SISTEM INFORMASI JURNAL PENELITIAN DAN
PENGABDIAN PADA MASYARAKAT UNIVERSITAS
MUHAMMADIYAH GORONTALO DENGAN MENERAPKAN
METODE NAIVE BAYES
Total View This Week0
Total View This Week0
Institusion
Universitas Muhammadiyah Gorontalo
Author
Sako, Febriyanto
Subject
QA75 Electronic computers. Computer science
Datestamp
2023-02-16 07:08:56
Abstract :
This study aimed at building an information system for the classification of journals in the Institute of Research and Community Service, Universitas Muhammadiyah Gorontalo. This information system was built by using the Naive Bayes classification method with prototype design. Before doing classification, the term weighting process was carried out by using TF-IDF (Term Frequency and Inverse Document Frequency) and looked for the journal and words probability values in the testing data. By adding up the two probability values in each categories, the highest probability value can be obtained. The results of the probability value calculation showed that there are 23 categories of journals that were successfully classified from 113 journal data that consist of 79 training data and 34 test data, there are 23 categories of journals that were successfully classified.
This study aimed at building an information system for the classification of journals in the Institute of Research and Community Service, Universitas Muhammadiyah Gorontalo. This information system was built by using the Naive Bayes classification method with prototype design. Before doing classification, the term weighting process was carried out by using TF-IDF (Term Frequency and Inverse Document Frequency) and looked for the journal and words probability values in the testing data. By adding up the two probability values in each categories, the highest probability value can be obtained. The results of the probability value calculation showed that there are 23 categories of journals that were successfully classified from 113 journal data that consist of 79 training data and 34 test data, there are 23 categories of journals that were successfully classified.
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
