KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)
Vol 9, No 1 (2022)

KLASIFIKASI DATA LULUSAN SMPN 3 TULAKAN MENGGUNAKAN METODE NAÏVE BAYES

Lesta Lia Regitaningtyas (Akademi Komunitas Negeri Pacitan)
Tamara Maharani Maharani (Akademi Komunitas Negeri Pacitan)
Bagus Hikmawan Hikmawan (Akademi Komunitas Negeri Pacitan)

Article Info

Publish Date
28 Feb 2022

Abstract

Alumni of junior high school students have a fairly diverse distribution of data. With a case study at SMP Negeri 3 Tulakan, the basis for this research is to predict the distribution of junior high school graduates in the following year. The data mining process is assisted by the WEKA application. The classification used is the nave Bayes classification using the test training set mode and cross validation folds 10. The results of this study from the test training set mode got Correctly Classified 83.2787% and Incorrectly Classified 16,7213% while in cross validation it got Correctly Classified 81.3115% and Incorrectly Classified 18.6885%. The percentage of accuracy value shows the effectiveness of the Admissions dataset applied to the Naïve Bayes Classification method which reaches 80%. The results of this study indicate that the data classification using Naïve Bayes has an accuracy level that is close to accurate.Keywords: data mining, Naive Bayes classification, student data, WEKA applicationAlumni siswa SMP memiliki persebaran data yang cukup beragam. Dengan studi kasus di SMP Negeri 3 Tulakan, menjadikan landasan pada penelitian ini untuk memprediksi persebaran lulusan Sekolah Menengah Pertama pada tahun selanjutnya. Proses data mining dibantu oleh aplikasi WEKA. Adapun klasifikasi yang digunakan adalah klasifikasi naïve bayes dengan menggunakan mode test training set dan cross validation folds 10. Hasil dari penelitian ini dari mode test training set mendapat sebesar Correctly Classified 83.2787% dan Incorrectly Classified 16.7213% sedangkan pada cross validation mendapat sebesar Correctly Classified 81.3115% dan Incorrectly Classified 18.6885%. Nilai persentase akurasi menunjukkan efektifitas dataset Admissions yang di terpkan pada metode Naive Bayes Classification yang mencapai 80%. Dari hasil penelitian ini menunjukkan bahwa klasifikasi data menggunakan Naive Bayes memiliki tingkat akurasi yang mendekati akurat.Kata kunci: data mining, klasifikasi naïve bayes, data siswa, aplikasi WEKA.

Copyrights © 2022




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)
Website

Abbrev

klik

Publisher

Universitas Lambung Mangkurat

Subject

Computer Science & IT

Description

KLIK Scientific Journal, is a computer science journal as source of information in the form of research, the study of literature, ideas, theories and applications in the field of critical analysis study Computer Science, Data Science, Artificial Intelligence, and Computer Network, published two ...