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All Journal Jurnal Ekonomi Manajemen Bisnis dan Akuntansi Journal Innovation in Information and Computer Technology
Md. Ruhul Amin
Department of Public Administration, Comilla University, Cumilla, Bangladesh
Economics, Econometrics & Finance

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Municipal Waste Management in Kushtia District: A Comparative Case Study of Two Municipalities Md. Ruhul Amin
Jurnal Ekonomi Manajemen Bisnis dan Akuntansi Vol. 3 No. 1 (2026): (January) Jurnal Ekonomi Manajemen Bisnis dan Akuntansi
Publisher : PT. Altaf Publishing Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70895/jemba.v3i1.87

Abstract

Municipal waste management is a serious problem in developing countries due to rapid urban growth and increasing population. This study compares waste management practices in two municipalities in the Kushtia District of Bangladesh: Kushtia Municipality and Kumarkhali Municipality. The aim is to evaluate the effectiveness and sustainability of their waste management systems. Data were collected through field observations, interviews with municipal officials, and secondary data analysis. The results show clear differences between the two municipalities. Kushtia Municipality has better financial resources and infrastructure, leading to more efficient waste collection, separation, and disposal. In contrast, Kumarkhali Municipality faces major challenges such as limited resources, poor facilities, and low public awareness. These differences are mainly caused by unequal resource distribution, weak community participation, and gaps in policy implementation. The study emphasizes the need for an integrated waste management approach that involves local communities and strengthens institutional capacity. Key recommendations include improving waste separation at the source, using appropriate waste treatment technologies, increasing public awareness, and strengthening monitoring systems. This research provides useful insights for improving municipal waste management and supports efforts to enhance environmental sustainability and public health in urban areas of Bangladesh.
Design of Augmented Reality Learning Media with AI Chatbot Support for Computer Network Learning Muhammad Ridho Ardiansyah; Andri Saputra; Md. Ruhul Amin
Journal Innovation in Information and Computer Technology Vol. 3 No. 2 (2026): (May) Journal Innovation in Information and Computer Technology (JICTECH)
Publisher : PT. Altaf Publishing Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70895/jictech.v3i2.123

Abstract

Computer network learning often involves abstract concepts, invisible data flows, and physical devices that are not always available in the classroom. This condition can make it difficult for beginner students to understand network devices, topology structures, and basic communication processes. This study aims to design augmented reality learning media with AI chatbot support for computer network learning. The research used a research and development approach adapted from the Multimedia Development Life Cycle (MDLC), consisting of concept, design, material collecting, assembly, testing, and distribution stages. The developed media integrates AR visualization, learning materials, and chatbot-based assistance in one learning environment. The AR feature presents three-dimensional models of network devices and topology structures, while the AI chatbot provides simple explanations and guidance related to computer network concepts. Functional testing was conducted to ensure that the main features operated according to the expected results, including the main menu, learning material page, AR object display, topology visualization, AI chatbot interaction, instruction menu, and navigation buttons. User response evaluation was also conducted using a Likert-scale questionnaire involving 20 students. The results showed that all main features worked properly, and the user response evaluation obtained an average score of 85.2%, categorized as Very Good. These findings indicate that the developed media is feasible as a supporting tool for computer network learning. The integration of AR visualization and AI chatbot support can help students learn more independently, understand network concepts more clearly, and receive immediate learning assistance. Future development may focus on improving AR object optimization, expanding chatbot knowledge, and testing the media’s effectiveness on students’ learning outcomes.
Co-Authors Andri Saputra