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All Journal International Journal Software Engineering and Computer Science (IJSECS) Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Al Faruq, Abdullah
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Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science

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Pemantauan dan Pengelolaan Sampah di Area Wisata Sukamakmur Jonggol Kabupaten Bogor Berbasis Web Sugiyono; Arham; Al Faruq, Abdullah; Aziz, Naufal
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 2 (2025): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i2.1370

Abstract

Waste monitoring and management in tourist areas based on a website is an innovative solution to maintain cleanliness and the beauty of tourism environments. This system is designed to assist tourism managers in monitoring trash bin conditions in real-time and efficiently managing waste handling data. Currently, waste management in many tourist areas is still performed manually, making it less effective in maintaining optimal cleanliness. Therefore, the author developed a waste monitoring and management system based on a website using the Waterfall model. This system was built using the PHP programming language, the Laravel framework, and MySQL as the database. The system consists of two main dashboards: the admin dashboard and the staff dashboard. The admin dashboard features include managing trash bin data, scheduling waste collection, and generating waste management reports. Meanwhile, the staff dashboard is equipped with features for reporting trash bin conditions and scheduling waste collection. This system can be accessed via computer or mobile devices, providing flexible and efficient management. With this system, waste management in tourist areas is expected to become more structured, helping to maintain environmental cleanliness and enhance visitor comfort.
Classification Optimization of Aedes albopictus and Culex quinquefasciatus Mosquito Larvae Using Vision Transformer Method Al Faruq, Abdullah; Mulyana, Dadang Iskandar; Adrianto, Sopan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5120

Abstract

Mosquito-transmitted diseases like Dengue Hemorrhagic Fever and Filariasis pose serious health threats throughout tropical regions, particularly in Indonesia. Quick and accurate identification of mosquito larvae plays a crucial role in disease prevention, especially for Aedes albopictus and Culex quinquefasciatus species that act as main disease carriers. Manual identification methods using microscopes or visual guides often struggle with time constraints, accuracy issues, and dependence on trained specialists. Our research focuses on improving the classification of Aedes albopictus and Culex quinquefasciatus mosquito larvae using Vision Transformer (ViT) technology, a deep learning method that has shown strong results in image recognition tasks. We applied the Vision Transformer model to classify mosquito larvae from microscopic field images. The study also tested how different factors impact model performance, such as image clarity, lighting conditions, and image resolution. Our findings show that using Vision Transformer in classification systems produced excellent results, achieving 98.00% accuracy in recall, precision, and F1-score measurements. The research reveals that Vision Transformer methods deliver better accuracy than traditional approaches like Convolutional Neural Networks and can be adapted into working systems for technology and healthcare sectors.
Co-Authors Arham Aziz, Naufal Dadang Iskandar Mulyana` SOPAN ADRIANTO Sugiyono