Article Per Year (5 Year)
p-Index From 2019 - 2024
0.562
P-Index
This Author published in this journals
All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) ABDIMAS: Jurnal Pengabdian Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika)
Denis Prayogi
Universitas Ahmad Dahlan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Introduction of the Internet of Things as a Debriefing for Students with Cross Interests in Information Technology and Computers Imam Riadi; Sunardi; Denis Prayogi; Restu Prima Yudha; Muchrisal
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2022): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (701.654 KB) | DOI: 10.35568/abdimas.v5i2.2634

Abstract

Hangtuah Tarakan High School is one of the secondary schools in Tarakan City that has ICT cross-interest subjects. This subject is followed by students of class XI and XII from the Department of Mathematics and Natural Sciences (MIA) and Social Sciences (IIS). The focus of this study is embedded systems using sensors and microcontrollers. For learning to be optimized and related to current technological developments in the Industry 4.0 era, an introduction to the Internet of Things (IoT) is held to open students' insight and knowledge. The seminar using the presentation method (lecture) which was attended by 35 participants was held in the school's computer laboratory. Based on the initial survey conducted regarding the material to be presented, the participant’s knowledge about the material was categorized as not understanding with a score of 2.42 on the Linkert 5 scale. The school in collaboration with the Faculty of Industrial Technology through the Master  Program of Informatics held a seminar on the introduction of IoT on August 22, 2022. The 195-minute event from 11.45–15.00 received an enthusiastic welcome from the participants so that their understanding of the material increased. Based on the post-test survey, the level of understanding of the participants increased to a score of 3.64 on a score scale of 5 and entered the criteria for very understanding
Sistem Pengenalan Wajah pada Keamanan Ruangan Berbasis Convolutional Neural Network S Sunardi; Abdul Fadlil; Denis Prayogi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.480

Abstract

Face recognition is a biometric system that is widely applied in various fields especially in the security for identify and verify purposes. For every method of face recognition, they have a unique ways on the process with their advantages and disadvantages themselves. This study designs a face recognition system that is applied to a room security system using the Convolutional Neural Network (CNN). This method works by imitating the way nerve cells to communicate with interrelated neurons or rather mimics how artificial neural networks work in humans. The process of taking images as training data and the face recognition process using a webcam camera installed on a Raspberry pi-based device and python programming language with tensorflow library. Based on the results of research obtained using 875 data samples which were divided into 75% for training and 25% (or 219 data) for testing data produce predictions with 100% accuracy that means all data were successfully recognized.
Sistem Pengenalan Wajah pada Keamanan Ruangan Berbasis Convolutional Neural Network S Sunardi; Abdul Fadlil; Denis Prayogi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.480

Abstract

Face recognition is a biometric system that is widely applied in various fields especially in the security for identify and verify purposes. For every method of face recognition, they have a unique ways on the process with their advantages and disadvantages themselves. This study designs a face recognition system that is applied to a room security system using the Convolutional Neural Network (CNN). This method works by imitating the way nerve cells to communicate with interrelated neurons or rather mimics how artificial neural networks work in humans. The process of taking images as training data and the face recognition process using a webcam camera installed on a Raspberry pi-based device and python programming language with tensorflow library. Based on the results of research obtained using 875 data samples which were divided into 75% for training and 25% (or 219 data) for testing data produce predictions with 100% accuracy that means all data were successfully recognized.
Co-Authors Abdul Fadlil Imam Riadi Muchrisal Restu Prima Yudha Sunardi, Sunardi