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All Journal Jurnal Paedagogy Insyst : Journal of Intelligent System and Computation
Dewi, Grace Levina
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Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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A Hybrid Machine Learning and Deep Learning Approach for In-Game Assistance Dianaris, Audrey Ayu; Vincent; Setiono, Kevin; Setiawan, Mikhael; Pranoto, Yuliana Melita; Dewi, Grace Levina
Intelligent System and Computation Vol 7 No 1 (2025): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v7i1.430

Abstract

The rapid development of artificial intelligence (AI) has opened new possibilities for enhancing user interaction within video games. This study presents the design and implementation of a button-based assistant system for the simulation game Story of Seasons: Friends of Mineral Town, aimed at simplifying repetitive player tasks and improving the overall gameplay experience. The proposed system leverages a hybrid approach that combines Machine Learning and Deep Learning techniques, specifically Optical Character Recognition (OCR) with Tesseract, object detection using a custom-trained YOLOv7 model, the A* pathfinding algorithm for navigation, and automated input control through scripting. The assistant is capable of reading in-game time, weather, and events directly from screen captures, recognizing non-player characters (NPCs), and automatically directing the player’s character to desired locations or NPCs based on contextual data such as day, time, and weather conditions. A database-driven module stores key information such as NPC schedules, favorite gifts, and daily events to enable informed decision-making and interaction automation. Comprehensive testing was conducted, including comparisons of pathfinding algorithms, model accuracy assessments, and user experience evaluations involving volunteers. Results showed high detection accuracy with YOLOv7 and positive user feedback on the assistant's interface and usability. Users reported a more streamlined and enjoyable gaming experience, especially in managing daily tasks and character interactions. This research demonstrates how a hybrid AI-based approach can be effectively applied to traditional video games, offering a foundation for future development in intelligent game assistance systems. The proposed methodology not only improves convenience but also provides insights into the practical integration of AI in user-centric game design.
Thesis Defense Scheduling Optimization Using Harris Hawk Optimization Setiono, Kevin; Setiawan, Mikhael; Dewi, Grace Levina; Dhaniswara, Erwin
Intelligent System and Computation Vol 6 No 2 (2024): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v6i2.361

Abstract

This research discusses how the Harris Hawk Optimization (HHO) algorithm handles scheduling problems. The scheduling of thesis defenses at the Institut Sains dan Teknologi Terpadu Surabaya (ISTTS) is a complex issue because it involves the availability of lecturers, teaching/exam schedules, lecturer preferences, and limited room and time availability. The scheduling constraints in this research are divided into two categories: Hard Constraints and Soft Constraints. Hard constraints must not be violated, including each lecturer's unique availability, conflicts, and existing exam or teaching schedules. Soft constraints, on the other hand, include preferences for specific days or rooms for the defense. The complexity of scheduling due to these two types of constraints leads to longer scheduling times and an increased likelihood of human error. To automate and optimize this process, the author employs the HHO algorithm. HHO is inspired by the behavior of the Harris Hawk, known for its intelligence and ability to coordinate while hunting. The results of the HHO algorithm are translated into a slot meter, which helps to map the solution to available time slots. The HHO algorithm can generate schedules that comply with 90% of the hard constraints at ISTTS. Evolutionary algorithms typically have high complexity and computational time; in this case, the researcher experimented with multiprocessing. Multiprocessing improved the computational time by up to 39%.
Development and Validation of "Merdeka": An Augmented Reality-Based Board Game for Indonesian History Learning Dewi, Grace Levina; Setiawan, Mikhael; Prayogi, Alan David
Jurnal Paedagogy Vol. 13 No. 1 (2026): January
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jp.v13i1.18285

Abstract

This study aims to develop and evaluate the feasibility of an educational board game, Merdeka, integrated with Augmented Reality (AR) technology as a history learning medium for junior high school students aged 13–15 years. The study employed a development research method using the Game Development Life Cycle (GDLC) model, which consists of six stages: initiation, pre-production, production, alpha testing, beta testing, and release. The feasibility of the product was assessed using a three-pronged evaluation approach: validation by material and media experts, black-box functionality testing of the AR application, and a limited beta trial involving 24 junior high school students. Data were analyzed using descriptive quantitative techniques based on Likert-scale scoring. The expert validation results indicated a “highly feasible” category, with average feasibility scores of 89.44% from material experts and 85.71% from media experts. The user trial results also demonstrated a very high level of acceptance, achieving a feasibility score of 84.8%. These findings indicate that the enjoyable gameplay experience and the integration of AR technology constitute the primary strengths of the product. In conclusion, the Merdeka educational board game is a valid, functional, and well-received learning medium and is therefore suitable for implementation and broader dissemination.
Co-Authors Alan David Prayogi Audrey Ayu Dianaris Dhaniswara, Erwin Mikhael Setiawan Setiono, Kevin Vincent Yuliana Melita Pranoto