Article Per Year (5 Year)
p-Index From 2020 - 2025
4.537
P-Index
This Author published in this journals
All Journal Jurnal Media Infotama Sistemasi: Jurnal Sistem Informasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Menara Ilmu JATI (Jurnal Mahasiswa Teknik Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Education Research Jurnal Sains Informatika Terapan (JSIT) Jurnal Komtekinfo Indo Green Journal Jurnal Quancom: Jurnal Quantum Komputer Journal of Information System and Education Development Jurnal Pengabdian Masyarakat Bangsa Jurnal TAM (Technology Acceptance Model)
Hendrik, Billy
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

Published : 33 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 33 Documents
Search

 1   2   3   4 
Perbandingan Metode Deep Learning dalam Deteksi Kekerasan Fisik Berbasis Video: Studi Literatur pada CNN, RNN/LSTM, 3D-CNN, dan YOLO Hasibuan, Elpina Sari Dewi; Hendrik, Billy
Journal of Education Research Vol. 6 No. 4 (2025): in Progress
Publisher : Perkumpulan Pengelola Jurnal PAUD Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37985/jer.v6i4.2180

Abstract

Deteksi tindak kekerasan merupakan salah satu tantangan utama dalam pengembangan sistem keamanan berbasis teknologi, khususnya pada pengawasan video. Penelitian ini bertujuan untuk melakukan kajian literatur mengenai keunggulan, kekurangan, dan aplikasi dari berbagai metode kecerdasan buatan, yaitu Convolutional Neural Network (CNN), Recurrent Neural Network (RNN)/Long Short-Term Memory (LSTM), 3D Convolutional Neural Network (3D-CNN), dan You Only Look Once (YOLO), dalam mendeteksi tindak kekerasan fisik. CNN dikenal efektif dalam mengenali pola visual statis, sementara RNN/LSTM unggul dalam analisis data sekuensial yang melibatkan aspek temporal. Di sisi lain, 3D-CNN menawarkan kemampuan untuk menangkap pola spasial dan temporal secara bersamaan dalam video, sedangkan YOLO menyediakan pendekatan real-time untuk deteksi objek, yang relevan untuk mendeteksi kekerasan dengan efisiensi tinggi. Studi ini membahas performa keempat metode berdasarkan parameter seperti akurasi, kecepatan, kompleksitas, dan kemampuan adaptasi terhadap data dunia nyata. Kajian ini diharapkan memberikan wawasan mendalam bagi pengembang sistem keamanan berbasis video dalam memilih metode yang paling sesuai untuk kebutuhan spesifik dalam mendeteksi tindak kekerasan fisik.
Application of Fuzzy Logic Method and Analytical Hierarchy Process in Assessment of Education Quality at the Madrasah Aliyah Level Andi, Muhammad Yusril Haffandi; Nurcahyo, Gunadi Widi; Hendrik, Billy
Jurnal KomtekInfo Vol. 12 No. 3 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i3.653

Abstract

Madrasas have a strategic role in producing a generation of the nation that is intellectually intelligent as well as spiritually and emotionally mature, but the quality between madrasas is still uneven, especially in rural areas such as Kerinci Regency. The assessment of the quality of madrasas until now tends to be subjective and has not been based on a measurable, systematic, and widely replicated system. This research aims to develop an objective and structured quality evaluation system for madrasah education using a technology-based approach. The methods used are Fuzzy Logic and Analytical Hierarchy Process (AHP) which are combined into Fuzzy AHP. The scope of the research is focused on aliyah madrasas under the coordination of the Ministry of Religious Affairs of Kerinci Regency. The data was obtained through direct interviews with the Head of the Madrasah Education Section and included eight aliyah madrasas as the object of the research, which were assessed based on nine main criteria: quality of teachers, teaching materials, infrastructure, school governance, learning environment, assessment system, leadership of school principals, parental support, and technology and digitalization. A web-based decision support system was developed to automatically manage Fuzzy AHP calculations, so that it can be used as a continuous evaluation tool. The results of the study show that this model is able to produce consistent, objective, and valid assessments with a Consistency Ratio (CR) value of < 0.1. Madrasah MA2 obtained the highest ranking in the assessment of the quality of education. The Fuzzy AHP approach has proven to be effective in multi-criteria education evaluation and can be the basis for policies that are more responsive to local needs.
Shortest Path Navigation Optimization using Algorithm A* in GPS-Based Augmented Reality Visualization Aswandi, Nopan; Hendrik, Billy; Arlis, Syafri
Jurnal KomtekInfo Vol. 12 No. 3 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i3.654

Abstract

The development of digital technology in the Society 5.0 era encourages the integration of technology-based solutions in various fields, including higher education. Ibnu Sina University faces challenges in providing informative and accurate access to campus navigation, especially for new students and visitors. The lack of a directional system and the absence of a digital map of the campus cause difficulties in finding service locations such as the rectorate, academic room, or finance department. Conventional technologies such as Google Maps have not been able to provide specific navigation in the campus environment due to the limitations of internal building mapping. This research aims to develop a campus navigation system based on Augmented Reality (AR) and Global Positioning System (GPS) that is optimized with the A* (A-Star) algorithm for the determination of the shortest path. AR technology is used to display visual directions in real-time in a real environment through a smartphone camera. GPS plays a role in determining the user's position, while the A* algorithm calculates the shortest route based on the structure of the campus location graph using a heuristic approach. The development method used is the Multimedia Development Life Cycle (MDLC) which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. Data collection was carried out through direct observation, interviews with the campus, and recording 14 coordinate points of campus service locations using Google Earth. The system is built using the Unity platform with support from the AR Foundation and ARLocation, as well as the A* implementation in route search. The results of this research are able to provide a more efficient, accurate, and interactive campus navigation solution. This system not only supports the convenience of users in finding a location, but also becomes an innovation in the development of campus services based on digital technology.
Co-Authors A'yuni, Qurrata Abdi Juliantho, Dwana Abdi Julianto, Dwana Ade saputra Amri, Yassirli Andi, Muhammad Yusril Haffandi Aswandi, Nopan Awal, Hasri Budiantoro, Hendro Deti Karmanita Febby Olivia, Ladyka Gevindo, Aprilian Gunadi Widi Nurcahyo Haffandi, Muhammad Yusril Hasibuan, Elpina Sari Dewi Ikhlas, Ariza Indhira, Sonia Lubis, Fitri Amelia Sari Lubis, Siti Sahara Mardhiah Masril Muhammad, Imam Fakhri Nasution, Ayu Lestiani Nugraha, Fajri Olivia, Ladyka Febby Raharjo, Tio Doli Resnawita Ridwan, Ridwan Ritna Wahyuni Ruri Hartika Zain Rusydi, Rezki Sahara Lubis, Siti Sani, Fadhila Putri Sonia Indhira Subarja, Roy Efendi Sumijan Supperianto, Bambang Suri, Melati Rahma Syafri Arlis Tamin, Zulfiqar Vidyanti, Angela Yuhandri