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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer CogITo Smart Journal Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi SENSITEK IT (INFORMATIC TECHNIQUE) JOURNAL INFOSYS (INFORMATION SYSTEM) JOURNAL DECODE: Jurnal Pendidikan Teknologi Informasi AJAD : Jurnal Pengabdian kepada Masyarakat International Journal Software Engineering and Computer Science (IJSECS) Jurnal Sains dan Ilmu Terapan Jurnal Elektronika dan Teknik Informatika Terapan
Fina Nasari
Politeknik Kampar
Aerospace Engineering Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Journal : Lontar Komputer: Jurnal Ilmiah Teknologi Informasi

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Implementation Equal-Width Interval Discretization in Naive Bayes Method for Increasing Accuracy of Students' Majors Prediction Alfa Saleh; Fina Nasari
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 9, No. 2 August 2018
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (406.221 KB) | DOI: 10.24843/LKJITI.2018.v09.i02.p05

Abstract

The Selection of majors for students is a positive step that is done to focus students in accordance with their potential, it is considered important because with the majors, students are expected to develop academic ability according to the field of interest. In previous research, Naive Bayes method has been tested to classify the student’s department based on the criteria that support the case study on Private Madrasah Aliyah PAB 6 Helvetia students and the accuracy of the test from 100 student data is 90%. in this study, the researcher developed a previously used method by applying an equal-width interval discretization that would transform numerical or continuous criteria into a categorical criteria with a predetermined k value, different k values ??would be tested to find the best accuracy value. from the 120-student data that have been tested, it is proved that the result of the classification of the application of equal-width interval discretization on the Naive Bayes method with the value of k = 8 is better and increased the accuracy value 91.7% to 93.3%.
Co-Authors Alfa Saleh Andri Nofiar Andri Nofiar Am Andri Nofiar. Am Anggun Dinda Putri Milenia Antoni Pribadi Antoni Pribadi Charles Jhony Manto Sianturi Dahriani Hakim Tanjung Fahdin Zikri Fenty Kurnia Oktorina Fitri Fitri Handayani Helmi Kurniawan Kurniawan, Helmi Labuan Nababan Muhammad Ridwan Niken Ellani Patitis Nina Veronika Nur Asma Deli Nurhayati Nurhayati Putra, Tengku Indra Ria Eka Sari Slamet Triyanto Tengku Indra Putra Vivi Elvina Simanjutak