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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sistem Informasi The Indonesian Journal of Computer Science
Panca Oktavia Hadi Putra
Universitas Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Gamification-based The Kampus Merdeka Learning in 4.0 era Qurotul Aini; Mukti Budiarto; Panca Oktavia Hadi Putra; Nuke Puji Lestari Santoso
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 15, No 1 (2021): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.59023

Abstract

Recently, education has been enlivened by the presence of the Merdeka Campus program initiated by Nadiem Makarim. It uses the Kampus Merdeka concept to learn to follow the development of education in the 4.0 era. This change has become a paradigm for Higher Education to build a Merdeka Campus to learn to face challenges in the 4.0 era. However, the challenge is not easy for universities, so that students join the independent program to learn quickly. This study aims to motivate students to participate in independent learning activities in a collaborative learning system with gamification techniques. Gamification is in the form of reward badges for student achievement in all learning activities carried out. The higher education independent learning system is designed using the library study method and Agile Development with two frameworks, namely Laravel and VueJS. It can be proven from the results of the SUS Score Analysis showing the number 92.5 indicating that the independent learning campus system provides positive benefits by gamification of students being more motivated and ready to face learning challenges in the 4.0 era.
The Application of Game Mechanics and Technological Trend in Game-Based Learning: A Review of the Research Mhd. Adhitiya Okta Riyandi; Harry Budi Santoso; Panca Oktavia Hadi Putra
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 4 (2023): August 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i4.4928

Abstract

The rapid development of information technology affects numerous aspects of human life, including education. An example of an IT application in education is game-based learning. Game-based learning has been implemented in various fields or subjects on various platforms. This is due to the potential of game-based learning to enhance student engagement in the learning process. However, the effectiveness of this method needs to be further studied. This systematic review of the literature aimed to explore the mechanics of games that are applied in current research on game-based learning, accompanied by the trend of technological use in research papers published in this domain. This study covered 30 journal and conference proceedings papers published from 2012-2022. The review was conducted using the Kitchenham method. The selected articles were then analyzed to determine the engagement model used in each paper (Feedback Model, Incentive and achievement model, and Progression Model). Findings included the trend of research in this field (technology applied to each research, on-line feature, study majors/subject) are displayed based on the time paper were published. The study result indicated that all previous research used at least one of the engagement models, with 12 articles using the three models. In terms of technology, it was found that the adoption of web-based technology has been increasing in recent years, including online features that have also increased, along with the study subjects who implemented game-based learning. In summary, game-based learning can be applied in a wide range of subjects and platforms with the support of its characteristic, making learning more flexible.
Integrating Financial Management and Gamification: A Systematic Literature Review and Future Research Agenda Prasetyo, Amrisandha Pranantya; Santoso, Harry Budi; Putra, Panca Oktavia Hadi
The Indonesian Journal of Computer Science Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i3.3244

Abstract

The implementation of gamification in PFM apps has the potential to motivate users to engage in positive financial behaviors. However, several research gaps corroborate the need to investigate gamification in the financial domain further. To address these gaps, this systematic literature review comprehensively examines current research on financial behavior and gamification. This review utilizes the Theory, Context, Characteristics, and Methodology (TCCM) framework to provide a holistic understanding of financial behavior and gamification-related behavioral intention. A total of 53 articles published between 2018 and 2022 were analyzed to assess the present research landscape and provide directions for future studies. This review makes three key contributions: (1) synthesizes current research on financial behavior and gamification-related behavioral intention, (2) presents integrated conceptual models that elucidate financial behavior and gamification-related behavioral intention, and (3) identifies research gaps and suggests avenues for future investigation.
Perancangan Antarmuka dan Fitur Training Management system (TMS): Studi Kasus Divisi Corporate University PT XYZ Iswara Maharani; Oktavia Hadi Putra, Panca
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4607

Abstract

This study addresses the fragmented learning systems at PT XYZ, where separate and manually managed platforms result in inefficient training documentation. With an annual learning volume of 156,018 training hours and a rise in mandays from 9.4 (2019) to 12.8 (2023), the inefficiencies significantly impact training management. The research aims to design the interface and features of a Training Management System (TMS) for PT XYZ using a Systematic Literature Review (SLR) and a user-centered design (UCD) approach to align with user needs. A mixed-methods approach combines qualitative and quantitative techniques, including interviews, pre-questionnaires, usability tests, feedback sessions, and Subject Matter Expert inputs. Evaluation results show an average score of 4.29 out of 5, reflecting user satisfaction with the system's functionality, efficiency, and reliability. Effective implementation of the TMS is expected to improve training quality, support human resource development, and help achieve strategic corporate objectives.
Data Protection Impact Assessment Framework in the Banking Sector in Indonesia to Implement Law of Personal Data Protection Dian Ismiati Anggraini; Panca Oktavia Hadi Putra
Jurnal Sistem Informasi Vol. 21 No. 1 (2025): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jsi.v21i1.1439

Abstract

Indonesia’s banking industry is evolving in personal data management due to technological advancements, which present both benefits and challenges. Influenced by global standards like the GDPR, Indonesia’s Law No. 27 of 2022 on Personal Data Protection incorporates these principles to enhance data protection. The Data Protection Impact Assessment (DPIA), a key risk mitigation tool mandated by the GDPR, is required for high-risk data processing under Indonesian law, though implementation regulation is still pending. This research develops and validates a DPIA framework tailored to the Indonesian banking sector, addressing components that can be considered to be the base framework of DPIA in Indonesia. Recommendations include adopting a comprehensive DPIA framework, staff training, instrument validation, integrating DPIAs into business processes, developing IT applications for DPIA, and continuous monitoring. This research offers practical solutions and contributes to the broader data protection literature.
Factors Influencing the Decline in Use of The Nebengers Application Christine Cecylia Munthe; Panca Oktavia Hadi Putra
Jurnal Sistem Informasi Vol. 21 No. 1 (2025): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jsi.v21i1.1437

Abstract

Nebengers is a popular ride-sharing application that helps many users find traveling companions and reduces the use of private vehicles in several regions in Indonesia. In 2022, there has been an increase in travel requests but a decrease in trip completion; in fact, only twenty-five percent of travel requests have been completed. This research aims to analyze the factors influencing the decline in trip completion in the Nebengers application based on the user's perspective. The identification process was carried out by conducting interviews with guided questions referring to the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Model and the Systematic Literature Review (SLR) results. Thematic analysis was used to identify factors discovered during the interviews. The results of the thematic analysis are four themes of factors that influence the use of the Nebengers application: Effort Expectancy, Facilitating Conditions, Hedonic Motivation, and Habit.
Evaluation of Open-ended Question’s Answers using Large Language Model (LLM): A Case Study of a Language Learning Center in University Faisal Wilmar; Panca Oktavia Hadi Putra
Jurnal Sistem Informasi Vol. 22 No. 1 (2026): Vol. 22 No. 1 (2026): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Massive open online courses (MOOCs) are a transformative tool in education. Their benefits are increasingly significant along with the development of artificial intelligence (AI) in the form of Large Language Models (LLMs). However, the use of LLMs in education raises several ethical issues, such as accuracy and fairness, especially when LLMs are used for assessment or evaluation. This is because of the risk of bias, inaccuracy, and inconsistency in the AI output. These risks can be reduced with the development of LLM capabilities and the use of prompt engineering techniques, namely, a way of communicating with LLM models. This study aims to evaluate the influence of factors affecting the accuracy of evaluation results from open-ended questions in an English MOOC at a university’s language learning center. The results of this evaluation are used to determine recommendations for the consistent and accurate use of LLMs in evaluating open-ended questions in English courses using the MOOC platform. This quantitative quasi-experimental research involved 580 participants divided into three proficiency groups who answered open-ended questions. Participants’ answers were evaluated by one human rater and three LLMs using three prompt engineering techniques to generate an evaluation result. The assessment results were analyzed using a three-way analysis of variance (ANOVA) to examine the factors influencing the LLM output. The mean absolute difference (MAE) between the human and LLM assessment results was used to assess the accuracy of LLM. The evaluation result was then calculated using the quadratic weighted kappa to generate inter-rater reliability to assess the raters’ consistency. The results showed that the participant group, LLM model used, and prompt engineering technique used influenced the assessment results. The ability level of the evaluated participants had the greatest impact on the results. A combination of LLM and prompt engineering technique, ChatGPT-4.1 with Chain-of-Thought, provided the best results, but it should not be used for high-stakes assessments. LLM can be used for initial assessment or as a complement to human assessment results without replacing actual human raters for high-stakes assessments.
Co-Authors Christine Cecylia Munthe Dian Ismiati Anggraini Faisal Wilmar Harry Budi Santoso Iswara Maharani Mhd. Adhitiya Okta Riyandi Mukti Budiarto Nuke Puji Lestari Santoso Prasetyo, Amrisandha Pranantya Qurotul Aini