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All Journal Jurnal Informatika Dan Tekonologi Komputer Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
A. Haidar Mirza
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering Other

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Rancang Bangun Sistem Informasi Dasbor Analitik Indikator Kinerja Pelayanan Rumah Sakit (Simpel-Sifat) Berbasis Web Menggunakan Framework Laravel RSUD Siti Fatimah Juliansa Juliansa; A. Haidar Mirza
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 6 No. 2 (2026): Juli: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v6i2.7510

Abstract

The South Sumatra Provincial Hospital, RSUD Siti Fatimah, continuously generates substantial amounts of medical data across multiple departments, including outpatient, inpatient, and emergency care. However, the fragmentation of these data sources frequently hinders the effective tracking of service metrics and medical audits, complicating critical evaluation and strategic governance. To address this challenge, this research outlines the design and implementation of SIMPEL-SIFAT, a web-based analytical dashboard for monitoring hospital performance indicators, engineered utilizing the Laravel framework. The development lifecycle encompassed comprehensive requirements gathering, architectural planning utilizing the Model-View-Controller (MVC) paradigm, and backend integration using Microsoft SQL Server. Functional validation was thoroughly conducted via Black Box Testing. The resulting platform delivers dynamic visualizations of essential operational metrics—such as Bed Occupancy Rate (BOR), Length of Stay (LOS), and Turn Over Interval (TOI)—alongside robust service audit capabilities and streamlined patient data retrieval. Evaluation outcomes demonstrate that the system performs strictly in accordance with specified requirements, effectively facilitating continuous data processing and oversight. Ultimately, SIMPEL-SIFAT successfully consolidates clinical data to provide actionable insights, empowering data-driven decision-making and significantly enhancing the efficiency of monitoring frameworks at RSUD Siti Fatimah.
Penerapan Algoritma Logistic Regression Untuk Memprediksi Penyakit Jantung Muhammad Fitra Rhomadon; Wydyanto Wydyanto; A. Haidar Mirza; Nurul Huda
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i3.8105

Abstract

Heart disease is one of the leading causes of death worldwide, including in Indonesia. Early detection of heart disease risk is crucial to prevent more severe complications and improve patients' quality of life. This study aims to apply the Logistic Regression algorithm to build a data-driven heart disease prediction model. The dataset used is from Kaggle, with 1,025 patient data and 14 attributes covering risk factors such as age, gender, blood pressure, cholesterol, maximum heart rate, and others. The research process was conducted using the CRISP-DM approach, which includes business understanding, data exploration, preprocessing, modeling, evaluation, and model testing. The preprocessing stage includes data cleaning, encoding categorical variables, standardizing numeric data, and dividing the data into training and test data. The model was developed using the Python programming language and the scikit-learn library, then evaluated using metrics such as accuracy, precision, recall, F1-score, confusion matrix, and ROC-AUC. The evaluation results showed that the Logistic Regression model was able to provide good prediction results, with an accuracy of 0.93, a precision of 0.93, a recall of 0.96, and an F1-score of 0.95. With this performance, this model can be used as a tool for medical personnel in early detection of heart disease risk and supporting more effective and efficient decision-making.
Co-Authors Juliansa Juliansa Muhammad Fitra Rhomadon Nurul huda Wydyanto Wydyanto