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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF SCIENCE AND SOCIAL RESEARCH KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Jurnal Varian KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JUKI : Jurnal Komputer dan Informatika MEANS (Media Informasi Analisa dan Sistem) Jurnal Ipteks Terapan : research of applied science and education Data Sciences Indonesia (DSI) International Journal of Economic, Technology and Social Sciences (Injects)
Zakarias Situmorang
Universitas Katolik Santo Thomas
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Journal : Jurnal Tekinkom (Teknik Informasi dan Komputer)

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PERBANDINGAN AKURASI ALGORITMA NAÏVE BAYES, K-NN DAN SVM DALAM MEMPREDIKSI PENERIMAAN PEGAWAI Novendra Adisaputra Sinaga; B Herawan Hayadi; Zakarias Situmorang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.446

Abstract

To supporting academic and non-academic activities, the Polytechnic Business Indonesian (PBI) must be supported by employees with reliable Human Resources (HRD) who have good behavior, good abilities and can complete work professionally and responsibly. Conventional techniques for analyzing existing large amounts of data cannot be handled which is the background for the emergence of a new branch of science to overcome the problem of extracting important information from data sets, which is called Data Mining. Utilizing methods to classify data by utilizing methods including: Naïve Bayes method, K-Nearest Neighbor (K-NN) and Supervise Vector Machine (SVM). From this research, in Predicting Applicants Graduation at PBI, the SVM method is better than Naïve Bayes and K-NN. With 33 test data used, SVM has 84.9% accuracy, 85.1% precision while K-NN has 81.8% accuracy, 84.1% precision and Naïve Bayes has 78.8% accuracy and 80.1% precision.
Co-Authors Abwabul Jinan Ade Clinton Sitepu Ade Clinton Sitepu Aditia Rangga Agus Fahmi Limas Putra Asyahri Hadi Nasyuha B Herawan Hayadi Daim Azhari Parinduri Edunal Yoppi Erna Budhiarti Nababan Herman Mawengkang Ita Juwita Saragih Jaka Kusuma Junaidi Junaidi Jupri Manungkalit Karina Andriyani Khairul Fadhli Margolang Khoirunsyah Dalimunthe Masri Wahyuni Mawaddah Harahap Muhadi M. Ilyas Gultom Muhammad Mizan Siregar Novendra Adisaputra Sinaga P.P.P.A.N.W. Fikrul Ilmi R.H. Zer Puji Sari Ramadhan Raden Aris Sugianto Ridha Maya Faza Lubis Ridha Maya Faza Lubis Rika Rosnelly Rika Rosnelly Rimbun Siringoringo, Rimbun Roslina, Roslina Sartika Mandasari Sugeng Riyadi Valencya Lestari Wanayumini Yuni Franciska Yusniar Lubis