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All Journal Jurnal Ilmiah FIFO JUTIK : Jurnal Teknologi Informasi dan Komputer METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi International Journal of New Media Technology Jurnal ULTIMATICS Jurnal PTK dan Pendidikan JOISIE (Journal Of Information Systems And Informatics Engineering) Journal of Information System, Applied, Management, Accounting and Research Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik JMECS (Journal of Measurements, Electronics, Communications, and Systems) Jurnal Teknik Informatika Jurnal Ilmu Siber
Cian Ramadhona Hassolthine
Universitas Siber Asia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences Other

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Journal : Jurnal ULTIMATICS

 1 
Implementation of Gamification Method and Fisher-Yates Shuffle Algorithm for Design and Development Django Learning Application Kiswara, Ade; Tobing, Fenina Adline Twince; Hassolthine, Cian Ramadhona; Saputra, Muhammad Ikhwani
Ultimatics : Jurnal Teknik Informatika Vol 16 No 2 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i2.3874

Abstract

The web framework emerges as a solution to enhance web development efficiency. Django, an open-source web framework written in the Python programming language, is one of the popular frameworks. Currently, there are not many programming learning platforms that provide specific programming learning materials for Django, implementing a method to boost user interest in using the platform. This research aims to design and build a web-based Django learning application using gamification methods designed based on the octalysis framework to enhance user learning interest. It also incorporates the Fisher-Yates shuffle algorithm to randomize questions for more variety. The application was tested by several users by filling out a questionnaire prepared using the Hedonic Motivation System Adoption Model (HMSAM). The evaluation results of the application obtained an average percentage of 84,15% in the aspect of behavioral intention to use, which means users strongly agree that the djangoing application generates a desire to use it again in the future. Furthermore, the results in the aspect of immersion were 81,44%, which means users agree that the djangoing application creates an immersive learning experience for the Django framework.
Implementation of Gamification Method and Fisher-Yates Shuffle Algorithm for Design and Development Django Learning Application Kiswara, Ade; Tobing, Fenina Adline Twince; Hassolthine, Cian Ramadhona; Saputra, Muhammad Ikhwani
ULTIMATICS Vol 16 No 2 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i2.3874

Abstract

The web framework emerges as a solution to enhance web development efficiency. Django, an open-source web framework written in the Python programming language, is one of the popular frameworks. Currently, there are not many programming learning platforms that provide specific programming learning materials for Django, implementing a method to boost user interest in using the platform. This research aims to design and build a web-based Django learning application using gamification methods designed based on the octalysis framework to enhance user learning interest. It also incorporates the Fisher-Yates shuffle algorithm to randomize questions for more variety. The application was tested by several users by filling out a questionnaire prepared using the Hedonic Motivation System Adoption Model (HMSAM). The evaluation results of the application obtained an average percentage of 84,15% in the aspect of behavioral intention to use, which means users strongly agree that the djangoing application generates a desire to use it again in the future. Furthermore, the results in the aspect of immersion were 81,44%, which means users agree that the djangoing application creates an immersive learning experience for the Django framework.
Design and Evaluation of an AI-Driven Gamified Intelligent Tutoring System for Fundamental Programming Using the Octalysis Framework Dzaky Fatur Rahman; Tobing, Fenina Adline Twince; Hassolthine, Cian Ramadhona
ULTIMATICS Vol 17 No 2 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i2.4514

Abstract

This research aims to address the challenges of student motivation and engagement in fundamental programming education by implementing the Octalysis Gamification Framework within an Intelligent Learning System. Traditional learning methods often fail to visualize abstract concepts or provide personalized feedback, leading to student demotivation. To overcome this, a platform named "Starcoder" was designed and built, integrating two conceptual pillars: the eight core drives of the Octalysis Framework and an AI-supported Intelligent Tutoring System (ITS). The system employs the Next.js framework and integrates the Gemini AI API (M.E.C.H.A.) to provide real-time, adaptive feedback and remedial learning paths. The effectiveness of the platform was evaluated using the Hedonic-Motivation System Adoption Model (HMSAM) with 54 respondents, comparing the gamified platform against traditional classroom methods. Evaluation results demonstrate that the platform significantly outperforms traditional methods, achieving an 86.44% score in Perceived Usefulness and an 85.56% score in Curiosity. Notably, Behavioral Intention to Use increased by 15.56% compared to the baseline. These findings demonstrate that the comprehensive integration of gamification frameworks with generative AI agents effectively enhances student motivation and immersion in technical education. Future work should focus on expanding the AI's capability to dynamically adjust gamification elements in real-time based on student performance.
Co-Authors Adline Twince Tobing, Fenina Alif Widiyanto Anna’im, Moh Armansyah, Syahrul Nur Aziz, Siti Nur Farrah Catur Nugroho Chandra, Darren Denisson Chusyairi, Ahmad Dzaky Fatur Rahman Fandi Chriswantoro Putro Haq, Fesa Asy Syifa Nurul Indriani, Melati Kiswara, Ade Kurniati Asmar, Kurniati kusnadi, adhi Lukman Medriavin Silalahi Maulana, Rijwan Mekeng , Ambros Magnus Rudolf Muhammad Ikhwani Saputra Muhammad Ikhwani Saputra Muliati, Vika Febri Nainggolan, Rena Novi Dian Nathasia Nur Iman Riad Sahara Rumbaman, Wulan Nursyifa Saputra, Muhammad Ikhwani Syahid Abdullah Teguh Yuhono Tobing, Fenina Adline Twince Toto Haryanto