IMPLEMENTASI ALGORITMA RANDOM FOREST UNTUK KLASIFIKASI RISIKO DIABETES MELITUS TIPE 2 PADA DATA PASIEN PUSKESMAS PALMERAH

Rivaldo Elshaddai Kalona Sianturi, . (2026) IMPLEMENTASI ALGORITMA RANDOM FOREST UNTUK KLASIFIKASI RISIKO DIABETES MELITUS TIPE 2 PADA DATA PASIEN PUSKESMAS PALMERAH. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] Text
ABSTRAK.pdf
Download (229kB)
[img] Text
AWAL.pdf
Download (947kB)
[img] Text
BAB I.pdf
Restricted to Repository UPNVJ Only
Download (288kB)
[img] Text
BAB II.pdf
Restricted to Repository UPNVJ Only
Download (419kB)
[img] Text
BAB III.pdf
Restricted to Repository UPNVJ Only
Download (299kB)
[img] Text
BAB IV.pdf
Restricted to Repository UPNVJ Only
Download (544kB)
[img] Text
BAB V.pdf
Download (259kB)
[img] Text
DAFTAR PUSTAKA.pdf
Download (253kB)
[img] Text
RIWAYAT HIDUP.pdf
Restricted to Repository UPNVJ Only
Download (142kB)
[img] Text
LAMPIRAN.pdf
Restricted to Repository UPNVJ Only
Download (3MB)
[img] Text
HASIL PLAGIARISME.pdf
Restricted to Repository staff only
Download (7MB)
[img] Text
ARTIKEL KI.pdf
Restricted to Repository staff only
Download (571kB)

Abstract

This study aims to classify the risk level of Type 2 Diabetes Mellitus by applying the Random Forest algorithm using patient data from Palmerah Community Health Center in 2024. The dataset consists of patients’ medical records that have undergone data prep rocessing stages, including data cleaning, variable transformation, and the division of training and testing datasets. The Random Forest model was developed by combining multiple decision trees to produce more stable and accurate predictions. Model perform ance was evaluated using a confusion matrix, accuracy, precision, recall, and f1 -s core metrics. The results indicate that the Random Forest algorithm demonstrates good classification performance in identifying the risk of Type 2 Diabetes Mellitus. Therefor e, this model is expected to support healthcare providers at the community health center in decision -m aking processes and in implementing early prevention strategies for diabetes.

Item Type: Thesis (Skripsi)
Additional Information: [No. Panggil : 2110512063] [Pembimbing : Ruth Mariana Bunga Wadu] [Penguji 1 : Iin Ernawati] [Penguji 2 : Bambang Triwahyono]
Uncontrolled Keywords: Type 2 Diabetes Mellitus, Random Forest, Classification.
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User: RIVALDO ELSHADDAI KALONA SIANTURI
Date Deposited: 22 Apr 2026 02:18
Last Modified: 22 Apr 2026 02:18
URI: http://repository.upnvj.ac.id/id/eprint/42591

Actions (login required)

View Item View Item