PERANCANGAN SISTEM PAKAR UNTUK MEMPREDIKSI PENYAKIT DIABETES MELLITUS TIPE 2 (STUDI KASUS: PUSKESMAS KECAMATAN TAMAN SARI)

Muhammad Hidayatullah, . (2025) PERANCANGAN SISTEM PAKAR UNTUK MEMPREDIKSI PENYAKIT DIABETES MELLITUS TIPE 2 (STUDI KASUS: PUSKESMAS KECAMATAN TAMAN SARI). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] Text
ABSTRAK.pdf

Download (13kB)
[img] Text
AWAL.pdf

Download (834kB)
[img] Text
BAB I.pdf
Restricted to Repository UPNVJ Only

Download (40kB)
[img] Text
BAB II.pdf
Restricted to Repository UPNVJ Only

Download (324kB)
[img] Text
BAB III.pdf
Restricted to Repository UPNVJ Only

Download (56kB)
[img] Text
BAB IV.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB V.pdf

Download (15kB)
[img] Text
DAFTAR PUSTAKA.pdf

Download (144kB)
[img] Text
LAMPIRAN.pdf
Restricted to Repository UPNVJ Only

Download (2MB)
[img] Text
DAFTAR RIWAYAT HIDUP.pdf
Restricted to Repository UPNVJ Only

Download (67kB)
[img] Text
HASIL PLAGIARISME.pdf
Restricted to Repository staff only

Download (17MB)
[img] Text
ARTIKEL KI.pdf
Restricted to Repository staff only

Download (271kB)

Abstract

Type 2 Diabetes Mellitus continues to rise globally, including in Kecamatan Taman Sari. Based on the interview results, the number of Type 2 Diabetes Mellitus cases in this area increases by approximately 200 to 500 cases each year. This rise is caused by unhealthy dietary habits containing high sugar content and a lack of physical activity. Puskesmas Taman Sari also faces challenges, as most patients only seek medical attention after symptoms appear or when the condition has become chronic. This study aims to design an expert system that can assist the public in predicting the likelihood of developing Type 2 Diabetes Mellitus. The method used is forward chaining, a reasoning technique in expert systems that processes facts sequentially based on rules obtained from experts and relevant literature. The system was developed using the Streamlit framework with Python, CSS, and MySQL programming language. Testing results show that the expert system can provide predictions with an accuracy rate of 100%, based on the rules defined by medical expert. Furthermore, the User Acceptance Testing (UAT) yielded a score of 81.06% from users and 90.79% from experts, indicating that the system meets the expected functional and usability standards.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2110512066] [Pembimbing 1: Andhika Octa Indarso] [Pembimbing 2: Nindy Irzavika] [Penguji 1: I Wayan Widi Pradnyana] [Penguji 2: M. Bayu Wibisono]
Uncontrolled Keywords: type 2 diabetes mellitus, puskesmas taman sari, forward chaining, expert system, user acceptance testing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User: MUHAMMAD HIDAYATULLAH
Date Deposited: 08 Jul 2025 08:04
Last Modified: 06 Aug 2025 01:33
URI: http://repository.upnvj.ac.id/id/eprint/37340

Actions (login required)

View Item View Item