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AGILE DEVELOPMENT OF A PROJECT BASED LEARNING MANAGEMENT APPLICATION: A SCRUM DRIVEN STRATEGY TO ENHANCE EDUCATIONAL OUTCOMES Reisa Permatasari; Bonda Sisephaputra
Jurnal Sistem Informasi dan Sains Teknologi Vol 7, No 2 (2025): Jurnal Sistem Informasi dan Sains Teknologi
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/sistek.v7i2.2401

Abstract

Programming education at the Faculty of Engineering, Surabaya State University, faces challenges including low student engagement, ineffective teaching methods, and difficulties in monitoring progress. This study proposes the adoption of the Scrum methodology to develop a Project-Based Learning Management Application (PBLMA) tailored for programming courses. The Scrum framework, with its iterative sprints and emphasis on collaboration, facilitates the development of a flexible, user-centered application. By integrating sprint retrospectives, the development process ensures continuous improvement, aligning the PBLMA with the dynamic needs of educators and students. Results demonstrate that Scrum enables efficient development, with iterative cycles allowing for rapid adaptation to feedback. The application enhances student engagement and simplifies progress tracking, addressing key educational challenges. This study highlights Scrum’s potential as a robust framework for educational software development, offering insights for future implementations in academic settings
Design And Development Of An N8N-Based Ai Chatbot System Integrated With Whatsapp As An Information Service At Maxy Academy Chiboy Cristian Sibarani; Bonda Sisephaputra
Jurnal Ilmu Ekonomi, Pendidikan dan Teknik Vol. 3 No. 6 (2026): IDENTIK - November
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/identik.v3i6.2025

Abstract

Maxy Academy experiences operational inefficiency due to the high volume of customer inquiries on WhatsApp being handled manually. This study aims to design and develop an automated information service solution using an n8n-based AI Chatbot integrated with WhatsApp. Utilizing a Research and Development (R&D) approach with a Rapid Application Development (RAD) model, the system architecture incorporates the n8n orchestrator, WhatsApp HTTP API (WAHA), Large Language Model (LLM) agents, and a PERN Stack-based operational dashboard. The developed system successfully operates 24/7, proactively extracts customer data, and facilitates a silent handover mechanism for human agent intervention. Functional evaluation using Black Box Testing demonstrated a 100% validity rate across all test scenarios, confirming the software’s functional reliability without any defects. The R&D process successfully produced a stable and responsive automated information service that effectively classifies message queues.