Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Aston Maruli Sitompul
STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara, Indonesia
Computer Science & IT Control & Systems Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Teknik Data Mining Dalam Prediksi Jumlah Siswa Baru Dengan Algoritma Naive Bayes Aston Maruli Sitompul; S Suhada; S Saifulah
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 2 (2021): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i2.65

Abstract

Sukosari Public Elementary School 095126 is an elementary school located in Gunung Malela sub district, Simalungun Regency. Prediction is an important tool in planning effective and efficient, especially in the field of education. In the modern world knowing the situation to come is not only important to see the good or bad but also aims to make forecast preparation. An important step after a prediction has been made is to verify the prediction in such a way that it reflects past data and the underlying system that underlies the request. As long as the prediction representation can be trusted, the predicted results can continue to be used. Schools are formal educational institutions that systematically carry out guidance, teaching, and training programs in order to help students to be able to develop their potential both in terms of moral, spiritual, intellectual, emotional and social aspects. The inference method used is the Naive Bayes method, the system will input student data such as the criteria needed for admission of new students at SD N 095126 Sukasari by collecting data on Indonesia Smart Cards (KIP), BPJS cards, Parent income, these data will be grouped and obtained from the past period is processed into the system and training process with the Rapid Miner application.
Co-Authors S Saifulah S Suhada