Article Per Year (5 Year)
p-Index From 2020 - 2025
4.905
P-Index
This Author published in this journals
All Journal Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research Jurnal Informatika Jurnal Mantik Penusa JIPN (Journal of Informatics Pelita Nusantara) JURTEKSI JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Visi Pengabdian Kepada Masyarakat Jurnal Media Informatika Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) JURNAL PENELITIAN BIDANG PENDIDIKAN Jurnal Pengabdian Inovasi Masyarakat Indonesia Jurnal Ilmiah Multidisiplin Indonesia Jurnal Pengabdian Masyarakat Multi Disiplin Ilmu Jurnal Pengabdian Masyarakat (Jubdimas)
Erwin Panggabean
STMIK Pelita Nusantara, Medan
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

Published : 44 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 44 Documents
Search

 1   2   3   4   5 
DETEKSI EMOSI SISWA SMKS METHODIST 8 BERBASIS AI UNTUK MEMBANTU DALAM PEMBELAJARAN Panggabean, Erwin; Simanjuntak, Richs; Apriani, Wira; Sihotang, Amran; Sinaga, Bosker
JUBDIMAS ( Jurnal Pengabdian Masyarakat) Vol 4 No 1 (2025): Jurnal Pengabdian Masyarakat, Maret 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jubdimas.v4i1.383

Abstract

The research conducted through community service aims to develop artificial intelligence (AI)-based software capable of detecting students' emotions at SMKS Methodist 8 in real time, as an effort to support teachers in implementing a more adaptive and responsive learning approach. This system is designed by integrating facial recognition and emotional expression analysis through a camera, which is then processed using the Certainty Factor method to determine the confidence level of the detected emotional classification. This approach allows the system to generate emotional diagnoses with a reliable degree of confidence, based on predefined parameters. Test results have shown that the software is capable of detecting several basic emotions such as happiness, sadness, anger, and neutrality with an adequate level of accuracy. The implementation of this system in classrooms is expected to assist teachers in quickly identifying students’ emotional states, allowing learning strategies to be adjusted accordingly to improve the effectiveness of the learning process. Therefore, this technology offers an innovative solution in supporting the improvement of education quality through an approach that focuses on individual students.
Penyuluhan Penggunaan Handhold Scanner Posiflex Pada Sistem Penjualan Dan Pembelian Di SMA Swasta Cahaya Medan Panggabean, Erwin
Jurnal Pengabdian Masyarakat Disiplin Ilmu Vol. 1 No. 2 (2023): Jurnal Pengabdian Masyarakat Multi Dispilin Ilmu Juli 2023
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpmasdi.v1i2.2589

Abstract

Penyuluhan tentang penggunaan Handhold Scanner Posiflex CD 3860 Series CD-3860U-B pada sistem penjualan dan pembelian di SMU Swasta CahayaMedan bertujuan untuk memberikan pemahaman tentang cara menggunakan perangkat scanner pada proses penjualan dan pembelian di perusahaan-perusahaan tertentu, atau toko-toko tertentu. Penyuluhan dilakukan dengan menggunakan metode ceramah dan praktek langsung di depan siswa siswi SMA Cahaya 1 Medan. Peserta akan diajarkan cara mengoperasikan scanner, memindai kode barcode, dan mengimpor data hasil pemindaian ke sistem penjualan dan pembelian. Hasil penyuluhan menunjukkan bahwa penggunaan scanner dapat membantu mempercepat proses transaksi dan meningkatkan efisiensi pengolahan data. Selain itu, peserta juga mendapatkan pemahaman tentang pentingnya menjaga dan merawat perangkat scanner untuk memastikan kinerjanya yang optimal. Kesimpulannya, penyuluhan ini memberikan manfaat penting bagi siswa SMA Cahaya 1 Medan dalam meningkatkan keterampilan dan pengetahuan mereka tentang penggunaan teknologi scanner pada sistem penjualan dan pembelian.
Integrated Cnn Based Facial Emotion Detection And Camera Based PPG Heart Rate Monitoring Panggabean, Erwin; Simanjorang, R. Mahdelena; Apriani , Wira; Nuraisana , Nuraisana; Sipahutar, Hartati Palentina; Siagian, Tesalonika Pesta
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6299

Abstract

Human emotion detection and heart rate estimation are two important aspects in developing a more responsive and adaptive human-computer interaction system. This study proposes a real-time video-based system that is able to detect facial emotions and estimate the user's heart rate simultaneously. The Convolutional Neural Network (CNN) method is used to classify facial expressions into several emotion categories such as happy, sad, angry, afraid, and neutral. Meanwhile, heart rate estimation is carried out using a non-contact Photoplethysmography (PPG) approach, which utilizes variations in color intensity in the user's facial area from video recordings to calculate the pulse rate. This system is developed using a standard webcam camera without additional medical devices, allowing for practical and economical implementation. The test results show that the system is able to recognize facial expressions with good accuracy, and estimate heart rate with an average error rate that is still within the tolerance limit of non-medical applications. By integrating computer vision technology and biometric signals, this study contributes to the development of a passive, real-time, and easily accessible emotion and health monitoring system.
Hybrid System for Palm Line Detection and Educational Health Prediction Using Certainty Factor Method Erwin Panggabean; Wira Apriani; Nuraisana, Nuraisana; Penda Sudarto Hasugian
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 4 No. 06 (2025): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), July 2025
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The difficulty in understanding individual characteristics based on palm lines is still an attraction in the context of education and technology-based experiments. This study aims to develop an educational application that is able to detect palm lines using a laptop camera, then predict certain characters or conditions based on the input. This system is built using the Certainty Factor (CF) method to provide certainty-based inferences on the visual symptoms of the detected palm lines. The process begins with taking a picture of the hand directly through the camera, followed by detection of main lines such as the life line, head line, and heart line using simple image processing techniques. After that, the system will display symptom-based questions related to the shape of the visible palm lines, then calculate the certainty value of the inference results using CF. This application is non-commercial and was developed as an educational tool to introduce the basic concepts of expert systems and Python-based visual processing. The system has successfully detected major palm lines with an accuracy of 80% under standard lighting conditions, and produced predictive results with certainty values that matched expected outcomes in over 70% of test cases. This demonstrates the potential of the CF method in processing visual data for educational inference. The system functions reliably as an educational tool, successfully demonstrating how certainty-based logic can be applied to simple visual data, and has been well-received in testing scenarios for learning purposes.
Co-Authors Abdul Jabbar Lubis Ade Putri Humaira Anita Sindar Apriani , Wira Ariani Natalia Sianturi Aritana Lahagu Aritonang, Tri Evalina Bosker Sinaga Damayanti, Alfina Dedi Sinaga, Dedi Dewi, Sumitra Dwi Novia Amala Faduhusi Lombu Fauduziduhu Laia Fitra, Awaludin Fransisco alexander Simbolon Gea, Asaziduhu Ginting, Ricky Martin Guntur Syahputra Guntur Syahputra Haida Dafitri Hengki Tamando Sihotang Herlina Zebua Ira Lina Kendayto Panjaitan Jijon R. Sagala Jijon R. Sagala Jijon Raphita Sagala, Jijon Raphita Josua, Alpon Juandi Syahfutra Simatupang Junita , Diana Justrina Br. Surbakti Justrina Br.Surbakto Kune, Margaritha M. Lahagu, Aritana Laia, Fauduziduhu Lase , Yulianto Logaraj Logaraj Lombu, Faduhusi Margaritha M. Kune Mulyana, Sri Ulina Nora Anisa Br. Sinulingga Nur Wulan Nuraisana , Nuraisana Nuraisana Nuraisana Nuraisana, Nuraisana Olven Manahan Pakpahan, Robertus Rinaldi Penda Sudarto Hasugian Ramadhan, Alya Sophia Risa Kartika Lubis Selvia, Sindu Siagian, Tesalonika Pesta Sihombing, Agus Putra Emas Sihotang, Amran Simangunsong, Agustina Simanjorang, R. Mahdelena Simanjuntak, Richs Sinaga, Anita Sindar Sinaga, Anita Sindar Ros Maryana Sindar Sinaga, Anita Sipahutar, Hartati Palentina Sitio, Arjon Samuel Sitorus, Martua Sri Mulyani Sri Mulyani Sri Ulina Mulyana Sulindawaty, Sulindawaty Sumi Khairani Telaumbanua, Imelda Tiara W Pratiwi Utami, Yulia Vinsensia, Desi Wanra Tarigan Wira Apriani Yerianus Lase