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All Journal Informatik : Jurnal Ilmu Komputer MULTINETICS Journal of Artificial Intelligence and Digital Business Journal of Informatics, Electrical and Electronics Engineering Journal Of Artificial Intelligence And Software Engineering
Yudistira, Bagus Gede Krishna
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Journal : Journal Of Artificial Intelligence And Software Engineering

 1 
Smart Fisheries: Real-Time Water Quality Management and Automated Feeding System Design for Tilapia Farming using ESP32 Micro Controller Yudistira, Bagus Gede Krishna; Hapsari, Cindy; Adnyana, Gede Defry Widhi; Nath, Wiswa; Putra, I Putu Romyadhy Maha
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7288

Abstract

The fisheries sector in Jinengdalem Village, Buleleng, Bali holds considerable potential but continues to face challenges related to operational efficiency and unstable production outcomes. This study proposes an innovative solution through Smart Fisheries: The AI-Powered IoT in Smart Fisheries, an intelligent aquaculture system powered by Artificial Intelligence (AI) and the Internet of Things (IoT). The system is designed to perform real-time monitoring of water parameters, automate feeding processes, and analyze fish growth in order to enhance aquaculture productivity and sustainability. The research methodology follows a Research and Development (RD) framework, utilizing the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). Preliminary results indicate that the system provides accurate environmental data and supports data-driven decision-making in fishery management. This project is expected to serve as a replicable model for implementing digital aquaculture technologies in similar regions.
Implementation of Honey Encryption to Improve Resilience against Brute Force Attacks in Cloud-based Microservices Communication Purba, Gabriel Nathanael; Yudistira, Bagus Gede Krishna; Aryanto, Kadek Yota Ernanda
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7211

Abstract

Arsitektur microservices berbasis cloud meningkatkan skalabilitas dan fleksibilitas sistem namun memperbesar risiko keamanan komunikasi antar layanan. Penelitian ini menerapkan Honey Encryption pada API Gateway di infrastruktur Amazon EC2, mengombinasikan Distribution Transforming Encoder dengan AES-CBC 256-bit untuk menjaga kerahasiaan dan integritas data. Hasil validasi menunjukkan bahwa dekripsi dengan kunci benar memulihkan data asli, sedangkan kunci salah menghasilkan decoy message yang plausible dan bervariasi per field, secara efektif menghambat upaya brute force. Evaluasi performa menegaskan bahwa waktu proses enkripsi dan dekripsi berbanding lurus dengan beban data namun tetap berada dalam batas latensi yang dapat diterima. Simulasi serangan memperlihatkan keunggulan decoy message dalam menyamarkan pesan asli, meningkatkan keamanan komunikasi data antar microservices.
Overcome Limited Data Challenge in Time Series Forecasting with Power Law Algorithm for Attribution Churn Value Hapsari, Cindy; Yudistira, Bagus Gede Krishna
Journal of Artificial Intelligence and Software Engineering Vol 6, No 1 (2026): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i1.8712

Abstract

Limited historical data is a major challenge in churn forecasting. This study shows that the Power Law Algorithm can model churn-related value patterns reliably even with minimal data, making it a promising approach for early churn analysis when historical data is scarce.
Co-Authors Adnyana, Gede Defry Widhi AMBARA, I KOMANG WAHYU AMBARA PUTRA Ananda, Ngurah Gede Prema Satya Gede Arna Jude Saskara Hapsari, Cindy Kadek Yota Ernanda Aryanto Nath, Wiswa Pradipta, Ketut Saka Purba, Darma Putra Purba, Gabriel Nathanael Putra, I Putu Romyadhy Maha