Article Per Year (5 Year)
p-Index From 2020 - 2025
4.091
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Eksos LPPM Techno LPPM Seminar Nasional Informatika (SEMNASIF) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Mineral, Energi dan Lingkungan Compiler Jurnal Ilmiah Lingkungan Kebumian Jurnal Mineral, Energi dan Lingkungan Teknika IEJST (Industrial Engineering Journal of the University of Sarjanawiyata Tamansiswa) Science in Information Technology Letters Industrial Research Workshop and National Seminar Jurnal Pengabdian Literasi Digital Indonesia Jurnal Pendidikan Geosfer Bulletin of Social Informatics Theory and Application Globe: Publikasi Ilmu Teknik, Teknologi Kebumian, Ilmu Perkapalan
Awang Hendrianto Pratomo
(SCOPUS ID 35174983600, Universitas Pembangunan Nasional Veteran Yogyakarta), Indonesia
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

Published : 40 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Science in Information Technology Letters

 1 
Image processing for student emotion monitoring based on fisherface method Awang Hendrianto Pratomo; Mangaras Yanu Florestyanto; Y I Sania; B Ihsan; H H Triharminto; Leonel Hernandez
Science in Information Technology Letters Vol 2, No 1: May 2021
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v2i1.690

Abstract

Monitoring academic emotion is an activity to provide information from students' academic emotions in the class continuously. Some research in the image processing field had done for face recognition but had not been many studies on image processing to detect student emotions. This paper aims to determine the percentage of facial recognition with fisherface and academic emotional recognition by monitoring changes in students' facial expressions using facial landmarks in various distances, camera angles, light, and attributes used on objects. The proposed method uses facial image extraction based on fisherface method for presence. Furthermore, face identification will be made with Euclidean distance by finding the smallest length of training data with test data. Emotion detection is done by facial landmarks and mathematical calculations to detect drowsiness, focus, and not focus on the face. Restful web service is used as a communication architecture to integrate data. The success rate of applications with the fisherface method obtains 96% percent accuracy of face recognition. Meanwhile, facial landmarks and mathematical calculations are used to detect emotions, with 84 %.
Optimizing CNN hyperparameters with genetic algorithms for face mask usage classification Awang Hendrianto Pratomo; Nur Heri Cahyana; Septi Nur Indrawati
Science in Information Technology Letters Vol 4, No 1 (2023): May 2023
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v4i1.1182

Abstract

Convolutional Neural Networks (CNNs) have gained significant traction in the field of image categorization, particularly in the domains of health and safety. This study aims to categorize the utilization of face masks, which is a vital determinant of respiratory health. Convolutional neural networks (CNNs) possess a high level of complexity, making it crucial to execute hyperparameter adjustment in order to optimize the performance of the model. The conventional approach of trial-and-error hyperparameter configuration often yields suboptimal outcomes and is time-consuming. Genetic Algorithms (GA), an optimization technique grounded in the principles of natural selection, were employed to identify the optimal hyperparameters for Convolutional Neural Networks (CNNs). The objective was to enhance the performance of the model, namely in the classification of photographs into two categories: those with face masks and those without face masks. The convolutional neural network (CNN) model, which was enhanced by the utilization of hyperparameters adjusted by a genetic algorithm (GA), demonstrated a commendable accuracy rate of 94.82% following rigorous testing and validation procedures. The observed outcome exhibited a 2.04% improvement compared to models that employed a trial and error approach for hyperparameter tuning. Our research exhibits exceptional quality in the domain of investigations utilizing Convolutional Neural Networks (CNNs). Our research integrates the resilience of Genetic Algorithms (GA), in contrast to previous studies that employed Convolutional Neural Networks (CNN) or conventional machine learning models without adjusting hyperparameters. This unique approach enhances the accuracy and methodology of hyperparameter tuning in Convolutional Neural Networks (CNNs). 
Co-Authors Abdur Rahman, Hafidz Fajar Agung Yulianto Nugroho Agung Yulianto Nugroho Agus Ristono Agusdin, Riza Prapascatama Alamin, Duta Alek Setiyo Nugroho Anak Agung Istri Sri Wiadnyani Andiko Putro Suryotomo Anton Satria Prabuwono Anton Satria Prabuwono Arif Rianto Budi Nugroho Arif Rianto Budi Nugroho Augyeris Lioga Seandrio B Ihsan Balza Ahmad Bambang Yuwono Danang Arif Rahmanda Dessyanto Boedi Prasetyo Dimas Candra Nugraha Putra Eko Teguh Paripurno Eko Teguh Paripurno Ficky Adi Kurniawan Ficky Adi Kurniawan Frans Richard Kodong Granitia Septirina Junaedi H H Triharminto Hafidz Fajar Abdur Rahman Hafidz Fajar Abdur Rahman, Hafidz Fajar Abdur Heru Cahya Rustamaji Heru Cahya Rustamaji Heru Cahya Rustamaji Hidayatulah Himawan Indra Aprillinfanteri Army Johan Danu Prasetya Kahiruddin Omar Khairuddin Omar Kusmendar, Kusmendar Leonel Hernandez Mangaras Yanu F Mochammad Assofa Indera Jati Mohd Shanudin Zakaria Mohd Shanudin Zakaria Muhadjir Fachrurradjie Muhammad Arif Wijaya Muhammad Rifai Samekta Adi Nandra Eko Nugroho Nidya Indah Sari Nur Heri Cahyana Nur Heri Cahyana Nur Heri Cahyana Nur Heri Cahyana Nuryono Satya Widodo Nuryono Setya Widodo Nuryono Setyo Widodo Oliver Samuel Simanjuntak Oyas Wahyunggoro Prasetya, Johan Danu Puji Pratiknyo Purwoto Purwoto Putra, Dimas Candra Nugraha Rachmad, Faiz Rafly Pradana Putra Rifki Indra Perwira Sabihaini Sabihaini Saifullah, Shoffan Septi Nur Indrawati Setiyo Hartato Setiyo Hartato M Siti Mu'arifah Siti Norul Huda Seikh Abdullah Siti Norul Huda Syeikh Abdullah Sudaryatie Sudaryatie Susilastuti Dwi Nugraha Jati Tahalea, Sylvert Prian Tejo Pramono Triharminto, Hendri Himawan Wahyu Sugeng Triadi Wilis Kaswidjanti Wilis Kaswidjanti Wilis Kaswidjanti Wilis Kaswidjanti Wiratama Putra Y I Sania Yenni Sri Utami Yuli Fauziah