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All Journal Community Empowerment OKTAL : Jurnal Ilmu Komputer dan Sains
Ahmad Rifa`i
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Arts Humanities Astronomy Chemistry Computer Science & IT Education Electrical & Electronics Engineering Public Health Social Sciences

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Study of community-based waste management strategy determination in Magelang City Ni Nyoman Nepi Marleni; Nurul Alvia Istiqomah; Bambang Agus Kironoto; Bambang Suhendro; Akhmad Aminullah; Danang Parikesit; Ahmad Rifa`i
Community Empowerment Vol 7 No 5 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (265.259 KB) | DOI: 10.31603/ce.6601

Abstract

The city of Magelang is having trouble providing Final Disposal Sites (TPA), as the Banyuurip TPA's storage capacity has reached its limit and expansion is no longer possible. The only approach to reduce garbage production and residue transferred to landfills is to engage the community and all other stakeholders in waste management. This program intends to develop a waste management strategy in Magelang City starting with the smallest units, namely RT and RW. According to the findings, waste management solutions for the community of RW 02, Magelang Village, Central Magelang District may be classified as socialization strategies, work plans or regulations, resource procurement, cooperation, and empowerment. Furthermore, the study's findings reveal that an effective strategy must include multiple activities that operate concurrently, progressively, and sustainably, as well as the participation of various parties (community, local government, and universities) in assuring effective management implementation.
Perancangan Sistem Sederhana Deteksi Helm Sepeda Motor dengan Metode Convolutional Neural Network Dan Algoritma YOLO v3 Ibnu Hajar; Ahmad Rifa`i; Ilham Fauzi Alam; Andang Ramadhan; Perani Rosyani
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 07 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Traffic accidents are one of the most common causes of death in the world, and helmet use has been effective proved in reducing the risk of head injuries for motorcyclists. Therefore, it is crucial to ensure that motorcyclists always wear helmets while riding. One method to detect helmet use is by utilizing object recognition technology based on Convolutional Neural Networks (CNN). This study focus on design and implement a simple helmet detection system using CNN methods and the YOLO v3 model for real-time detection. The system is expected to accurately detect helmet use by riders. In this research, the YOLO v3 model is trained using the COCO dataset, which includes various images with diverse contexts. The results of this implementation show that the system can detect helmet use effectively under various lighting conditions and environments. This demonstrates the potential use of a helmet detection system based on CNN and YOLO in enhancing riding safety.
Perancangan Sistem Pakar Diagnosis Tingkat Stres Pada Siswa Korban Bullying Menggunakan Metode Forward Chaining (Studi Kasus: SMK Triguna Utama) Ahmad Rifa`i; Lely Panca Andriyanto
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 4 No 09 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Advances in technology have encouraged the development of web-based expert systems to help diagnose stress levels in students who are victims of bullying. This study aims to develop and build an expert system that can overcome the difficulties in manually identifying students' stress levels at SMK Triguna Utama. Manual processes so far often face problems such as inconsistent results and lack of clear data. The system is designed using the forward chaining method, which works by analyzing stress symptoms based on the data entered. Data for the system was collected through questionnaires filled out by students. The findings of this research are expected to assist schools understand students' conditions better, provide accurate information, and help make decisions to provide assistance to students. This system is expected to support efforts to improve students' mental health at SMK Triguna Utama and other schools.
Co-Authors Aminullah, Akhmad Andang Ramadhan Bambang Agus Kironoto Bambang Suhendro Danang Parikesit Ibnu Hajar Ilham Fauzi Alam Lely Panca Andriyanto Ni Nyoman Nepi Marleni Nurul Alvia Istiqomah Perani Rosyani