Sistem Deteksi Penyakit Tuberkulosis Paru Dengan Metode Naïve Bayes di Puskesmas Jelbuk

Fitriana, Laili (2026) Sistem Deteksi Penyakit Tuberkulosis Paru Dengan Metode Naïve Bayes di Puskesmas Jelbuk. Undergraduate thesis, Politeknik Negeri Jember.

[img] Text (Abstract)
Abstract .pdf - Submitted Version
Available under License Creative Commons Attribution Share Alike.

Download (259kB)
[img] Text (Bab 1 Pendahuluan)
Bab 1 Pendahuluan.pdf - Submitted Version
Available under License Creative Commons Attribution Share Alike.

Download (287kB)
[img] Text (Daftar Pustaka)
Daftar Pustaka.pdf - Submitted Version
Available under License Creative Commons Attribution Share Alike.

Download (276kB)
[img] Text (Laporan Lengkap)
Laporan Lengkap.pdf
Restricted to Registered users only

Download (4MB) | Request a copy

Abstract

Tuberculosis is an infectious disease that remains a health problem in Indonesia. The number of suspected tuberculosis cases at the Jelbuk Community Health Center has increased year by year, necessitating a system that can assist in early detection. This study aims to design and build a pulmonary tuberculosis detection system using the Naive Bayes method. The data used came from 228 medical records at the Jelbuk Community Health Center, and after going through the preprocessing stage, 140 data were obtained for analysis. The variables studied included coughing for more than 2 weeks, coughing up phlegm and blood, decreased appetite, weight loss, malaise, night sweats, fever, and shortness of breath. Based on the results of the cross-tabulation analysis, coughing for more than 2 weeks was the variable with the highest proportion of tuberculosis cases. Data distribution used a stratified sampling technique with a ratio of 80:20, namely 112 training data and 28 testing data. Model evaluation using a confusion matrix yielded an accuracy of 92.86%, with precision and recall for the tuberculosis class of 87.50% and 100%, respectively, and for the non-tuberculosis class of 100% and 85.71%. The results showed that the Naïve Bayes algorithm performed very well in classifying tuberculosis. Based on these results, a website-based detection system was developed using the waterfall method. Blackbox testing demonstrated that all system functions ran according to user requirements.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDK
Thesis advisorPrakoso, Bakhtiyar HadiNIDN198804042019031013
Uncontrolled Keywords: Tuberkulosis, Sistem Deteksi Penyakit, Algoritma Naïve Bayes, Waterfall
Subjects: 340 - Rumpun Ilmu Kesehatan > 350 - Ilmu Kesehatan Umum > 351 - Kesehatan Masyarakat
340 - Rumpun Ilmu Kesehatan > 370 - Ilmu Keperawatan dan Kebidanan > 379 - Analis Medis
340 - Rumpun Ilmu Kesehatan > 350 - Ilmu Kesehatan Umum > Sistem Informasi Kesehatan
Divisions: Jurusan Kesehatan > Prodi D4 Manajemen Informasi Kesehatan > Tugas Akhir
Depositing User: Laili Fitriana
Date Deposited: 23 Jul 2026 00:53
Last Modified: 23 Jul 2026 00:53
URI: https://sipora.polije.ac.id/id/eprint/58551

Actions (login required)

View Item View Item