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All Journal PROtek : Jurnal Ilmiah Teknik Elektro JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Ewi Ismaredah
Fakultas Sains dan Teknologi Universitas Islam Negeri (UIN) Sultan Syarif Kasim Riau
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy

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Electronic Networking System With Laser Light To Detect And Repel Sparrow Pests Nuracantha, Luqyana Aufa; Kharisma, Oktaf Brilian; Simaremare, Harris; Ismaredah, Ewi
PROtek : Jurnal Ilmiah Teknik Elektro Vol 12, No 2 (2025): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v12i2.9204

Abstract

Rice is one of the staple foods of the Indonesian population and has an important role in the formation of the Gross Domestic Product (GDP). However, this role has not been able to run well because many pests attack and cause crop failure, one of which is sparrow pests. For this reason, a study was conducted using ultrasonic sound to disturb the pests so that they do not land and leave the rice plant. The ultrasonic sound is emitted when the bird approaches and breaks the electronic net of the laser beam spread over the rice plant. This prototype was built using the NodeMCU ESP32 microcontroller as the controller and system. And telegram is used as a supporting application to give on/off commands and battery percentage detectors to facilitate use. According to the the research, the prototype functions properly and the disturbed by ultrasonic sound with frequencies ranging from 0 - 22,000 Hz and sound pressure levels between 31.6 - 93.2 decibels.
Deteksi Kode Etik Berpakaian pada Area Kampus Menggunakan YoloV8 Firdaus, Agung Ridhatullah; Kharisma, Oktaf Brillian; Ismaredah, Ewi; Abdillah, Abdillah
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4741

Abstract

In the current digital era, the development of computer vision technology has played a crucial role in various fields, including security and surveillance. This study proposes the application of the YOLOv8 (You Only Look Once version 8) object detection model to identify violations of clothing etiquette in the UIN Suska environment. The proposed approach involves collecting a dataset of 5195 accurately labeled images of clothing and training it using the YOLOv8 architecture, enabling real-time object detection at high speed. The research results indicate that the use of YOLOv8 can recognize and differentiate clothing that adheres to the dress code with good accuracy in the campus context, achieving an mAP of 0.819 at epoch 100 and an F1-Score of 0.79 with a dataset split of 87% training, 8% validation, and 5% testing. By employing appropriate evaluation metrics such as recall, precision, and F1-score, the model's performance can be comprehensively measured to produce optimal results. This research provides a crucial foundation for the development of the YOLOv8 object detection system in maintaining dress code compliance in the campus environment. The study includes the implementation of YOLOv8 on a clothing dataset that reflects the variations commonly found at UIN Suska. Performance evaluation is conducted by comparing detection results with labels provided by humans as ground truth. The use of this model is expected to assist authorities and security staff at UIN Suska in identifying clothing etiquette violations effectively, strengthening supervision, and supporting the creation of a comfortable campus environment in line with institutional values
Co-Authors Abdillah Abdillah Firdaus, Agung Ridhatullah Kharisma, Oktaf Brilian Kharisma, Oktaf Brillian Nuracantha, Luqyana Aufa Simaremare, Harris Simaremare