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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 Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) 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

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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.
Pelatihan Software Matematika Geogebra Sebagai Media Pembelajaran Berbasis Teknologi Vinsensia, Desi; Utami, Yulia; Lubis, Risa Kartika; Panggabean, Erwin; Amala, Dwi Novia; Sianturi, Ariani Natalia
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 5 No. 3 (2024): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN) Edisi Mei- Agustus
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v5i3.3759

Abstract

Kemajuan teknologi pada dunia pendidikan sangat pesat, sehingga dapat digunakan dalam pembelajaran. Salah satu teknologi yang digunakan adalah software Geogebra. Geogebra berguna membantu siswa dalam memecahkan masalah disetiap persoalan. Matematika merupakan mata pelajaran yang sulit bagi kebanyakan siswa. Oleh karena itu siswa merasa matematika merupakan mata pelajaran yang membosankan, sangat sulit dalam memahami dan menyelesaikan persoalan matematika yang diberikan oleh guru. Berdasarkan hal tersebut pengabdian ini dilakukan dengan tujuan meningkatan kemampuan siswa dalam memahami pembelajaran matematika melalui pelatihan berbasis teknologi yakni Geogebra dengan belajar menggunakan Geogebra belajar matematika dengan sajian yang interaktif semakin menyenangkan dan tidak membosankan. Kegiatan pelatihan ini menggunakan metode ceramah, diskusi dan praktikum langsung kepada siswa-siswi. Hasil yang dicapai dalam kegiatan yang terdiri dari 30 siswa, sebanyak 93% siswa dapat menyelesaikan persoalan matematika diantaranya dengan nilai (100 – 91) sebanyak 4 siswa, nilai (90 – 81) sebanyak 18 dan nilai (80-71) sebanyak 6 siswa. Melalui kegiatan pengabdian ini juga, diharapkan keterampilan siswa-siswi dalam menggunakan bantuan Geogebra untuk belajar materi matematika di sekolah dan pemahaman siswa-siswi meningkat dan memahami konsep materi matematika secara efektif.
Forecasting Exponential Smoothing untuk Menentukan Jumlah Produksi Utami, Yulia; Vinsensia, Desi; Panggabean, Erwin
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 7 No. 1 (2024): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jikomsi.v7i1.2853

Abstract

Adapun tujuan dalam penelitian ini ialah meramalan jumlah penjualan untuk minggu berikutnya dengan menggunakan Single Eksponential Smoothing dan memberikan informasi kepada produsen tentang jumlah bahan baku yang akan dibutuhkan dalam proses pembuatan produksi, dengan mencari kesalahan terkecil melalui MAPE yang telah diuji dengan nilai konstanta alpha. Data dalam penelitian ini diambil berdasarkan data 1 bulan penjualan terakhir pada UMKM produsen keripik pisang didesa Selotong. Dalam pengolahan data peneliti menggunakan 3 Model Exponential Smoothing yaitu: Simple Seanonal Models, Winter’s Additive Models, Winter Multiplicative Models, dari 3 model tersebut peneliti mencari nilai MAPE tekecil untuk digunakan dalam peramalan jumlah produksi berikutnya. Berdasarkan hasil dari ketiga model tersebut didapat nilai MAPE terkecil pada model Winters’ Additive sebesar 11,565 artinya tingkat kesalahan dalam melakukan peramalan sebenar 11,56% dan peramalan tersebut dapat kategorikan baik. Maka forecast yang dihasilkan berdasarkan model Winters’ Additive ialah hasil forecast berdasarkan tabel diatas diperoleh pada minggu ke-5 hari selasa jumlah produksi sebesar 178 kg, pada minggu ke-5 hari rabu jumlah produksi sebesar 199 kg, pada minggu ke-5 hari kamis jumlah produksi sebesar 228 kg, pada minggu ke-5 hari jumat jumlah produksi sebesar 211 kg, pada minggu ke-5 pada hari sabtu jumlah produksi sebesar 217 kg.
The Comparison of the K Mean Algorithm with the C 45 Algorithm in Dataming Applications: Balancing Precision and Speed in Data Mining Solutions Panggabean, Erwin; Simangunsong, Agustina; Sinaga, Dedi; Sihombing, Agus Putra Emas; Aritonang, Tri Evalina
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5319

Abstract

This research topic discusses the comparison of the K-Means and C4.5 algorithms in the application of data mining to predict aquarium sales in a company. K-Means is a clustering algorithm that functions to group data based on similarity, for example grouping customers based on frequency or type of purchase. This helps companies understand market segments and design marketing strategies accordingly. Meanwhile, C4.5 is a classification algorithm that builds decision trees based on important attributes that influence sales, such as price, season, or promotions. This algorithm is able to predict sales categories, such as increases or decreases, based on historical data. By comparing these two algorithms, the research sought to find out which algorithm is more effective in helping companies predict sales and make strategic decisions. A combination of the two can also be used, with K-Means grouping the data first, then C4.5 classifying each segment formed. These results can provide more accurate sales predictions and more effective marketing strategies. This research is important to understand the effectiveness of algorithms in data mining to improve business decision making.
Peningkatan Mutu Biji Cokelat Dengan Sistem Pengeringan Otomatis Berbasis Internet of Things Sindar, Anita; Nuraisana; Erwin Panggabean; Bella Saputri; Nadia Aulia
Jurnal Visi Pengabdian Kepada Masyarakat Vol. 6 No. 2 (2025): Jurnal Visi Pengabdian Kepada Masyarakat : Edisi Agustus 2025
Publisher : LPPM Universitas HKBP Nommensen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51622/pengabdian.v6i2.2848

Abstract

The type of drying tool depends on the amount of production, availability of resources, and capital owned by farmers. Controlled drying can produce products with even quality and diminish the risk of disruption due to uncertain weather conditions. Automatic drying enables farmers to use various types of agricultural and plantation products, which require special drying equipment. Chocolate is a type of plant that is easy to grow and also provides high profits for farmers. After the harvest, farmers separate the cocoa beans to be dried in the sun. Drying relies on sunlight, it takes days to dry. To facilitate drying cocoa beans, farmers are introduced to automatic tools using sensors. The Internet of Things (IoT) works based on the type of sensor, the sensor reads the data and then works to produce temperature and heat that makes it easier to dry chocolate. This activity aims to produce maximum cocoa beans so that they can be sold at high prices.
Pemanfaatan Teknologi Internet of Things dalam Meningkatkan Hasil Pertanian Tanaman Melinjo Sinaga, Anita Sindar; Nuraisana, Nuraisana; Panggabean, Erwin; Mulyani, Sri; Damayanti, Alfina
Jurnal Pengabdian Inovasi Masyarakat Indonesia Vol. 4 No. 1 (2025): Edisi Februari
Publisher : Program Studi Pendidikan Kimia FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpimi.v4i1.6234

Abstract

Increasing productivity in the agricultural sector increasingly requires modernization of plant planting technology. This can be done by encouraging human resources such as helping farmers to be interested in knowledge about better and more appropriate agricultural techniques. Good agricultural technology must have a positive impact on the surrounding environment, not have a negative impact on human health and the surrounding environment, and be accessible and affordable to farmers. IoT tools are able to monitor soil through sensors that can measure soil conditions in real time. Sensors can observe various aspects of soil conditions, such as pH, humidity, temperature, and nutrients. IoT technology in the agricultural sector is utilized to achieve progress in melinjo plant production. Sensors as devices used can provide information on conditions such as soil humidity, air temperature, and humidity levels. Data obtained from sensors are sent via the internet to an intelligent system for analysis. The results of this analysis can provide information for farmers to make the right decisions to provide appropriate nutrition. Community service activities contribute to increasing melinjo plant agricultural yields in Dalu Sepuluh Village through the use of IoT technology for automatic plant watering.
DIAGNOSA AWAL PERKEMBANGAN MOTORIK BAYI PADA POSYANDU DESA SIDODADI BERBASIS KECERDASAN BUATAN Sindar, Anita; Nuraisana, Nuraisana; Panggabean, Erwin; Mulyani, Sri
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 4 (2024): Volume 5 No. 4 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i4.30923

Abstract

Kondisi ketidaknormalan motorik yang terjadi terus menerus pada balita dapat menyebabkan kemampuan pergerakan fisik anak terganggu selama hidup, sehingga sangatlah penting memberikan ransangan motorik pada bayi sejak lahir. Ruang lingkup kegiatan pengabdian di Desa Ramunia membantu penggerak posyandu meningkatkan kesehatan bayi umur 0 – 12 bulan dengan meperkenalkan cara mengetahui perkembangan bayi yang sebenarnya sesuai pertumbuhan usia bayi. Metode kegiatan diawali workshop kesehatan ibu dan bayi dilanjut memperkenalkan pengenalan sistem aplikasi yang bertujuan membantu para ibu bayi dapat memperhatikan kesesuaian maupun keterlambatan gerakan motorik kasar bayi yang dipandu melalui aplikasi ditutup dengan evaluasi kegiatan. Pelaksanaan diagnosa awal perkembangan motorik bayi usia 0-1 tahun sangat perlu diterapkan guna mendapatkan penanganan yang tepat secara medis. Dengan membangun sistem diagnosa yang dihasilkan melalui penerapan teknolologi kecerdasan buatan maka permasalahan stunting mudah terdeteksi.
Co-Authors Abdul Jabbar Lubis Ade Putri Humaira Amala, Dwi Novia Apriani , Wira Arikhifo, Arikhifo Aritana Lahagu Aritonang, Tri Evalina Bella Saputri Damayanti, Alfina Dedi Sinaga, Dedi Dewi, Sumitra Faduhusi Lombu Fauduziduhu Laia Fitra, Awaludin Fransisco alexander Simbolon Gea, Asaziduhu Ginting, Ricky Martin Guntur Syahputra Guntur Syahputra Haida Dafitri Harefa, Jikarni Hasugian, Penda Sudarto 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 Lubis, Risa Kartika Margaritha M. Kune Mulyana, Sri Ulina Nadia Aulia Nora Anisa Br. Sinulingga Nur Wulan Nuraisana Nuraisana , Nuraisana Nuraisana, Nuraisana Olven Manahan Pakpahan, Robertus Rinaldi Penda Sudarto Hasugian Ramadhan, Alya Sophia Selvia, Sindu Siagian, Tesalonika Pesta Sianturi, Ariani Natalia Sihombing, Agus Putra Emas Simangunsong, Agustina Simanjorang, R. Mahdalena Simanjorang, R. Mahdelena Sinaga, Anita Sindar Sinaga, Anita Sindar RM Sinaga, Anita Sindar Ros Maryana Sindar Sinaga, Anita Sipahutar, Hartati Palentina Sitio, Arjon Samuel Sitohang, Amran Sitorus, Martua Sri Mulyani Sri Ulina Mulyana Sulindawaty, Sulindawaty Sumi Khairani Telaumbanua, Imelda Tiara W Pratiwi Utami, Yulia Vinsensia, Desi Wanra Tarigan Wira Apriani Yerianus Lase