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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal Information System Development ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Sistem Informasi Kaputama (JSIK) Building of Informatics, Technology and Science Majalah Ilmiah Warta Dharmawangsa JTIK (Jurnal Teknik Informatika Kaputama) JUKI : Jurnal Komputer dan Informatika Jurnal Manajemen Informatika Jayakarta Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Journal of Vision and Ideas (VISA) Jurnal Pengabdian Masyarakat IPTEK EXPLORER Bulletin of Multi-Disciplinary Science and Applied Technology Journal Of Human And Education (JAHE) Journal of Information Systems and Technology Research Sci-Tech Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Ulead : Jurnal E-pengabdian Journal of Engineering, Technology and Computing (JETCom) Journal of Mathematics and Technology (MATECH) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) JOURNAL OF ICT APLICATIONS AND SYSTEM Jurnal Teknik, Komputer, Agroteknologi dan Sains Zadama: Jurnal Pengabdian Masyarakat International Journal of Health, Engineering and Technology Jurnal Penelitian Sistem Informasi Indonesian Journal of Education And Computer Science Indonesian Journal of Science, Technology, and Humanities Pengabdian Pendidikan Indonesia (PPI) Jurnal Ilmu Komputer dan Sistem Informasi Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan Switch: Jurnal Sains dan Teknologi Informasi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Saturnus: Jurnal Teknologi dan Sistem Informasi KETIK : Jurnal Informatika Ulil Albab Pascal: Journal of Computer Science and Informatics Journal of Computer Science Artificial Intelligence and Communications Jurnal Ilmu Komputer dan Teknik Informatika Jurnal Pengabdian Masyarakat Berdampak
Rusmin Saragih, Rusmin
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Implementation of YOLOv8 for Object Detection in Urban Traffic Surveillance A Case Study on Vehicles and Pedestrians from CCTV Imagery Saragih, Rusmin; Imeldawaty Gultom; Frans Ikorasaki; Theodora MV Nainggolan
Journal of ICT Applications System Vol 4 No 1 (2025): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jictas.v4i1.430

Abstract

Implementation of the YOLOv8 object detection algorithm for enhancing traffic surveillance through accurate identification of multiple road entities, including cars, motorcycles, trucks, and pedestrians. Using a 41-second CCTV video as the primary dataset, the research adopts a deep learning-based training approach via Google Colab to evaluate YOLOv8's performance under real-world urban conditions. The detection model was assessed using key evaluation metrics such as accuracy, precision, recall, and Mean Average Precision (mAP). The experimental results demonstrate that YOLOv8 achieves an overall detection accuracy of 80%, showing reliable performance in identifying vehicles and people despite challenges such as occlusions, varied lighting, and complex backgrounds. However, accuracy variations were observed in cases involving partial visibility and non-optimal camera angles. The findings highlight the potential of YOLOv8 as a robust and scalable solution for real-time traffic object detection, with implications for smart city development and automated traffic management systems. Further improvements are recommended in dataset diversity and model fine-tuning to enhance detection robustness across dynamic traffic scenarios
Pelatihan Peningkatan Kompetensi Guru dalam Penggunaan Canva untuk Pembelajaran Berdiferensiasi pada Kurikulum Merdeka Gultom, Imeldawaty; Saragih, Rusmin; Pakpahan, Emma Martina
Pengabdian Pendidikan Indonesia Vol. 2 No. 01 (2024): Artikel Periode April 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ppi.v2i01.4528

Abstract

Pelatihan peningkatan kompetensi guru dalam penggunaan Canva untuk pembelajaran berdiferensiasi di SMP Swasta Primbana Medan bertujuan untuk memperkuat keterampilan guru dalam memanfaatkan teknologi untuk mendukung implementasi Kurikulum Merdeka. Kegiatan ini berangkat dari kebutuhan untuk meningkatkan kualitas materi pembelajaran dan keterlibatan siswa melalui penggunaan alat digital yang inovatif. Pelatihan ini melibatkan sesi teori dan praktik yang dirancang untuk mengenalkan fitur Canva dan aplikasinya dalam pembuatan materi ajar yang visual dan interaktif. Metodologi yang digunakan dalam pelatihan ini mencakup pendekatan kualitatif dan kuantitatif. Data dikumpulkan melalui wawancara, kuesioner, observasi, dan analisis dokumen untuk menilai peningkatan keterampilan guru dan kualitas materi pembelajaran yang dihasilkan. Hasil dari pelatihan menunjukkan peningkatan signifikan dalam keterampilan guru dalam menggunakan Canva, yang berdampak positif pada kualitas materi pembelajaran. Guru-guru di SMP Swasta Primbana Medan kini dapat menciptakan materi yang lebih menarik dan sesuai dengan kebutuhan siswa, yang pada gilirannya meningkatkan keterlibatan dan motivasi siswa. Pelatihan ini juga berhasil membentuk komunitas belajar di kalangan guru, di mana mereka saling berbagi pengetahuan dan pengalaman dalam penggunaan Canva. Temuan ini menunjukkan bahwa integrasi teknologi seperti Canva dapat mendukung pembelajaran berdiferensiasi dan pelaksanaan Kurikulum Merdeka dengan lebih efektif. Rencana tindak lanjut meliputi pendampingan berkelanjutan dan pengembangan modul pelatihan tambahan untuk memperkuat kemampuan guru dalam memanfaatkan teknologi pendidikan.
A Narrative Exploring the Potential of ChatGPT: How AI Models Are Changing the Way We Interact with Technology Eka, Muhammad; Asih, Munjiat Setiani; Damayanti, Fera; Saragih, Rusmin; Supiyandi, Supiyandi
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.5

Abstract

This study explores the perceptions, attitudes, and ethical considerations surrounding the use of ChatGPT among university students. By combining quantitative and qualitative research methods, including surveys and a review of existing literature, the study examines how ChatGPT is utilized in academic settings and its impact on learning outcomes, academic integrity, and scholarly achievements. The findings suggest that ChatGPT significantly enhances students' productivity, learning experiences, and writing abilities. However, concerns regarding its potential misuse, particularly about academic integrity, plagiarism, and over-reliance on AI tools, were also identified. The research highlights the importance of establishing clear ethical guidelines and policies to regulate the use of AI in educational settings. Future research should focus on the long-term effects of ChatGPT on students' academic development and investigate strategies for promoting responsible AI usage in higher education.
Sentiment Analysis of Social Media Towards Public Services Using Naive Bayes and Text Mining Rusmin Saragih; Mardiah; Deni Apriadi
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.18

Abstract

The rapid development of information and communication technology has driven the increased use of social media as a means of interaction between the public and service providers. Social media has become a platform for the public to express their opinions on the quality of services they receive, whether in the form of praise, suggestions, or complaints. Therefore, sentiment analysis of social media data can be a strategic tool in evaluating the performance of public services. This research aims to analyze public sentiment towards public services by utilizing text mining techniques and the Naive Bayes Classifier algorithm. The data used was collected from social media platforms such as Twitter and Facebook, followed by a text preprocessing stage that included tokenizing, stopword removal, and stemming. Subsequently, the data was analyzed to classify sentiment into positive, negative, and neutral categories. The test results show that the Naive Bayes algorithm is capable of classifying data with a satisfactory level of accuracy, making it an efficient method for monitoring public perception in real-time. This research contributes to supporting decision-making by government agencies regarding the improvement of public service quality based on publicly available feedback from social media
The Use of Knowledge Management Systems to Improve Decision-Making in Local Government Saragih, Rusmin; Lestari, Yuyun Dwi; Lubis, Yessi Fitri Annisah; Handoko, Divi
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 1 (2025): May 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i1.22

Abstract

Effective and data-driven decision-making has become an urgent need for local governments in facing the challenges of public service complexity, socio-economic dynamics, and demands for transparency and accountability. One of the strategic approaches to support this process is through the implementation of a Knowledge Management System (KMS). This research aims to explore the role and impact of KMS implementation on the improvement of decision-making quality in regional government organizations. A qualitative approach is used in this study with a case study method on several regional government agencies in Indonesia that have implemented KMS, combined with an analysis of related academic literature. Research results show that KMS is capable of improving the efficiency of storage, distribution, and access to organizational knowledge, both tacit and explicit. KMS supports faster, more accurate, and participatory decision-making because strategic information can be obtained and used promptly by policymakers. The findings also indicate that the success of KMS implementation is greatly influenced by organizational culture, leadership support, and the capacity of human resources in managing and sharing knowledge. This study recommends the comprehensive integration of KMS into the government work system, with an emphasis on training aspects, digital infrastructure, and internal policies that support the knowledge-sharing process. The theoretical and practical implications of these findings are an important contribution to the development of knowledge-based governance at the regional level.
Data Mining Pengelompokan Akta Nikah Berdasarkan Usia Nikah atau Domisili Menggunakan Metode Clustering: Studi Kasus  Kemenag Langkat Nurlaila, Nurlaila; Buaton, Relita; Saragih, Rusmin
Sci-tech Journal Vol. 2 No. 1 (2023): Sci-tech Journal (STJ)
Publisher : MES Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (921.437 KB) | DOI: 10.56709/stj.v2i1.62

Abstract

One way to find out the marriage certificate data is to group the prospective bride and groom data that has been recorded at the Langkat Ministry of Religion. The analysis was carried out using the Clustering method using the K-Means method which was translated into a software. This software is used for grouping data. The output is to find out the grouping of marriage certificate data with the closest relationship between the age group of the groom, occupation and address. The results showed that the age of the groom-to-be between 19-28 years old had a civil servant job at the address/district of Kutambaru. Keywords: age, occupation, address/location and clustering
Diagnosa Penyakit Hisprung pada Bayi menggunakan Metode Dempster Shafer Nadia Nurhafiza; Rusmin Saragih; Melda Pita Uli Sitompul
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 6 (2025): November: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i6.1140

Abstract

Hirschsprung’s disease is a congenital disorder caused by abnormal nerve cell development in the large intestine, leading to chronic intestinal obstruction in infants. This condition often manifests through symptoms such as constipation, abdominal distension, vomiting, and failure to thrive. The weak immune system of infants makes them highly susceptible to bacterial infections and further complications. At Bidadari General Hospital, there were 110 patients suspected of having Hirschsprung’s disease. One of the major challenges in managing these cases is the limited number of medical specialists, particularly pediatricians and pediatric surgeons, resulting in long waiting times for accurate diagnosis, especially during peak service hours. To address this issue, this study applies the Dempster-Shafer method in an expert system to assist in diagnosing Hirschsprung’s disease based on clinical symptoms. The method effectively handles uncertainty and combines multiple pieces of medical evidence to produce more accurate diagnostic probabilities. The analysis results show that from the selected symptoms, the highest diagnosis probability corresponds to short-segment Hirschsprung’s disease with a confidence level of 71.54%. These findings suggest that the Dempster-Shafer method can serve as an effective alternative tool to support early and accurate diagnosis of Hirschsprung’s disease in infants.
Implementation of Mechine Learning Eligibility for Customer Credit Payments at Bank BTN Using the K – Nearst Neighbor Algorithm Sari Suwandi, Ema; Buaton, Relita; Saragih, Rusmin
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.246

Abstract

Credit is the provision of money or bills that can be equated with that, based on a loan agreement or agreement between a bank and another party that requires the borrower to pay off the debt after a certain period of time with interest (Government of Indonesia, 1998). In its initial development, credit had a function in stimulating mutual assistance aimed at meeting needs, both in the field of business and meeting daily needs.In developing applications, it is necessary to predict applications at Bank BTN Medan accurately, accurate prediction results are very important in showing the right rating and decision-making in selecting customers. When customers experience arrears, the system used by Bank BTN Medan is still manual and has not applied predication in credit arrears to customers of Bank BTN Medan. Tests carried out in this test use a credit customer dataset from Bank BTN Medan. This study predicts the eligibility of customer credit payments at Bank BTN with the K – Nearst neighbor algorithm. The prediction of the level of smoothness of credit payments is made using K-Nearest Neighbor in order to be able to predict the smoothness of future credit payments.
Clustering Disease on Settlements Inhabitant In place seedy With Use Clustering Method Sitepu, Ruine Buana Br; Achmad Fauzi; Saragih, Rusmin
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.275

Abstract

Residents living in slum areas often face serious problems related to public health, where the prevalence of disease tends to be high and its spread is difficult to control. The impact of the formation of slums for the community is that safety is threatened, health deteriorates, and social conditions worsen, causing many diseases for people living in slums. Therefore, this study aims to identify patterns and clusters of diseases that exist in residential areas in slums Binjai city using clustering method. The K-Means Algorithm clustering method was chosen because it is able to group data based on similar characteristics, so that it can help identify diseases in a more focused and efficient manner, using the MATLAB application is also very appropriate in this problem so that it can produce output from data mining that can be used in decision making. future decisions. By utilizing the data mining process using the clustering method, clustering can be a problem of grouping diseases in slum settlements. Based on the results of trials with 20 sample data conducted with MATLAB obtained in cluster 1 DHF cases with high slums, Cluster 2 cases of vomiting with moderate slums and cluster 3 cases of diarrhea with moderate slums. The results of this study are expected to provide in-depth insight into disease patterns and clusters in residential areas in slums.
Expert System To Determine Psychological Disorders In Chronic Kidney Failure (CKD) Patients Undergoing Hemodialysis Therapy Using Certainty Factor Method SELVY ANGGRAINI, SELVY; Saragih, Rusmin; Khair, Husnul
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.280

Abstract

Chronic Kidney Failure (CKD) is damage to the kidneys both in structure and/or function that lasts for 3 months or more. Hemodialysis is a prolonged therapy that can significantly impact the physical and psychological well-being of patients with chronic kidney disease. This therapy has a big effect on sufferers. The psychological impact that appears can affect the success of therapy so it is important to recognize these symptoms and provide appropriate treatment to overcome them. Based on research at Delia General Hospital, patients who will undergo Hemodialysis therapy must come to the hospital to receive comprehensive therapy by a doctor. Long patient queues when undergoing therapy can make patients tired and remember the patient's condition in order to get information and therapy. Handling of these problems can be overcome by building a system that can determine psychological disorders in patients. Expert systems are computer-based systems that use knowledge, facts and reasoning techniques in solving problems that usually can only be solved by an expert in a particular field. Certainty Factor (CF) is a method capable of defining the degree of certainty of a rule or fact in describing an expert's belief in the problem at hand. With an expert system, it can help identify and determine early on psychological disorders in patients. From the results of trials conducted by expert systems to determine psychological disorders in patients with kidney failure using the Certainty Factor method, the highest value is depression with a percentage of 94.59%.
Co-Authors , Eka Putra Abdul Azan Abdul Azan Abdullah Hamid, Abdullah Abdullah Husein Achmad Fauzi ACHMAD FAUZI Alfina Damayanti Ambarita, Indah Andini Andini Andre Adrian Andrean Samuel Siahaan Aprilianda, Dinda Arianta Bangun Arnes Sembiring Asih, Munjiat Setiani Barany Fachri Boyke Gunawan Manurung Br Sitepu, Dinda Isabella Buaton, Relita Chairul Rizal Charles Jhony Mantho Sianturi, Charles Jhony Mantho Cindy Primadona Siahaan Damayanti, Fera Dandi Satria R Deni Apriadi Dewantara, Nowell Dimas Prayogi Dinda Firdawati Simamora Divi Handoko Eka Pandu Cynthia Eka, Muhammad Fany Juliawati Fatimah Fatmaira, Zira Fauzi, Achmad frans ikorasaki Fuzy Yustika Manik Fuzy Yustika Manik, Fuzy Yustika Gea, Fide Evianti Ginting, Darmawan Gultom, Imeldawaty Handoko, Divi Herdiansyah Harahap Herdiansyah Harahap Hesty Vitara I Gusti Prahmana Ikhsan Arif Indra Prasetia, Indra Irfan Yusuf Ismi Asmita Jesayas Sembiring Khair, Husnul Khalidy, Furqan Lestari, Yuyun Dwi Lili Musarofah Lili Musarofah Loo, Petrus Magdalena Simanjuntak Magdalena Simanjuntak Magdalena Simanjuntak Mardiah Marto Sihombing Marto Sihombing Meisaroh Melda Pita Uli Sitompul Mhd Ferdiansyah Putra Mili Alfhi Syari Muhammad Danil Syahputra Muhammad Danil Syahputra Muhammad Eka Muhammad Eka Muhammad Noor Hasan Siregar Muhammad Reza Habibi Muhammad Zen, Muhammad Munadi Munadi Nadia Nurhafiza Nasril Hidayat Nico Kurniawan Purba Nikous Soter Sihombing Novriyenni Novriyenni Novriyenni Novriyenni, Novriyenni Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurlaila Nurlaila Nurlaila Nurlaila Nuryahati - Pakpahan, emma martina Pakpahan, Victor Maruli Pardede, Akim Manaor Hara Pasaribu, Tioria Rafli Fitriawan Rahayu Utami Rahmadani Rahmadani Rahmawati Rahmawati, Rahmawati Raihan, Muhammad Ramadani, Suci Ramli Ramli Ramos Parulian Ambarita Ratih Puspadini Rianty Zabitha Siregar Ricky Ramadhan Harahap Rizki Kurniawan Ryan Hidayat Sari Suwandi, Ema Saripurna, Darjat Satria R, Dandi SELVY ANGGRAINI, SELVY Sihombing, Anton Sihombing, Marto Simanjuntak, Magdalena Sinaga, Ayu Puspita Sari Sirait, Win Gomgom Parsaulian Siswan Syahputra Sitepu, Ruine Buana Br SITORUS, ERBIN Sonadi Perangin Angin Suci Pratiwi, Kiki Supiyandi Supiyandi Syahputra, Siswan Syari, Milli Alfhi Tantia Azzahra Tata Mustika Dewi tata, tatamustikadewi Theodora MV Nainggolan Ulandari, Seri Wati, Sri Kesuma Yani Maulita Yekolya Anatesya Yessi Fitri Annisah Lubis Yulia Ningsih Yusuf Afani Yuyun Dwi Lestari