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All Journal Syntax Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal RESISTOR (Rekayasa Sistem Komputer) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknik Informatika (JUTIF) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Eduvest - Journal of Universal Studies
Faisal, Sutan
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Journal : Building of Informatics, Technology and Science

 1 
Perbandingan Metode K-Means dan K-Medoids Untuk Clustering Jenis Kriminalitas Azizah, Nurul; Fauzi, Ahmad; Rohana, Tatang; Faisal, Sutan
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5723

Abstract

Crime in Indonesia includes acts that violate the law, social norms and religion which cause economic and psychological losses as well as social tensions in society. Crimes such as theft, violence, fraud and drugs are often triggered by factors such as poverty and environmental conditions that support criminal behavior. This research needs to be carried out to overcome the complex and far-reaching crime problem in Indonesia, especially in Karawang Regency. With crimes such as theft, violence, fraud and drugs on the rise, often fueled by factors such as poverty and environmental conditions, a more effective approach is needed to understand and address these problems. This research uses data mining techniques, especially cluster analysis, to group types of crime. The aim is to identify existing crime patterns and understand the factors that influence their spread. Thus, the results of this research can help the authorities in developing more targeted crime prevention and handling strategies, so as to minimize the negative impact of crime in the area. Apart from that, this research also contributes to increasing knowledge regarding the most effective methods for analyzing crime data, which can be applied in other areas with similar problems. The results of the research show that the K-Means algorithm is more effective than K-Medoids in handling data variability, with a Silhouette Coefficient value of 0.482 and a Davies Bouldin Index of 0.915. It is hoped that the implementation of this algorithm will make it easier to identify and handle crimes in the area.
Implementasi Algoritma Convolutional Neural Network dan YOLOV8 Untuk Klasifikasi Ras Kucing Adinata, Abdul Rohim; Rohana, Tatang; Baihaqi, Kiki Ahmad; Faisal, Sutan
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5913

Abstract

The cat with the scientific name Felis catus is a very popular pet and is often kept in various parts of the world. There are many types or breeds of cats, each of which has its own characteristics and characteristics, such as style, body shape, fur and color. However, because of the many breeds and the uniqueness of each breed, it is often difficult for ordinary people to differentiate between the types of cat breeds that exist. Therefore, technology is needed to identify and differentiate cat breeds. By comparing the Convolutional Neural Network (CNN) and YOLOV8 methods, this research aims to develop a cat breed classification model. This research uses data from six different cat breeds, namely Bengal, Bombay, Himalayan, Local, Persian and Sphynx. There are 1,200 images in all, with 200 images for each race. Before the data is used for training with the CNN and YOLOV8 methods, a preprocessing stage is carried out which includes resize and rescale for the CNN method, while for YOLOV8 a data labeling process is carried out. There are two parts to the dataset: 20% validation data and 80% training data. The training process is carried out with the same parameters for each model, namely a learning rate of 0.001, batch size of 15, and 100 epochs. From the test results with the confusion matrix, the YOLOV8 model shows the best performance with an accuracy value of 99%, precision 96.1%, recall 98.4%, and F1-score 97.2%.
Co-Authors Adinata, Abdul Rohim Al Fathir Rizal Januar Alganiu, Ajeng Shalwa Alvionika, Nindy Amril Mutoi Siregar Ardiansyah, Fikri ARIF, SITI NOVIANTI NURAINI Arum Puspita Lestari, Santi Awal, Elsa Elvira Azhaar, Siti Alia Baihaqi, Kiki Ahmad Fauzi Ahmad Muda Fitri Nur Masruriyah, Anis Halif, Jenny Hanny Hikmayanti Handayani Hartono Wijaya, Sony Hermawan, Slamet Iman Sanjaya Indra, Jamaludin Jamiluddin, Fathir Jayidan, Zirji Juwita, Ayu Ratna Koirunnisa, Koirunnisa Kusumaningrum, Dwi Sulistya Lestari, Santi Arum Puspita Maulana, Ikhsan Mudzakir, Tohirin Al Munzi, Gugy Guztaman nabila, putri Niendha Biell Binna Novita, Hilda Yulia NURUL AZIZAH Pratama, Adi Rizky Pratama, Rio Purnama, Ariya Rachmawati, Dhea Rafikoh, Zahra Anggun Rahmat Rahmat Rohana, Tatang Romlah Siregar, Amril Mutoi Sujana, Sylvia Tjong Wan Sen Tri Vicika, Vikha Tukino, Tukino Wahiddin, Deden Wicaksana, Yusuf Eka Yaman, Nuurul Izzati Yana Cahyana