Article Per Year (5 Year)
p-Index From 2020 - 2025
1.347
P-Index
This Author published in this journals
All Journal Dinamika Informatika Jurnal Komtika (Komputasi dan Informatika) JURNAL PENDIDIKAN TAMBUSAI Informasi Interaktif Respati Jurnal Ekonomi dan Teknik Informatika International Journal Artificial Intelligent and Informatics Techno Jurnal Indonesia Sosial Teknologi
Sudarmawan, Sudarmawan
UNiversitas AMIKOM Yogyakarta
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Indonesia Sosial Teknologi

 1 
Classification Of Malaria Types Using Naïve Bayes Classification La Ariandi, Hadin; Setyanto, Arief; Sudarmawan, Sudarmawan
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 5 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i5.1088

Abstract

This study was conducted to determine the level of accuracy of the naïve bayes classification method in the process of determining the group type of malaria. This method is used to predict the category of malaria based on the symptoms displayed. In this study, the dataset used was divided into 60% for training and 40% for testing. The results showed that the naïve bayes algorithm had an accuracy rate of 99.8% in predicting malaria categories. Evaluation of model performance using confusion matrix and ROC curve also showed good results, with classification accuracy of 0.998, error 0.002, and AUC 0.999. The results of the classification report show that the Quartana, Tertiana, and Tropica categories are more dominant than the Ovale category, based on precision, recall, and f1-score. These results show that the naïve bayes classification method is effective in classifying types of malaria and can be used as an aid in the diagnosis of malaria.
Co-Authors Abdillah, M A Abidarin Rosidi Adiwisanghagni, Mohammad Agung Mulyono Agung, Kris Ahmad Zarkasih Amrullah, Ahmad Afief Arief Setyanto Arif Rahman Arik Sofan Tohir Sofan Tohir, Arik Sofan Tohir Bambang Soedijono W A, Bambang Soedijono Eko Purwanto Ema Utami Fatkhurohman, Ari Hendrik Setiawan, Hendrik Hermanto (STMIK AMIKOM Yogyakarta) JOKO PRAYITNO Kusrini Kusrini Kusrini Kusrini Kusrini, Kusrini La Ariandi, Hadin Listyanto, Ahmad Wildan Mohammad Suyanto Napianto, Riduwan Nugroho, Muhammad Agung Nurmalasari, Maulidya Dwi Putra, Afrizal Yudano Perdana Rumini - Sukasna, Sukasna Suryadin, Imam Tri Tri Yusnanto