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All Journal Jurnal Ilmu Ternak Indonesian Journal of Physics (IJP) BULETIN FISIKA
Aditya, Irfan Dwi
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Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Medicine & Pharmacology Physics Veterinary

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The Utilization and Optimization of Histogram of Oriented Gradients and Machine Learning in Face Recognition System Rachmat, Muhammad Ervandy; Aditya, Irfan Dwi; Muttaqien, Fahdzi
Indonesian Journal of Physics Vol 34 No 2 (2023): vol 34 no 2 2023
Publisher : Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itb.ijp.2023.34.2.4

Abstract

Computer science and technology development in recent years has experienced great developments. This time, some types of technology digitise almost everything related to human life, including facial recognition. In recent years, various methods for recognising human faces have developed. One of them is using the Histogram of Oriented Gradients (HOG). On this occasion, an image processing system will be designed to recognise human faces using Histograms of Oriented Gradients (HOG) and machine learning such as Convolutional Neural Networks (CNN) and Support Vector Machines (SVM). Detects the winking of the face, using computer-recognisable points in the eye area from 68 facial landmarks, so from these results, the distance between the upper and lower eyelids can be measured. If the distance (in pixels) is small enough, it can be interpreted as a wink. In addition, it is also limited by the distance of faces that can be detected to blink. In the end, if a recognised face blinks are detected, the time and date will be recorded. It will then open a solenoid lock using serial communication via Arduino Uno to become a security system. From 100 facial photos and 207 blink tests, 89.86% found that the computer could detect a "True Positive" wink. Besides, this facial recognition system's recommended tolerance parameter value is between 0.42 and 0.48.
Study of Nitrogen Nutrient Absorption and Forage Production in Kalopo Plants (Calopogonium mucunoides) Triputra, Kustiawan; Mansyur, Mansyur; Susilawati, Iin; Aditya, Irfan Dwi
Jurnal Ilmu Ternak Universitas Padjadjaran Vol 25, No 1 (2025): Volume 25 No. 1 Maret 2025
Publisher : Fakultas Peternakan, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jit.v25i1.53762

Abstract

AbstractThis research aims to evaluate differences in soil nitrogen content, nitrogen absorption by plants, and forage production of Calopogonium mucunoides plants grown on andosol and ultisol soils during a 90-day planting period. The research method used was experimental, with treatment factors in the soil type (andosol and ultisol). The parameters observed included the soil’s moisture, temperature, pH, nitrogen content, and the plant’s nitrogen content and forage production. The results showed that Andosol's average soil moisture value (53.61%) was higher than Ultisol (43.68%). The soil temperature of Ultisol (24.34°C) tends to be higher than Andosol (23.36°C). Andosol soil pH (5.04) exceeds Ultisol's (4.87). The soil nitrogen content in Andosol (4,838%) is higher than in Ultisol (4,058%). The nitrogen content in plant tissue in both soil types is relatively the same, namely (2.423%) for andosol soil and (2.523%) for ultisol soil. However, forage production on Andosol (42.65 g/pot fresh weight; 11.85 g/pot dry weight) was almost 2 times higher than Ultisol (21.75 g/pot fresh weight; 5.907 g/pot dry weight). Nitrogen uptake in andosol soil is 0.247 grams/pot, higher than in ultisol soil, 0.149 grams/pot. In conclusion, Andosol is more optimal for the growth of C. mongoides in forage production.
Design and Construction of a Portable and Real-Time Monitoring System Based on the Internet of Things (IoT) for CO2 Gas Leaks Putri, Novia Masni Dwi; Muid, Abdul; Aminah, Nina Siti; Aditya, Irfan Dwi
BULETIN FISIKA Vol. 27 No. 2 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i02.p01

Abstract

Carbon dioxide (CO₂) is the second most abundant contributor to the greenhouse effect after water vapor. Its atmospheric concentration has continued to rise over the past decade, correlating with the increase in global average temperature. Carbon Capture and Storage (CCS) is a technological approach designed to reduce CO₂ emissions by capturing CO₂ from industrial sources, transporting it to designated sites, and storing it securely. Continuous monitoring of CO₂ levels plays a critical role in CCS operations to ensure that stored CO₂ does not leak back into the atmosphere. This study presents a portable, real-time monitoring system for detecting CO₂ leakage using an MG-811 sensor integrated with an Internet of Things (IoT) platform. The system utilizes long-range communication networks for data transmission, enabling real-time visualization and analysis. In contrast to previous research, the proposed system not only displays concentration data but also includes an early warning feature and user-friendly visualization. It is powered by solar energy, allowing autonomous operation in remote areas.The results demonstrate that the sensor responds effectively to variations in gas concentration and environmental parameters. The system provides leakage vulnerability alerts using three categories: SAFE, ALERT, and DANGER. This approach enables faster identification of potential CO₂ leakage, supporting earlier and more effective mitigation actions.
Co-Authors Abdul Muid Aminah, Nina Siti Iin Susilawati Mansyur Mansyur Muttaqien, Fahdzi Putri, Novia Masni Dwi Rachmat, Muhammad Ervandy Triputra, Kustiawan