Klasifikasi keterlambatan pembayaran sumbangan pembinaan pendidikan menggunakan algoritma Naïve Bayes dan support Vector machine

Umar, Huzaifah, Kusumawati, Ririen ORCID: https://orcid.org/0000-0001-6090-7219, Imamudin, Mochamad and Rohman, Moh. Ainur (2024) Klasifikasi keterlambatan pembayaran sumbangan pembinaan pendidikan menggunakan algoritma Naïve Bayes dan support Vector machine. Terapan Informatika Nusantara (TIN), 4 (11). pp. 709-718. ISSN 2722-7987

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Abstract

Payment delinquency of SPP is a commonly occurring issue in school. It affects the salary of teachers and staffs alongside school’s various development program. The study aims to classify payment delinquencies using Naïve Bayes and Support Vector Machine. Research methode is Cross-Industry Standard Process for Data Mining (CRISP-DM). Method testing was carried out with 5 trials. Based on the test results, the average performance of Naïve Bayes is accuracy (62,88%), precision (65,27%), recall (77,42%) dan f1-score (70,75%). Meanwhile, the average performance of the Support Vector Machine is accuracy 63,51%), precision (62,25%), recall (94,48%) dan f1-score (75,04%).

Item Type:	Journal Article
Keywords:	Classification; SPP; Naïve Bayes; Support Vector Machine; CRISP-DM
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified 08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080309 Software Engineering 08 INFORMATION AND COMPUTING SCIENCES > 0807 Library and Information Studies > 080709 Social and Community Informatics
Divisions:	Graduate Schools > Magister Programme > Graduate School of Informatics Engineering
Depositing User:	Ririen Kusumawati
Date Deposited:	27 Aug 2024 14:58

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