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All Journal BERKALA FISIKA JURNAL SISTEM INFORMASI BISNIS YOUNGSTER PHYSICS JOURNAL Jurnal Sains dan Teknologi Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of Physics and Its Applications Journal of Information Systems and Informatics Jurnal Fisika Indonesia JINAV: Journal of Information and Visualization Jurnal Algoritma Journal of Emerging Science and Engineering Scientific Journal of Informatics
Catur Edi Widodo
Departemen Fisika, Fakultas Sains Dan Matematika, Universitas Diponegoro, Semarang
Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Mathematics Physics

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Journal : Journal of Information Systems and Informatics

 1 
Application of Life Simulation Games in Teaching Network Security and Cryptography Taufani, Agusta Rakhmat; Soeprobowati, Tri Retnaningsih; Widodo, Catur Edi
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1161

Abstract

Information security-related mathematical methods are used in the science of cryptography. A collection of methods that offer information security, cryptography is more than just a means of concealing messages. Using only presentation slides or video links at each meeting, the interaction between lecturers and students via SIPEJAR e-learning hinders the Network Security and Cryptography learning process at the State University of Malang (UM) Information Engineering (IT) Undergraduate Study Program. To help students learn more about the area of encoding using SIPEJAR, a game that explicitly explains cryptography was created using these several challenges as the background. The creation of a cryptographic life simulation game is intended to serve as a teaching and learning aid for lecturers and students. Students are expected to better understand related material in a learning atmosphere that is new, more interesting, opens the horizons of the mind, and is more investigative. After going through the equivalence partitioning testing process, in general this system produces a total percentage of 100% in system item test success in the testing process of the 6 item tests carried out and a respondent satisfaction percentage of 84.3%. Thus, the system is running according to the prototype design.
Global Research Trends and Map on Machine Learning Applications in Stunting Detection in Vulnerable Populations: A Bibliometric Analysis Bachri, Otong Saeful; Widodo, Catur Edi; Nurhayati, Oky Dwi
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1248

Abstract

Stunting and malnutrition continue to be significant public health challenges, particularly in low-income and rural populations. With the growing reliance on data-driven strategies in public health, machine learning (ML) has emerged as a promising tool for identifying, classifying, and predicting conditions related to undernutrition. This study presents a bibliometric analysis of global research from 2019 to 2025, focusing on the application of ML techniques—such as clustering, support vector machines (SVM), and random forest—in addressing malnutrition and stunting. A total of 417 Scopus-indexed publications were analyzed using Biblioshiny (R) to assess research trends, key themes, influential authors, prominent journals, and thematic evolution. The analysis reveals a consistent growth rate of 10.72% in publications, with notable contributions from China and other low- and middle-income countries. Keyword mapping highlights that “machine learning,” “spatial analysis,” and “stunting” are central to the research, although they remain areas for further development. Thematic evolution indicates a shift towards more integrated, context-aware approaches, with a growing focus on built environments and vulnerable populations. The study concludes that while ML holds significant promise for advancing decision-making in child health and nutrition, its impact will depend on continued methodological refinement and effective implementation within public health systems.
Co-Authors Agusta Rakhmat Taufani Aprilia Ayu Andarinny Arif Setiawan Budi Warsito Choirul Anam AM Diponegoro Didik Supriyadi, Didik Eko Sediyono Fatkhur Rohman Figur Humani Fitra Nur Asri, Muh H Hadiyanto Hadyan Arifianto Husen Nasrullah Armin I Gusti Bagus Wiksuana Irwan Agus Saputro Isnain Gunadi Iswanti, Arie Jatmiko Endro Suseno K. Sofjan Firdausi Kusworo Adi Kuworo Adi Labib Mustofa, Refo Labib Mustofa, Tarno Muchammad Azam, Muchammad Mustafid Mustafid Oky Dwi Nurhayati Otong Saeful Bachri R Rizal Isnanto R. Rizal Isnanto Rachmat Gernowo Rahmatika, Yuni Ramanda, Febri Retno Hapsari, Angga Ayu Rizky Ayomi Syifa Romadhon, Zainur Royani, Noorhanida Saitem Saitem Salsabila Naqiyah Sri Mulyani Tri Retnaningsih Soeprobowati Tutur Urip Ucky Pradestha Novettralita Wahyu Adi Wibowo Yulaikha Maratullatifah Zainal Bachrudin