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All Journal BIOTROPIA - The Southeast Asian Journal of Tropical Biology Teknika: Jurnal Sains dan Teknologi Jurnal Pendidikan Biologi Indonesia ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Sistemasi: Jurnal Sistem Informasi Jurnal Teknika Biosaintifika: Journal of Biology & Biology Education Jurnal Listrik, Instrumentasi, dan Elektronika Terapan Medika Trada Makara Journal of Technology Enigma in Education
Irma Saraswati
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Veterinary Other

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Classification of Beef, Goat, and Pork using GLCM Texture-Based Backpropagation Neural Network Saraswati, Irma; Fahrizal, Rian; Fauzan, Anugrah Nuur; Yudono, Muchtar Ali Setyo
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i6.4715

Abstract

Identifying different types of meat is crucial for preventing fraudulent activities and improving food safety. This research aims to create a classification system for various meat types (beef, goat, and pork) using the Gray Level Co-occurrence Matrix (GLCM) for extracting texture features, followed by classification through a Backpropagation Neural Network (BPNN). The methodology utilizes 60 images of beef, goat, and pork, achieving a remarkable accuracy of 100% in the training phase, which highlights the model's capability to effectively recognize patterns. However, when tested with new data, the system exhibits a sensitivity of 90% and a specificity of 95%, with some misclassifications occurring between goat and beef due to their similar textures. The findings of this study suggest that GLCM is an effective tool for deriving relevant statistical parameters necessary for classification. This research makes a significant contribution to developing a meat identification system that safeguards consumers and promotes awareness of food safety issues. The results are anticipated to provide a solid foundation for advancing meat type recognition and practical applications in the marketplace, ultimately boosting public trust in the meat products they purchase.
Perancangan Sistem Pemantauan Suhu, Kelembaban, Asap, Kebakaran, Kecepatan Angin dan Arah Angin Berbasis SMS di Lahan Pertanian UNTIRTA Saraswati, Irma; Alimuddin, Alimuddin; Irwan, Sobriansyah; Yudono, Muchtar Ali Setyo
MEDIKA TRADA : Jurnal Teknik Elektomedik Polbitrada Vol 6 No 2 (2025): MEDIKA TRADA: Jurnal Teknik Elektromedik Polbitrada Vol 6 No 2 (2025)
Publisher : LPPM POLBITRADA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59485/jtemp.v6i2.159

Abstract

Farm fires are a major cause of agricultural loss, leading to the destruction of millions of hectares of farmland. In Indonesia alone, the financial losses due to farm fires were estimated at 221 trillion rupiah in 2015. This study proposes the development of an early fire detection and environmental monitoring system that integrates MQ-7 and photodiode sensors for smoke and fire detection, along with additional sensors for monitoring temperature, humidity, wind speed, and wind direction. The system utilizes Short Message Service (SMS) for communication, which was selected due to its low cost, extensive coverage, and ability to facilitate rapid responses during emergencies. Sensor testing revealed that the temperature and humidity sensors (DHT11) exhibited a temperature deviation of 0.37°C and a humidity error of 2 Percent. The photodiode sensor successfully detected fire at distances of up to 150 cm, especially at night, under low light intensity conditions (0-10 Lux). The GSM communication module showed an average response time of 2 seconds, with a deviation range of 1 to 4 seconds between the sending and receiving of SMS messages. The system demonstrated its effectiveness in detecting fire and monitoring environmental parameters, providing real-time alerts every 10 minutes via SMS. This system offers a reliable, cost-effective solution for early fire detection and continuous environmental monitoring, enabling timely intervention to mitigate farm fire risks.
ETHNOBOTANICAL STUDY OF DIGESTIVE SYSTEMS DISORDERS IN BADUY ETHNIC, INDONESIA Khastini, Rida Oktorida; Wahyuni, Indria; Saraswati, Irma
BIOTROPIA Vol. 28 No. 1 (2021): BIOTROPIA Vol. 28 No. 1 April 2021
Publisher : SEAMEO BIOTROP

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (585.317 KB) | DOI: 10.11598/btb.0.0.0.1055

Abstract

Digestive disorders rank among the most common problems faced in Indonesia, especially for the Baduy people in Banten Province. Although the Baduy live in water-rich areas, their lack of sanitation facilities and unawareness of methods of disease prevention have prompted high morbidity and mortality rates in their communities, largely due to digestive system disorders that they continue to treat with medicinal plants. This survey was undertaken to document Baduy indigenous medicinal plants that were used to treat and prevent different types of digestive system disorders in their communities using quantitative ethnobotanical approaches. Ethno medicinal data were collected from 30 informants regarding their knowledge on medicinal plants. Quantitative approaches were used to determine the use value and informant consensus factor values of collected data. The results revealed that the Baduy currently use 54 medicinal plant species belonging to 30 families to treat digestive system disorders. Additional research is required, however, to validate the function of the medicinal plants and identify their active compounds.
Co-Authors Achmad Abdur Rozaq Ahendyarti, Ceri Alimuddin, A. Elhadj Dogheche Fachry Abda El Rahman Fauzan, Anugrah Nuur Hamzah Hamzah Heri Kusharyanto Hermawan, Cecep Maman Imamul Muttakin Indria Wahyuni Irwan, Sobriansyah Kevin Dilly Junior Luh Putu Ratna Sundari Lukman Nul Hakim Lukman Nul Hakim Mega Tjaraka, Mega Muchtar Ali Setyo Yudono Nji Raden Poespawati OKTA ROSFIANI Prasart Nuangchalerm, Prasart Rahmah, Aqila Azizah Retno Wigajatri Purnamaningsih Ri Munarto Ri Munarto, Ri Rian Fahrizal Rida Oktorida Khastini RIYANDIKA, RIZKY Rocky Alfanz, Rocky Rohmadi Rohmadi Supriyanto Supriyanto Syah Alam Teguh Firmansyah Toto Supriyanto Wahyuni, Indria Wahyuni Wildan, Muh.