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Victor Saputra Ginting
Universitas Amikom, Yogyakarta

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Implementation Of C4.5 Algorithm For Predicting Late School Tuition Payments Using Python Victor Saputra Ginting; Kusrini Kusrini; Emha Taufiq
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 10, No 1 (2020): Jurnal Inspiration Volume 10 Issue 1
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v10i1.2535

Abstract

The Donation of Educational Development (SPP) School is one of the important components in implementing education, because School SPP is one of the requirements in achieving educational goals. Research conducted by Muqorobin, 2019 with the title "Optimization of the Naive Bayes Method with Feature Selection Gain for Predicting Late School Fee Payments" with Object Research conducted at SMK Al-Islam Surakarta resulted in an accuracy rate of 90%. The research was conducted by using several variables such as the amount of income, family dependents, parents 'educational background and parents' age. The research that will be carried out later will predict the late payment of School Fees by using the Dataset from the research conducted by Muqorobin, 2019 and implemented into the form of programming using the python programming language to produce prediction results. The research results obtained get an accuracy rate of 73%.