjana Teknik Informatika, Universitas Amikom Yogyakarta
Computer Science & IT

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OPTIMASI METODE NAIVE BAYES DENGAN FEATURE SELECTION INFORMATION GAIN UNTUK PREDIKSI KETERLAMBATAN PEMBAYARAN SPP SEKOLAH Muqorobin Muqorobin; Kusrini Kusrini; Emha Taufiq Luthfi
Jurnal Ilmiah SINUS Vol 17, No 1 (2019): Vol. 17 No. 1 Januari 2019
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (703.712 KB) | DOI: 10.30646/sinus.v17i1.378

Abstract

The cost of education is one component of input that is very important in implementing education. Because costs are the main requirement in an effort to achieve educational goals. SMK Al-Islam Surakarta is a private education institution that requires students to pay school fees in the form of Education Development Donations. Educational Development Donation is a routine school fee that is conducted every month. Based on last year's TU report, many students were late in paying Education Development Donations, around 60%. This is a big problem. The purpose of this study is that researchers will build a predictive system using the Naïve Bayes method. Because the method can classify the class right or late, in the payment of school fees. Data processing was taken from the dapodik data of schools in 2017/2018 with the test dataset taking 30 records. To find out the level of accuracy, this research was conducted with the Naive Bayes Method and the Information Gain Method for feature selection. Accuracy testing is done by the Confusion Matrix method. The results showed that the highest accuracy was obtained by combining the Naive Bayes Method with the Information Gain Method obtained by 90% accuracy. 
Co-Authors Emha Taufiq Luthfi Kusrini Kusrini