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All Journal Jurnal Informatika Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL PENGABDIAN KEPADA MASYARAKAT Early Childhood Research Journal (ECRJ) Jurnal Sisfokom (Sistem Informasi dan Komputer) Journal of Education Technology Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJISTECH (International Journal Of Information System & Technology) JURTEKSI Jurnal Riset Informatika Jurnal Teknologi Informasi dan Pendidikan Jurnal Gema Ngabdi JIIP (Jurnal Ilmiah Ilmu Pendidikan) Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Jurnal Pengabdian Olahraga Masyarakat Jurnal Abdi Masyarakat Indonesia Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Asian Journal of Community Services (AJCS) Jurnal Pengabdian Papua Journal of Health, Education, Economics, Science, and Technology (J-HEST) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Remuz MB Kmurawak
Cenderawasih University
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Clustering for Mapping Food Insecurity in the Land of Papua: A Five-Year Multiyear Analysis with Spatial Interpretation (2020-2024) Ishak Semuel Beno; Alvian M Sroyer; Felix Reba; Remuz M. B. Kmurawak; Antonius A. P. Tama
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40366

Abstract

Food insecurity in the Land of Papua remains a critical issue due to extreme geographical conditions, limited infrastructure, and unstable food distribution systems. This study aims to map food vulnerability across 42 districts/cities in Papua using insufficient food consumption data from 2020 to 2024. Clustering was performed using five methods—Single Linkage, Complete Linkage, Ward, K-Means, and Gaussian Mixture Model (GMM)—and evaluated using three validation indices: Silhouette, Davies–Bouldin Index (DBI), and Calinski–Harabasz Index (CHI). To obtain a balanced and comprehensive model selection, a Performance-Based Weighting (PBW) framework was applied. In this framework, the DBI was first transformed to ensure a consistent higher-is-better orientation, and all validation indices were normalized to the [0,1] range prior to computing variance-based weights. This normalization step mitigates potential scale dominance, particularly from the unbounded CHI metric, ensuring proportional contribution from each validation criterion in the aggregated score. Although individual validation indices exhibited varying optimal values of k, the integrated PBW evaluation consistently identifies the two-cluster configuration as the most stable and interpretable overall structure. Specifically, Complete Linkage with k = 2 achieved the highest combined PBW score (0.8658), reflecting strong cluster separation and consistency across validation measures. Spatial interpretation of the resulting clusters reveals that the first cluster predominantly consists of high-risk mountainous districts with persistently elevated levels of food consumption inadequacy, particularly during 2021–2022, while the second cluster represents coastal and urban regions with comparatively lower and improving prevalence in 2023–2024. These findings provide a multiyear clustering perspective with geographic insight into regional disparities in food insecurity across Papua. Overall, this study presents a data-driven and reproducible multiyear clustering framework that integrates multiple validation criteria to enhance robustness in model selection and support evidence-based regional policy formulation.
Application of blockchain technology in decentralized medical data security and privacy systems Muhammad Fajar Dwi Setyoko; Muhamad Alief Firmansyah Putra; Muhammad Asghar Nazal; Remuz MB Kmurawak
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 11 No 1 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v11i1.649

Abstract

In a time when both the quantity and number of medical records are growing, protecting medical information has taken on particular significance. Medical data security and privacy are still compromised by the current system, which leaves room for manipulation and data leaks. Prior research has suggested techniques to safeguard medical data using encrypted algorithms like Blowfish and Vigenere. Nonetheless, this study suggests blockchain technology as a remedy for medical data security and decentralized data protection solutions this work, we implement decentralized data protection and medical information security using smart contracts. Smart contracts are blockchain-encoded agreements that, under specific circumstances, guarantee the contract's execution. In medical information management, smart contracts are used to control how patients, physicians, and healthcare organizations may utilize information. By doing this, patients can consent to the secure and encrypted use of their medical data, guaranteeing that only individuals with the proper authorization can access the information. In this work, we leverage smart contracts and blockchain technology to enhance the security of medical data stored in hospitals or outpatient clinics. The study's findings demonstrate that the data held in blockchains is distributed among several nodes, making them resistant to malware attacks and making the technology hard to alter
Integration of PSO-based advanced supervised learning techniques for classification data mining to predict heart failure Mesran Mesran; Remuz Mb Kmurawak; Agus Perdana Windarto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 1: February 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i1.25357

Abstract

Heart failure (HF) is a global health threat, requiring urgent research in its classification. This study proposes a novel approach for HF classification by integrating advanced supervised learning (ASL) and particle swarm optimization (PSO). ASL techniques like bagging and AdaBoost are employed within the PSO+ASL optimization model to enhance prediction accuracy. PSO optimizes model weights and bias, while ASL addresses overfitting or underfitting issues. Split validation and cross-validation (70:30, 80:20, 90:10 with k-fold=10) are used for further optimization. The testing phase involves 12 classifiers in five groups: decision tree models (DTM), support vector machines (SVM), Naïve Bayes classifiers models (NBCM), logistic regression models (LRM), and lazy model (LM). Evaluating the proposed approach with an HF patient dataset from https://www.kaggle.com, results are compared against the standard model, PSO optimization, and PSO+ASL. Experimental findings demonstrate the superiority of the proposed approach, achieving higher accuracy in HF prediction. The PSO+ASL optimization model with the k-nearest neighbor (k-NN) method exhibits the best classification performance. It consistently achieves the highest accuracy across all tests on dataset composition ratios, with 100% accuracy, f-measure, sensitivity, specificity values, and area under cover (AUC) of 1. The proposed approach serves as a reliable tool for early detection and prevention of HF.
IOT-BASED HOME AUTOMATION USING NODEMCU ESP8266 Paul K.A Windesi; Mingsep Rante Sampebua; Remuz MB Kmurawak
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i4.166

Abstract

Home automation is an automation technology that manages circuits and electronic equipment in homes, offices, and others. Home automation is a form of Internet of Things (IoT) development that allows communication and control through devices connected to the internet. This study aims to design a Home Automation prototype on lighting devices such as lamps, light sensors to activate lights, and several lights controlled using mobile devices. The research method uses the prototype method, where system development is focused on the results of input from customers who will be evaluated for software development. The stages in this research begin with analyzing device requirements, literature study, system design, hardware design, user interface design testing, and arriving at the results. This research output will be made in the form of a prototype, where all components will be placed based on the layout described in the design. This system can help users control the equipment in the house from anywhere and anytime, including using light sensors to provide input to turn the lights on or off.
Evaluating the Usability and Learning Impact of an Augmented Reality Application for World War II Historical Tourism Sites among Indonesian High School Students Agung Dwi Saputro; Theonaria Kaban; Remuz Maurenz Bertho Kmurawak; Mingsep Rante Sampebua; Ishak Semuel Beno
Journal of Education Technology Vol. 9 No. 3 (2025): August
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jet.v9i3.101048

Abstract

Education in the modern era is carried out by integrating technology to support the learning process. However, its implementation still faces several challenges, such as limited access to authentic learning resources and low student engagement due to the use of static instructional media. The developed application, BERCABAR (Belajar Cagar Budaya dengan AR), was designed using Unity 3D and Blender, combining three-dimensional models, interactive quizzes, and multimedia content accessible in offline mode. This study explores the development and effectiveness of an Augmented Reality (AR)-based learning application aimed at enhancing students’ understanding of history through interactive and contextual learning experiences. The research employed a mixed-method approach with a one-group pretest–posttest design involving secondary-level students as research participants. Quantitative data were collected through learning achievement tests and analyzed using the N-Gain test, while qualitative data were obtained through interviews and observations of user experiences. The findings revealed a significant improvement in students’ cognitive abilities, accompanied by a very high level of user satisfaction and stable system performance on mobile devices. These results affirm that the integration of AR technology has strong potential to enrich historical literacy, increase learning engagement, and offer innovative solutions for education in resource-limited environments.
Co-Authors . Supiyanto Agnes Supraptiwi Rahayu Agung Dwi Saputro Agung Dwi Saputro Agus Perdana Windarto Akhmad Kadir Albert T. Wairara Aleda Mawena Alvian M Sroyer Amelia Ludia Kafiar Andi N. Ramadhana Anton Yudi U Putra Antonius A. P. Tama Axsel Riando Soplanit Bernardo Nugroho Yahya Bevie Marcho Nahumury Bolly, Hendrikus MB Daniel Womsiwor Dewi Nurhidayah Diana Setyaningsih Evi Sinaga Felix Reba Filia Meitri Alelo Fitrine Christiane Abidjulu Ida Mariati Hutabarat Inggaber, Mamberuman Irja T. Simbiak Ishak Semuel Beno Jembise, Trajanus Laurens Jober, Naomi Frolinda Johni J Numberi Jonathan k. Wororomi Junalia Muhammad Lia Medy Tandy Lily Puspa Dewi Lisiard Dimara Lokollo, Priskila Damaris Mandang, Aditya Mandowen, Samuel Mandowen, Samuel Aleksander Mesran, Mesran Miftah Fariz Prima Putra Mingsep Rante Sampebua Mingsep Rante Sampebua Mochammad Fachorrozi Monika Gultom Muhamad Alief Firmansyah Putra Muhammad Asghar Nazal Muhammad Fajar Dwi Setyoko Naomi Frolinda Jober Oscar Oswald O. Wambrauw Oviliani Yenty Yuliana Paul K.A Windesi Paulus K A Windesi Pawan, Elvis Petrus Santoso Puteri, Qalmi Nurqalbi Jukwati Randa, Joshua Rodhi Rusdianto Hidayat S Supiyanto Samuel Piter Irab Saputro, Agung Dwi Soplanit, Axsel Riando Supiyanto Supiyanto, Supiyanto Supiyanto, . Supiyanto, S Supriyadi, Jenifer Margareth Sutoro . Tery Wanena Theonaria Kaban Tobing, Helena Trajanus Laurens Jembise Tri Setyo Guntoro Untung Muhdiarto Verhagen, Melky Welly Lokollo Wigati Yektiningtyas Worumi, Hengki Yacob Ruru Yensenem, Binyedi Binwerd Yokelin Tokoro Yos Wandik