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All Journal Journal of Artificial Intelligence and Technology Information INTECH - Informatika Dan Teknologi
Christian A. J. Soewoeh
Universitas Sam Ratulangi
Computer Science & IT Engineering

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Performance Analysis of ECS Architecture in 2D Mobile Game Development: Ocean Hero Raynaldi Irfansya Regar; Benny Pinontoan; Christian A. J. Soewoeh
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 4 No. 2 (2026): Volume 4 Number 2 June 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v4i2.267

Abstract

Mobile game development frequently encounters computational performance bottlenecks when a system must render and update the logic of many objects simultaneously in each frame. Conventional Object-Oriented Programming (OOP) architecture produces high memory overhead and elevated cache miss rates because game objects are allocated in scattered, non-contiguous memory locations. This research aims to design, implement, and analyze the performance of an Entity Component System (ECS) architecture in a 2D Android educational arcade game titled Ocean Hero. The development process followed the Game Development Life Cycle (GDLC). ECS separates identity, data, and behavior into entities, components, and systems, allowing game logic to process homogeneous component data sequentially through Unity DOTS. Evaluation was conducted on a Samsung Galaxy A15 4G by comparing ECS and OOP implementations through white-box functional verification and stress testing across six entity workloads from 500 to 3,000 entities, each observed over a 20-second tracking period. The ECS implementation maintained a stable 30 FPS and 33.3 ms frame time across all tested entity levels. In contrast, the OOP implementation degraded to 11 FPS and 90.73 ms frame time at 3,000 entities. Based on the relative performance improvement formula, ECS achieved approximately 172.7% higher runtime performance than OOP at the highest workload. These results confirm that ECS is an effective architectural solution for improving scalability and computational efficiency in real-time 2D mobile games with large entity counts.
Pengembangan Chatbot Perpustakaan Berbasis Retrieval-Augmented Generation (RAG) pada Telegram Elrica Meriana Isabel Tutu; Benny Pinontoan; Edwin Tenda; Christian A. J. Soewoeh; Mahardika I. Takaendengan; Stephano C. W. Ngangi
INTECH Vol. 7 No. 1 (2026): INTECH (Informatika Dan Teknologi)
Publisher : Informatics Study Program, Faculty of Engineering and Computers, Baturaja University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54895/intech.v7i1.3435

Abstract

The library of Sam Ratulangi University (UNSRAT) has a large collection of books and academic resources; however, users still experience difficulties in obtaining book availability information quickly and efficiently. This study aims to develop and evaluate a Telegram-based chatbot using a Retrieval-Augmented Generation (RAG) approach integrated with the GPT-4.1-mini Large Language Model (LLM). The system was developed using the Waterfall method and implemented through the n8n workflow automation platform by integrating Telegram Bot, MySQL, and Pinecone as a vector database. The chatbot applies a Text-to-SQL RAG mechanism, where user questions are converted into embeddings, matched with database context, and transformed into SQL queries limited to SELECT operations. System evaluation was conducted using Black Box Testing, User Acceptance Testing (UAT), and RAG evaluation metrics consisting of Answer Relevancy and Faithfulness. The results show that the chatbot successfully performs its main functions and achieved a UAT score of 82.3%, while Answer Relevancy and Faithfulness obtained scores of 100%. The developed system is capable of providing relevant and interactive information regarding library collections.
Pengembangan Chatbot Perpustakaan Berbasis Retrieval-Augmented Generation (RAG) pada Telegram Elrica Meriana Isabel Tutu; Benny Pinontoan; Edwin Tenda; Christian A. J. Soewoeh; Mahardika I. Takaendengan; Stephano C. W. Ngangi
INTECH Vol. 7 No. 1 (2026): INTECH (Informatika Dan Teknologi)
Publisher : Informatics Study Program, Faculty of Engineering and Computers, Baturaja University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54895/intech.v7i1.3435

Abstract

The library of Sam Ratulangi University (UNSRAT) has a large collection of books and academic resources; however, users still experience difficulties in obtaining book availability information quickly and efficiently. This study aims to develop and evaluate a Telegram-based chatbot using a Retrieval-Augmented Generation (RAG) approach integrated with the GPT-4.1-mini Large Language Model (LLM). The system was developed using the Waterfall method and implemented through the n8n workflow automation platform by integrating Telegram Bot, MySQL, and Pinecone as a vector database. The chatbot applies a Text-to-SQL RAG mechanism, where user questions are converted into embeddings, matched with database context, and transformed into SQL queries limited to SELECT operations. System evaluation was conducted using Black Box Testing, User Acceptance Testing (UAT), and RAG evaluation metrics consisting of Answer Relevancy and Faithfulness. The results show that the chatbot successfully performs its main functions and achieved a UAT score of 82.3%, while Answer Relevancy and Faithfulness obtained scores of 100%. The developed system is capable of providing relevant and interactive information regarding library collections.
Co-Authors Benny Pinontoan Elrica Meriana Isabel Tutu Mahardika I. Takaendengan Raynaldi Irfansya Regar Stephano C. W. Ngangi Tenda, Edwin