SISTEM REKOMENDASI PENERIMAAN MAHASISWA BARU MENGGUNAKAN NAIVE BAYES CLASSIFIER DI INSTITUT PENDIDIKAN INDONESIA

Andri Suryadi, Erwin harahap

Sari


The quality of a university in creating qualified graduates is determined by the prospective students who enter the college. One of the things that can determine the quality is how the selection process of candidates for good student acceptance. However, the selection process of admissions in every college of course is different. Often the input of prospective students who enter the university is not in accordance with the expected so that the impact of graduate results. Therefore it is necessary for a system that can support the decision in the selection of new student candidates in order to get a good student input. This research builds a Recommendation System that will assist in the selection process of universities for the selection team of new student candidates. This recommendation system uses the naïve Bayes classifier method where the test scores of incoming selection of students who have been accepted will be used as training data and then classified based on the value of ipk that has been obtained. The value of the ipk will be a benchmark for the formation of classes - classes that are recommendations to the selection team. The classes that are formed are classes whose ipk value is at the accepted point and the class whose ipk value is not accepted. Then given a new student data, if the prospective student enters the safe class then it will be recommended to be accepted but otherwise it will be recommended to be rejected

Kata Kunci


Recommendation System, Naïve bayes Classifier, College

Teks Lengkap:

PDF

Referensi


A. G. Mabrur and R. Lubis.2012. "Penerapan Data Mining untuk Memprediksi Kriteria Nasabah Kredit," Jurnal Komputer dan Informatika (KOMPUTA), vol. 1, pp. 53-57

Fahrurozi Achmad. 2014. Klasifikasi Kayu Dengan Menggunakan Naive Bayes-Classifier. KNM XVII ITS Surabaya

Giovani, Ronny Ardi.2011. Sistem Pendukung Keputusan Prediksi Kecepatan Studi Mahasiswa Menggunakan Metode ID3. Universitas Atmajaya Yogyakarta.

Mustaqbal1.M. Sidi, Firdaus.Roeri Fajri , Rahmadi.Hendra. 2015 . Pengujian Aplikasi Menggunakan Black Box Testing Boundary Value Analysis.Jurusan Teknik Informatika, Fakultas Teknik, Universitas Widyatama. Jurnal Ilmiah Teknologi Terapan ISSN : 2407 – 3911.

Nugroho Yuda Septian. Data Mining Menggunakan Algoritma Naive Bayes Untuk Klasifikasi Kelulusan Mahasiswa Universitas Dian Nuswantoro. Jurusan Sistem Informasi, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Pressman, Roger S. 2002.”Rekayasa Perangkat Lunak (Pendekatan Praktis).” Yogyakarta : Andi.

Rodiyansyah, Sandi Fajar dan Winarko Edi.2012. Klasifikasi Posting Twitter Kemacetan Lalu Lintas Kota Bandung Menggunakan Naive Bayesian Classification. FPMIPA UGM Yogayakarta

S Andri, E Harapap.2017. Pemeringkatan Pegawai Berprestasi Menggunakan Metode AHP (Analytic Hierarchy Process) di PT. XYZ. Jurnal Teori dan Terapan Matematikan Vol.16 No.2 2017

Shalahuddin, M dan Rosa AS. 2014. Rekayasa Perangkat Lunak terstruktur dn berbasis Objek. INFORMATIKA

Sommerville.Ian.2004.Software Enggineering:7th Edition. McGraw-Hill

Suryadi.Andri, Nurdiana, Dian.2015. Sistem Pengambilan Keputusan Untuk Pemilihan Teknisi Lab Dengan Multi Kriteria Menggunakan Metode Ahp (Analytic Hierarchy Process). Jurnal Mosharafa Vol.4 No.1 Januari 2015

Suryadi.Andri, Nurdiana Dian.2016. Sistem Pendukung Keputusan Seleksi Ujian Masuk Perguruan Tinggi Menggunakan Nbc (Naïve Bayes Classifier). Jurnal Kinetik Vol.1 No.3 2016 Hal 173-182

Suryadi,. Andri.2015. PERANCANGAN APLIKASI TES BERBASIS KOMPUTER (CBT) MENGGUNAKAN PENDEKATAN TERSTRUKTUR UNTUK PENERIMAAN MAHASISWA BARU DI PERGURUAN TINGGI. Petik Vol.1 No.1 2015 Hal. 68-81.

Wahyunningrum.Tenia, Januarita.Dwi.2015. Implementasi dan Pengujian Web E-commerce untuk Produk Unggulan Desa. Jurnal Politeknik Caltex Riau Vol.1 no.1 hal 57-66.




DOI: https://doi.org/10.30736/jti.v3i2.231