Article Per Year (5 Year)
p-Index From 2021 - 2026
0.92
P-Index
This Author published in this journals
All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika Infotekmesin Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Blend Sains Jurnal Teknik
Muhammad, Kukuh
Unknown Affiliation
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Design of the HealthyQue Mobile Application for Hospital Registration Based on Android Using the Design Thinking Approach and UML Modeling Mahardika, Fajar; Ripai, Rizki; Shandy, Sony Veri; Fazar Sidik; Pari, Riki Aldi; Muhammad, Kukuh
Blend Sains Jurnal Teknik Vol. 4 No. 2 (2025): Edisi Oktober
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v4i2.1287

Abstract

The increasing number of patient visits to hospitals each year poses challenges in providing fast and efficient services, especially during the registration process. Conventional registration systems often cause long queues and patient discomfort. This study aims to design the HealthyQue mobile application as a digital solution for hospital registration based on the Android platform. The application development follows the Design Thinking approach through five stages: empathize, define, ideate, prototype, and test, to deeply explore user needs and behaviors. The results of this process are realized in the form of system modeling using Unified Modeling Language (UML), including use case diagrams, activity diagrams, sequence diagrams, and class diagrams to structurally depict the system's workflow and architecture. This application offers features such as online patient registration, doctor schedule checking, and real-time queue notifications. The implementation of HealthyQue is expected to improve hospital administrative efficiency, reduce patient waiting times, and enhance service quality. The design results demonstrate that the Design Thinking approach effectively produces solutions aligned with user needs, while UML modeling supports the system documentation in a technical and systematic manner.
An OWL-Based Ontology Model of Food Production and Distribution in Indonesian Purwanto, Joko; Muin, Muhammad Abdul; Nugroho, Adlan; Muhammad, Kukuh
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15664

Abstract

Food security in Indonesia is influenced by the dynamics of production, distribution, and availability between regions. However, many existing information systems still rely on conventional data structures without semantic integration, which limits interoperability and hinders interregional analysis. To address this gap, this study developed an ontology model based on the Web Ontology Language (OWL) that formally represents the relationships between food production, commodity characteristics, distribution flows, food insecurity conditions, and geographical context. The ontology was built using Protégé through stages of literature review, official data collection from BPS, FAO, and the Ministry of Agriculture, conceptual model design, implementation, and evaluation. Conceptual validation was conducted through Focus Group Discussions (FGD) with food supply chain experts to ensure the suitability of the ontology structure and the actual conditions of the national food system. The technical evaluation involved consistency testing using the Pellet reasoner and Competency Question (CQ) testing through SPARQL queries to assess the ontology's ability to respond to essential information needs. The resulting ontology consists of five core classes (FoodProduction, FoodItem, FoodDistribution, FoodSecurityStatus, and GeographicRegion) which collectively represent the semantic structure of Indonesia's food supply chain. The evaluation results show that the ontology is structurally consistent and capable of producing outputs that are in line with CQ, including the retrieval of production-distribution information and the initial identification of commodity surpluses and deficits based on instance data. These findings indicate that the developed ontology provides a coherent semantic foundation for modeling food systems and has strong potential to support the development of knowledge-based food security management applications.
Pengembangan Model Random Forest untuk Prediksi Kesehatan Jiwa Berbasis Data Klinis Terstruktur dan Tidak Terstruktur Muhammad, Kukuh; Trianto, Rahmawan Bagus; Purwanto, Joko
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 3 (2025): Volume 11 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i3.100012

Abstract

Penelitian ini mengembangkan model prediksi kesehatan jiwa menggunakan algoritma Random Forest berbasis data klinis terstruktur dan tidak terstruktur dari pasien poli kejiwaan RSUD dr. R. Goeteng Taroenadibrata Purbalingga. Dataset terdiri dari 4.432 rekam medis yang mencakup parameter fisiologis serta catatan naratif yang diproses melalui cleaning, stemming Sastrawi, dan pembobotan TF-IDF. Evaluasi model dilakukan menggunakan dua skema pembagian data (85:15 dan 80:20) serta dua kondisi preprocessing (stemming dan non-stemming). Hasil menunjukkan bahwa jumlah data berpengaruh signifikan terhadap performa model, di mana akurasi meningkat dari 0,62–0,66 pada 1.000 data menjadi 0,79–0,81 pada 4.432 data. Namun, nilai presisi, recall, dan F1-score berbasis macro masih rendah akibat ketidak seimbangan kelas. Setelah diterapkan teknik oversampling SMOTE, performa model meningkat sangat signifikan dengan akurasi mencapai 0,9490 dan F1-score macro 0,9360. Pengukuran ROC-AUC sebesar 0,9991 menunjukkan kemampuan diskriminatif yang hampir sempurna. Perbandingan dengan algoritma lain menunjukkan bahwa Random Forest menghasilkan kinerja terbaik, melampaui SVM, Naive Bayes, dan Decision Tree. Hasil penelitian menegaskan potensi Random Forest untuk prediksi kesehatan jiwa berbasis data klinis terintegrasi, serta pentingnya penanganan class imbalance untuk meningkatkan performa pada kelas minoritas.
Optimalisasi Manajemen Downtime pada SIMRS dan REM di RSUD dr. R. Goeteng Taroenadibrata Purbalingga Muhammad, Kukuh; Fajar Mahardika; Rahmawan Bagus Trianto; Joko Purwanto
Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Vol. 7 No. 2 (2025): Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/abdimaspolibatam.v7i2.11194

Abstract

Guidance in managing downtime in the Hospital Management Information System (SIMRS) and Electronic Medical Records (RME) is a strategic step to maintain operational continuity and the quality of healthcare services at RSUD dr. R. Goeteng Taroenadibrata Purbalingga. Recurrent downtime negatively impacts administrative processes and medical services, necessitating systematic and continuous management. This study aims to provide technical guidance in managing downtime and to enhance the understanding and skills of human resources, particularly the Information Technology (IT) team and users of SIMRS and RME. The methods employed include technical training, identification of downtime causes, development of system maintenance procedures, and capacity building for users in operating the information systems. The results indicate that structured training and technical support can reduce downtime frequency and accelerate responses to technical disruptions. These findings highlight the importance of strengthening the IT team through ongoing training, more systematic system maintenance planning, and the establishment of clear, user-friendly operational procedures. Continuous guidance is expected to improve the effectiveness of downtime management and support the smooth delivery of healthcare services. This effort is an integral part of enhancing the quality of information systems and advancing digital transformation in healthcare services.
Support Vector Machine (SVM) - Based Optimization of Leukemia Cell Image Classification Wanti, Linda Perdana; Romadloni, Annisa; Muhammad, Kukuh; Supriyono, Abdul Rohman
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.2974

Abstract

Leukemia is a type of blood cancer characterized by the uncontrolled proliferation of abnormal white blood cells that originate from the bone marrow. Early detection of leukemia poses a significant challenge in the medical field, as the conventional diagnostic process still relies on manual microscopic observation by hematologists, which is time-consuming and prone to subjective errors. This study aims to analyze the potential of the Support Vector Machine (SVM) algorithm in optimizing the classification of leukemia cell images based on morphological and texture features extracted from microscopic images. The test results show that the SVM model with the RBF kernel provides the best performance with an accuracy of 96.4%, a precision of 95.8%, a recall of 96.1%, and an F1-score of 96.0%, surpassing the results of linear and polynomial kernels. The analysis shows that the use of a combination of shape and texture features has a significant effect on improving classification accuracy.
Co-Authors Annisa Romadloni Fazar Sidik Joko Purwanto Joko Purwanto Mahardika, Fajar Muhammad Abdul Muin Nugroho, Adlan Pari, Riki Aldi Rahmawan Bagus Trianto Rizki Ripai Shandy, Sony Veri Supriyono, Abdul Rohman Wanti, Linda Perdana