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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Simantec Jurnal Sisfokom (Sistem Informasi dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer International Journal of Engineering, Technology and Natural Sciences (IJETS) International Journal of Advances in Data and Information Systems Jurnal Janitra Informatika dan Sistem Informasi Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Informatika dan Teknologi Pendidikan Journal of Scientific Research, Education, and Technology Jurnal Komputer dan Teknologi (JUKOMTEK)
Ahmad Tri Hidayat
Universitas Teknologi Yogyakarta
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Social Sciences

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Development of a Violence Scene Prediction System in Films Based on Visual Poster Analysis Using The Machine Learning Method Convolutional Neural Network(CNN) Immanuel V William; Ahmad Tri Hidayat
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 5 No. 2 (2026): Vol. 5 No. 2 2026
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v5i2.1003

Abstract

Films as an entertainment often contain various visual elements, one of which is violent scenes. In some cases, the presence of violence in films can have a negative impact on viewers, especially children. Therefore, a system is needed that can predict the potential existence of violent scenes in a film, particularly based on poster. This research aims to develop a system that uses machine learning methods to analyze movie posters and estimate the likelihood of the film containing violent scenes. The designed system will be trained using a dataset of movie posters labeled according to the level of violence present in the films. The posters will be analyzed using digital image processing techniques, and the results will serve as input for the machine learning model used in the system. The development process involves using artificial neural network (ANN) techniques, which have been proven effective in detecting relevant visual patterns. The research results show that the proposed system can achieve a high level of accuracy in predicting films that contain violent scenes based on their visual posters. Thus, this system can be useful for the film industry, parents, and regulatory agencies to identify inappropriate films for certain age before their release.
Implementasi Sistem Pengendalian Hama Kopi dengan Sumber Daya Panel Surya Berbasis IoT Wahyu Sulastri; Ilham Saputro; Kartika Syifa; Ikrima Alfi; Ahmad Tri Hidayat
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 6 No. 1 (2026): Mei 2026 - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v6i1.294

Abstract

Kopi merupakan salah satu komoditas ekspor unggulan di Indonesia, namun produktivitas dan kualitas biji kopi sering menghadapi ancaman serius dari berbagai jenis hama seperti hypothenemus hampei (H. hampei). Meskipun penggunaan pestisida kimia umum dilakukan untuk pengendalian hama, metode ini menimbulkan dampak negatif bagi lingkungan dan kesehatan. Untuk itu diperlukan pengendalian hama yang ramah lingkungan. Pengabdian ini bertujuan untuk mengenalkan teknologi dalam pertanian dengan mengembangkan alat pembasmi hama menggunakan insect light trap dan kawat listrik dengan sumber daya panel surya berbasis IoT. Program pengabdian masyarakat ini telah berhasil menerapkan sistem pembasmi hama yang ramah lingkungan. Penerapan sistem ini membuka wawasan petani bahwa teknologi yang diterapkan pada bidang pertanian lebih efektif dan sangat mempermudah kinerja petani.
Co-Authors Adib Mubarok Adityo Nugroho, Adityo Afwan Anggara Aini, Anggun Nur Andi Muhammad Dirham Dewantara Damayanti, Elok Dewantara, Rizki Fachrun Wira Prana Fatkhur Rohman, Arif Fendari, Sausan Nada Lutfi Fitriana, Anis Gilang Estu Saputra Haq, Ellail Has Hasshol Ikrima Alfi Ilham Saputro Immanuel V William Ismail Ibraheem, Kais Jaka Pratama, Moh Alfrizal Septian Joko Aryanto Kartika Syifa Nur Alifah, Putri Pambudi, Tegar Prakosa, Riyo Fendi Pramukti, Latif Fajar Pratama, Yoga Surya Putro, Lilik Hananto Rahmadina, Atya Ridwan, Ridwan Ryan Maulana Saiful Bahri Saifullah, Shoffan Santoso, Dimas Saucha Diwandari Setiawan, Imam Budi Suhirman Sutarman Sutarman Suyoto Suyoto Suyud Widiono Wahyu Adjie Saputra Wahyu Sulastri Yuli Wijayanti YULI WIJAYANTI