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All Journal Jurnal Teknologi Industri Pertanian Teknotan: Jurnal Industri Teknologi Pertanian Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Jurnal Aplikasi Teknologi Pangan Indonesian Journal of Chemistry IKRA-ITH Humaniora : Jurnal Sosial dan Humaniora JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Conference on Innovation and Application of Science and Technology (CIASTECH) Jurnal RESISTOR (Rekayasa Sistem Komputer) IKRA-ITH ABDIMAS Pontianak Nutrition Journal (PNJ) Journal of Industrial and Information Technology in Agriculture Canrea Journal: Food Technology, Nutritions, and Culinary Journal Jurnal Abdi Insani JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Food ScienTech Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Decode: Jurnal Pendidikan Teknologi Informasi SN-Biosper Scientific Student Journal for Information, Technology and Science Jurnal Buana Pengabdian Pontianak Nutrition Journal (PNJ) Composite Jurnal Sains dan Teknologi Pangan Jurnal Komtika (Komputasi dan Informatika)
Yana Cahyana
Fakultas Teknologi Industri Pertanian, Universitas Padjadjaran
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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
CLASSIFICATION OF RICE PLANTS AFFECTED BY RATS USING THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM Nofie Prasetiyo; Baihaqi, Kiki Ahmad; Lestari, Santi Arum Puspita; Cahyana, Yana
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1949

Abstract

In the era of Indonesia's agrarian economy which is supported by the agricultural sector, rice plants play an important role in meeting food needs. However, pest attacks, especially field mice, can cause significant losses in rice production. To overcome this, this research proposes the use of the Support Vector Machine (SVM) algorithm with the Particle Swarm Optimization method in predicting rat pest attacks on rice plants. This research involves the process of collecting data from drone photos to identify affected agricultural land. The preprocessing stage involves changing colors from RGB to GRAY and zoom augmentation. Feature extraction is carried out using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP). Testing was carried out involving the SVM/SVC model and performance evaluation was carried out using accuracy, precision and recall metrics. The preprocessing test results showed an increase in performance with training accuracy of 68.33%. However, the actual prediction on the original image results in a low accuracy of around 25%. However, image testing after involving the entire process, including preprocessing and model prediction, shows a higher level of accuracy, reaching around 90%.
IMPLEMENTATION OF THE YOLOV8 METHOD TO DETECT WORK SAFETY HELMETS Direja, Azhar Ferbista; Cahyana, Yana; Rahmat, Rahmat; Baihaqi, Kiki Ahmad
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.2005

Abstract

Work safety helmets are an important tool in OHS (Occupational Health and Safety) that must be used by workers. Workers who work with heavy equipment must wear work safety helmets as an obligation. Unfortunately, there are still many workers who do not comply with this rule. They will only wear helmets if there is supervision from a supervisor. However, if the supervisor is not on site, many workers will remove their helmets. The need for supervision of workers is important in reducing work accidents. From these problems, a work safety helmet detection model was created using the YOLOv8 method. This implementation aims to increase the accuracy values ​​obtained and can reduce workload and increase efficiency in checking violations of the use of work safety helmets among workers. The method used consists of several stages, namely image acquisition of 670 images, image labeling, preprocessing, augmentation in roboflow, YOLOv8x model training with 100 epochs, image testing with a distance of 1, 3, 5 meters between the object and the camera, evaluation of test results. Based on the results of training with 467 images, the mAP50 reached 99.5%. Meanwhile, the test results with 100 images showed an accuracy of 99%.
Co-Authors Abda Abda Abdullah Darussalam Addion Nizori Adi Rizky Pratama Adi Susilo Aenul Fuadah Agung Triatna Agustin, Rachmayanti Tri Ahmad Fauzi Alifa, Naila Ratu Ambarwati, Evi Karlina Amid Rakhman amril siregar Anisa Itiawanti Annisa Nurhalizah Aqib Zhaky Arum Galih Pertiwi Awal, Elsa Elvira Ayu Juwita Baihaqi, Kiki Ahmad Banafshah Shafa Bramandito Affandi Budiyanto Budiyanto Deden Wahiddin Dewi, Indah Purnama Didik Remaldhi Direja, Azhar Ferbista Duhita D Utama DWI KUSUMANINGRUM Een Sukarminah Efri Mardawati Enjelia, Lola Faisal, Sutan Fauzan Azima Fauzi Ahmad Muda Fitri Nur Masruriyah, Anis Fitria, Denisa Gumilar, Rizki Bintang Hanan, Sofiah Marwah Hanny Hikmayanti Handayani Hartono Wijaya, Sony Heri Hermawan Herlina Marta Hilda Novita Humaryanto, Humaryanto Iis Sadiah Imas Siti Setiasih In-In Hanidah Indira Lanti Kayaputri Indra Lasmana Tarigan Iskandar, Muhammad Irsyad Jovan Pangestu Juwita, Ayu Ratna Kiki Baihaqi Kusumaningrum, Dwi Sulistya Lestari, Santi Arum Puspita M. Budi Kusarpoko M. Naufal Faqih Madyawati Latief Marsetio Marsetio Melia Siti Ajijah Miptahul Ulum Mochamad Djali Mohammad Djali Mohammad Djali Mohammad Djali Mohammad Djali Mudzakir, Tohirin Al Muhamad Amirrullah Muhammad Fadillah, Farhan Muhammad Ramadhan Mursyid Djawas Narwan Nahrudin Nina Puspitaloka Nofie Prasetiyo Nova Wulandari Praditya Putri Utami Pratama, Adi Rizky Pratiwi, Sinta Amanda Putra Rizki Pangestu Putri, Septiani Nuruldharma Rachmawati, Dhea Rahmat Rahmat Rahmat Rahmat Rahmat Restiana, Resti Ricky Steven Chandra Ridho Pratama, Ilham Ridwan, Ridwan Rizka Ayu Permana Rizki Ananda Rizki Nur Annisa Rizky Nugraha Rizky Riyanto Robi Andoyo Rohana, Tatang Rossi Indiarto Sabirin Sandra Intan Sari Santi Lestari Seow, Eng Keng Siregar, Amril Siregar, Amril Mutoi Siregar, Amril Mutoi Siti Hanifah Khairun Nisa Suci Rahma Ajiaviaty Sukmawati, Cici Emilia Sulistya, Dwi Suningwar Mujiana Surya Martha Pratiwi Sutan Faisal Syahril, Ade Tatang Rohana Tita Rialita Tjong Wan Sen Tohirin Al Mudzakir Tsani Adiyanti Tukino, Tukino Utama, Duhita Diantiparamudita Wahiddin, Deden Wahyu Setio Aji Wazzan, Huda Wenda Adi Kusnaya Widiharto, Banani