Journal of Engineering, Technology, and Applied Science (JETAS)

Developing a Sustainable Business Model for Electric Motorcycle Conversion in Indonesia Using SBMC and PROMETHEE

2025-08-31T11:15:27+00:00

The transportation sector accounts for approximately 37% of Indonesia’s final energy consumption, with 99.9% still relying on fossil fuels. This dependency increases energy subsidy burdens and contributes significantly to greenhouse gas emissions. In response, the Indonesian government has introduced policies to promote battery electric vehicles, including incentives for converting internal combustion engine (ICE) motorcycles to electric. This study aims to develop a sustainable business model for motorcycle electrification in Indonesia using the Sustainable Business Model Canvas (SBMC) framework. To prioritize key business components, the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) method was applied. A mixed-methods approach was adopted, involving semi-structured interviews with 14 stakeholders and multi-criteria decision analysis. The findings highlight legality assurance, urban user targeting, and strategic partnerships as the most critical elements. The resulting SBMC provides actionable insights for policymakers and industry actors to accelerate electric motorcycle adoption and contribute to Indonesia’s Net Zero Emission goals through more energy-efficient and low-carbon transport solutions.

Comparative Analysis of Chatbot Development Methods on Flexibility and Control

2025-08-31T23:16:38+00:00

Chatbots are dialogue systems driven by Natural Language Processing (NLP) and Artificial Intelligence (AI), extensively utilized in areas like customer support, education, and healthcare. Nonetheless, the variety in approaches to chatbot development, ranging from rule-based systems to generative AI, creates difficulties in harmonizing design decisions with user requirements and technical limitations. This research seeks to examine and contrast the primary approaches employed in chatbot creation: rule-based, retrieval-based, and generative-based systems. Employing a descriptive-qualitative methodology, the study is carried out in the first quarter of 2025 and utilizes scholarly literature, technical documents, and case studies of Mitsuku, Google Assistant, and ChatGPT, concentrating on applications in Indonesia and Malaysia. A comparative analysis assesses every method based on development complexity, accuracy, flexibility, user experience, interpretability, cost, and ethical risks. The results indicate that rule-based systems provide low expenses and significant transparency, but they fall short in scalability and flexibility. Retrieval-based systems excel in accuracy for domain-specific queries but struggle with new interactions. Chatbots based on generative models provide the most natural and contextually aware interactions, but they require significant resources and present issues related to interpretability and ethics. The research suggests that hybrid models integrating control and adaptability could be the most efficient approach. Further studies are required to improve transparency in generative systems, reduce bias, and create adaptive hybrid architectures appropriate for Southeast Asian use.

Evaluating the AGTS as a Sustainable Urban Transit Innovation in Metro Manila

2025-08-31T23:14:33+00:00

Metro Manila faces chronic traffic congestion and growing environmental concerns due to rapid urbanization and rising vehicle numbers. In response, the Department of Science and Technology and the University of the Philippines developed the Automated Guideway Transit System (AGTS) as a compact, automated, and eco-friendly public transport alternative. This study evaluates AGTS's effectiveness and efficiency as a sustainable urban mobility solution, focusing on pilot sites in UP Diliman and Bicutan. Using a mixed-methods approach, data were collected through stakeholder interviews, technical assessments, and field observations. Findings indicate strong system reliability, reduced energy consumption (up to 40% less than conventional LRT), and lower CO₂ emissions. Despite high public support, implementation challenges persist, particularly in funding, land acquisition, and intermodal integration. The study highlights AGTS's replication potential in mid-sized cities like Cebu and Davao, with considerations for scalability in less developed areas. This research contributes to the discourse on sustainable transport innovation in developing urban contexts.

Arduino-Based Heart Rate Monitoring System Using Mamdani Fuzzy Logic

2025-09-09T14:10:43+00:00

Heart disease remains one of the leading causes of death worldwide, highlighting the need for an early and accurate monitoring system. This research aims to design an Arduino-based heart rate monitoring system that integrates the MAX30102 pulse sensor and the MLX90614 body temperature sensor. Using the Mamdani fuzzy logic method, the system classifies a user's health condition into three categories: healthy, alert, and at risk, based on inputs from heart rate, body temperature, and age. A total of 27 fuzzy rules are applied, and the results are displayed in real-time via a laptop monitor. Compared to conventional heart monitoring methods, this system offers a lower-cost and portable solution suitable for household use. Preliminary tests conducted on six samples yielded an average error rate of 16.3% (beats per minute, bpm) for the pulse sensor, which falls into the medium error category, and 3.95% (°C) for the temperature sensor, which falls into the low error category. The system was evaluated by comparing sensor readings with those of standard commercial devices, indicating acceptable accuracy for a prototype stage. While the system functions well, its performance could be further improved with enhanced sensor accuracy, wireless data transmission, and integration with mobile applications. Future developments could also focus on increasing the sample size and benchmarking against clinical-grade devices to strengthen reliability and usability. The proposed system is unique in combining heart rate, body temperature, and age data through fuzzy logic to provide real-time classification of health status in a low-cost and portable design, making it a promising tool for household-based preventive heart health monitoring.