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Journal : Journal of Information Technology and its Utilization

Implementation of Collision Avoidance System Algorithm in NPC Game 3D Gugah Alwan Hamanako; Adi Sucipto
Journal of Information Technology and Its Utilization Vol 6 No 1 (2023): June 2023
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.6.1.4988

Abstract

Nowadays, with the rapid development of technology, we are given the convenience of finding entertainment such as games. Now this game can be quickly run on various media, one of them is a smartphone. Most smartphones' operating systems (OS) are Android and IOS. Among the both of OS which is currently popular is Android. This research aims to create an Artificial Intelligent of Non-Player Character (NPC) that can avoid every obstacle using the Collision Avoidance System algorithm. The result of the research is an android game app that applies the Collision Avoidance System that can make AI NPC avoid obstacles. The application of the algorithm to the NPC is made in 3 stages, namely, design by making a flowchart of the algorithm, then writing a program from the Collision Avoidance System, and finally, testing the AI ​​NPC. The test is carried out by comparing the reactions of NPC 1 and NPC 2 in passing through obstacles when on different paths by being carried out jointly between NPC. Based on the tests on AI NPC, NPC managed to avoid obstacles in front of them and the players, and it is almost 93% successful. 
Enhancing Maritime Safety Education through Mobile Gamification: Development and Design of an Android-Based Learning Game for Safe Working Practices on Board Ship Atmaja Septa Miyosa; Aka Shakthi Avri Afika; Restu Bumi Krisaputra Krisaputra; Muhammad Irfan Hanafi; Firdi Kurnia Rahman; Tri Anggraeni; Adi Sucipto
Journal of Information Technology and Its Utilization Vol 7 No 2 (2024): December 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.2.5996

Abstract

Semarang Maritime Polytechnic (PIPS) requires an Android-based English learning tool that is integrated with courses related to work safety on ships. This study aims to create an English learning tool that is integrated with courses related to work safety on ships in the form of a quiz and is Android-based. The development of this game uses the Game Development Life Cycle (GDLC) method which is a guideline that includes the game development process (Hendrick in Ramadan and Widyani, 2013). This method consists of six development phases: Initiation, Pre-production, Production, Testing, Beta testing, and Release. This application is called "Safe Working Practices on Board Ship" and is expected to be an alternative or new media for students to practice their English language skills while understanding work safety on ships.
The Clustering of Ranting Muhammadiyah Using the K-MODES Algorithm Sucipto, Adi
Journal of Information Technology and Its Utilization Vol 8 No 2 (2025): December 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.2.6066

Abstract

Research on Muhammadiyah often focuses on its preaching models, responses to various conditions, and strategies in proselytization or resource management, but there is limited exploration of the Muhammadiyah organization itself. Specifically, the condition of Pimpinan Ranting Muhammadiyah (The Leader of Muhammadiyah Sub-Branch or PRM) as the lowest organizational structure, is seldom addressed. Currently, the LPCR utilizes SICARA to categorize organizations based on scores reflecting routine activities, yet it does not map these organizations based on similar potential. Thus, there is a need for a method to group these organizations based on a condition mapping to facilitate targeted revitalization efforts. This study aims to cluster PRM based on the Branch and Sub-branch Information System (Sistem Informasi Cabang dan Ranting or SICARA) questionnaire responses. Given that the SICARA questionnaire data is categorical, the K-MODES method was chosen for clustering. The optimal number of clusters was determined using the elbow method. The resulting clusters, derived using the elbow method, there are eight clusters, each exhibiting distinct characteristics.