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All Journal Bulletin of Electrical Engineering and Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research Jurnal Mantik Penusa Cetta: Jurnal Ilmu Pendidikan Jurnal Teknik Informatika UNIKA Santo Thomas JIPN (Journal of Informatics Pelita Nusantara) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sains dan Teknologi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) INFOKUM JUKI : Jurnal Komputer dan Informatika BERNAS: Jurnal Pengabdian Kepada Masyarakat Login : Jurnal Teknologi Komputer MEANS (Media Informasi Analisa dan Sistem) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Media Informatika Jurnal Info Sains : Informatika dan Sains DISTANCE: Journal of Data Science, Technology, and Computer Science Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Ulead : Jurnal E-pengabdian Jurnal Pendidikan LLDIKTI Wilayah I (JUDIK) Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Jurnal Komputer Indonesia (JU-KOMI) Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN) "Journal of Data Science Journal Majelis Paspama
Hasugian , Paska Marto
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Comparison and Evaluation of Euclidean Distance and Dice Distance in the K-Means Adaptive Algorithm for Clustering Composite Indexes of Food Security and Vulnerability Maps Emma Romasta Naulina Nainggolan; Paska Marto Hasugian
Journal Of Data Science Vol. 3 No. 02 (2025): Journal Of Data Science, September 2025
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/jds.v3i2.6941

Abstract

This study aims to compare and evaluate the effectiveness of two distance measurement methods, namely Euclidean Distance and Dice Distance, in the K-Means Adaptive algorithm for clustering Food Security and Vulnerability Composite Index data. The dataset used includes index data from 2022 to 2024, comprising 305 entries, which were then cleaned to 298 entries. The evaluation was conducted manually using a sample dataset and automatically using the entire dataset via Google Colab with Python. The algorithm's performance was assessed using the Silhouette Score metric to measure the quality of the resulting clusters. The evaluation results showed that the Euclidean method produced an average Silhouette Score of 0.3082, indicating an suboptimal cluster structure. This study concludes that the choice of distance method significantly influences clustering results, and selection should be tailored to the characteristics of the data.
Ground Acceleration Clustering Using Self-Organizing Map Method Siska Simamora; Amran Manalu; Paska Marto Hasugian
Journal Of Data Science Vol. 3 No. 02 (2025): Journal Of Data Science, September 2025
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/jds.v3i2.7281

Abstract

Peak Ground Acceleration (PGA) is an important parameter in seismic studies because it is directly related to the level of shaking felt on the earth's surface. Analysis of ground acceleration data is needed to identify patterns, group regions based on their seismic characteristics, and support earthquake disaster mitigation efforts. This study uses the Self-Organizing Map (SOM) method, which is an unsupervised learning approach based on artificial neural networks that can map high-dimensional data into a two-dimensional map representation without losing its topological structure. The ground acceleration dataset used in this study consists of key seismic parameters such as depth, magnitude, source distance, and PGA values. The SOM learning process is carried out iteratively to produce a cluster map that groups earthquake data into several groups with different ground acceleration characteristics. The results show that the SOM method is able to identify ground acceleration distribution patterns more clearly than conventional methods, by producing clusters that represent variations in PGA from low to high. These findings can provide important contributions to earthquake risk mapping, regional spatial planning, and the formulation of more accurate disaster mitigation strategies.
Comparison and Evaluation of Euclidean and Canberra Distances in the Adaptive K-Means Algorithm for Classifying the Food Security Status of Indonesian Provinces Cinthya Agatha Sinaga; Paska Marto Hasugian
Jurnal Komputer Indonesia (Ju-Komi) Vol. 3 No. 02 (2025): Jurnal Komputer Indonesia (JU-KOMI), April 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/ju-komi.v3i02.752

Abstract

Food security issues in Indonesia are a major concern because they affect the sustainability of people's livelihoods and regional disparities. This study was conducted to classify food security conditions between provinces based on two main indicators, namely the Food Security Index and the Percentage of Adequate Food Consumption. The method used is the K-Means Adaptive algorithm with a comparison of two types of distance measurements, namely Euclidean and Canberra. The selection of centroids is done gradually using a probabilistic approach to improve the stability of the clustering results. Before conducting a comprehensive test, the method is first tested using sample data to see the characteristics of each distance function. Subsequently, all data were analyzed using Python programming, and the results were evaluated using the Silhouette Score metric. The analysis results showed that the Canberra distance function provided better clustering quality than the Euclidean function with a value of 0.415. This approach is expected to serve as a reference for more accurate and informative regional-based food security analysis.
DEVELOPMENT OF A FACE RECOGNITION AND GEOFENCING BASED ATTENDANCE INFORMATION SYSTEM USING THE PROTOTYPING METHOD Situmorang, Caesar Juanda Theodorus; Hasugian, Paska Marto
Jurnal Komputer Indonesia (Ju-Komi) Vol. 4 No. 01 (2025): Jurnal Komputer Indonesia (JU-KOMI), October 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/ju-komi.v4i01.755

Abstract

An attendance information system is a crucial component in managing attendance in educational institutions and organizations. This research aims to develop an attendance system that integrates face recognition and geofencing technology to improve the accuracy and efficiency of the attendance recording process. Face recognition technology recognizes users' faces in real-time, while geofencing ensures users are within a designated area when taking attendance. The system development method used is prototyping, allowing the design process to be carried out iteratively by involving direct feedback from users. The results of this research are a mobile and web-based attendance information system that can automatically detect faces and locations, and store attendance data securely and structured. The developed system is expected to be an innovative solution in realizing a more modern, accurate, and reliable attendance process.
Development Of E-Learning using Moodle as Online Course Media on Private Sean Institute Hasugian, Paska Marto; Sijabat, Petti Indrayati
Login : Jurnal Teknologi Komputer Vol. 17 No. 02 (2023): Jurnal Teknologi Komputer, Edition Desember 2023
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/login.v17i02.29

Abstract

Today's technological developments have developed rapidly and have become an integral part of supporting the smooth running of activities or daily activities in government agencies, marketing, and even informal and non-formal education. The purpose of this research is to develop e-learning in support of online course activities given the current conditions during the pandemic, which resulted in activities being carried out from home or with the term Work From Home (WFH). From Leni Zuliana's research, she has researched the topic of analyzing the use of e-learning and found that there was a significant increase when using the media, with the calculation of the media expert's assessment being said to be very feasible with an overall average of 100% and the evaluation of material experts in every conceivable category. With an overall mean of 95.4%. This research aims to produce e-learning, which can be used as a medium for online course learning. Some of the work steps used to make e-learning are ensuring problems with the object under study, collecting data, developing applications, testing, and implementing media. The content on e-learning is created with several features, namely 1) uploading course material in a specific form, pdf, PowerPoint and video 2) making daily questions and assessing and returning answer papers 3) real-time video conference facilities with zoom or with supporting facilities and other supporting activities that can be included in e-learning.
Image Edge Detection for Batak Ulos Motif Recognition using Canny Operators Sitanggang, Sarinah; Hasugian, Paska Marto
Login : Jurnal Teknologi Komputer Vol. 18 No. 01 (2024): Jurnal Teknologi Komputer, Edition June 2024
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/login.v18i01.42

Abstract

Batak ulos is one of the handicrafts originating from North Sumatra. In Batak Ulos, there are various kinds of motifs that are characteristic of these ulos. One way to find out the type of ulos is by knowing the motives found on the ulos. For that we need a system that can detect ulos and then can recognize these ulos. The system was built using the canny edge detection method proposed by Jhon Canny in 1986, and is known as the optimal edge detection operator. Canny operator is one of edge detection which is very good in detecting image edges. Canny operators have met the criteria in detecting, namely detecting very well, responding well and localizing well and clearly. The system built also uses the C # programming language in Microsoft Visual Studio 2010.
Information Technology Resource Framework Hasugian, Paska Marto
Login : Jurnal Teknologi Komputer Vol. 18 No. 01 (2024): Jurnal Teknologi Komputer, Edition June 2024
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/login.v18i01.109

Abstract

This study is a literature review aimed at investigating and analyzing concepts and frameworks related to Information Technology Resource. Through a literature review approach, this research gathers, organizes, and analyzes previous studies conducted in this field. The main focus of this study is to gain an understanding of the roles, components, and characteristics of the Information Technology Resource framework, as well as its impact on company performance. The method used in this research involves searching and selecting relevant scientific articles, journals, and publications related to the topic. After a careful selection process, the literature studies that meet the inclusion criteria are analyzed in detail, and relevant essential information is extracted for further analysis. The results of this literature review present various frameworks within the domain of Information Technology Resource. These frameworks encompass crucial aspects such as managing information technology resources, integrating information technology into business strategies, measuring information technology performance, and developing information technology competencies within organizations. In this context, the research identifies key concepts, theoretical perspectives, and recent trends in the development of Information Technology Resource frameworks.
PENGENALAN ARTIFICIAL INTELLIGENCE (AI) UNTUK MENINGKATKAN LITERASI DIGITAL MASYARAKAT Siska Simamora; Paska Marto Hasugian
Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN) Vol. 3 No. 02 (2025): Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN), 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/abdimassean.v3i02.762

Abstract

Keterbatasan pemahaman dan pemanfaatan teknologi kecerdasan buatan (Artificial Intelligence/AI) menjadi salah satu faktor yang menghambat peningkatan kualitas publikasi di Lembaga Paspama Institute. Selama ini, proses penyusunan naskah, pengolahan data, dan penyuntingan artikel masih dilakukan secara konvensional, sehingga memerlukan waktu lama dan sering kali menghasilkan kualitas tulisan yang tidak konsisten. Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan literasi digital dan kemampuan praktis peserta dalam memanfaatkan teknologi AI guna memperbaiki efektivitas serta mutu publikasi ilmiah di lingkungan Paspama Institute. Metode pelaksanaan kegiatan dilakukan melalui pendekatan pelatihan dan pendampingan interaktif, meliputi tiga tahapan utama: (1) pengenalan konsep dasar AI dan potensinya dalam bidang publikasi, (2) workshop penerapan aplikasi AI seperti ChatGPT, Grammarly, dan Copilot untuk asistensi penulisan akademik, serta (3) pendampingan penyusunan artikel ilmiah berbasis AI secara etis dan bertanggung jawab. Hasil kegiatan menunjukkan peningkatan signifikan pada kemampuan peserta dalam menulis dan mengedit naskah, dengan nilai rata-rata post-test meningkat sebesar 32% dibandingkan pre-test. Selain itu, peserta menunjukkan peningkatan kepercayaan diri dalam menggunakan teknologi digital untuk kegiatan publikasi. Kegiatan ini berdampak positif terhadap penguatan kapasitas sumber daya manusia Paspama Institute dalam menghasilkan karya ilmiah yang lebih berkualitas, efisien, dan adaptif terhadap perkembangan teknologi digital.
PELATIHAN PEMBUATAN MEDIA PRESENTASI BAGI GURU-GURU SEKOLAH DASAR NEGERI 203 SIHOMBU KECAMATAN TARABINTANG Paska Marto Hasugian
Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN) Vol. 3 No. 02 (2025): Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN), 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/abdimassean.v3i02.765

Abstract

Guru memiliki peran penting dalam menciptakan pembelajaran yang menarik dan efektif, namun keterbatasan kemampuan dalam memanfaatkan teknologi sering menjadi kendala di sekolah-sekolah dasar, termasuk di SD Negeri 203 Sihombu. Guru-guru masih banyak yang menggunakan metode konvensional tanpa dukungan media digital, sehingga pembelajaran cenderung monoton dan kurang interaktif. Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan keterampilan guru dalam membuat media pembelajaran berbasis Microsoft PowerPoint yang menarik, interaktif, dan mudah dipahami oleh siswa. Metode pelaksanaan dilakukan melalui pelatihan dan pendampingan yang meliputi tahap pengenalan fitur PowerPoint, prinsip desain visual, pembuatan slide tematik, hingga penyisipan animasi dan multimedia. Evaluasi dilakukan melalui observasi langsung dan perbandingan hasil karya peserta sebelum dan sesudah pelatihan. Hasil kegiatan menunjukkan peningkatan kemampuan guru sebesar 85% dalam pembuatan media pembelajaran yang sesuai standar desain komunikasi visual. Selain itu, guru menunjukkan antusiasme tinggi dan mulai menerapkan hasil pelatihan dalam proses belajar mengajar di kelas. Kegiatan ini memberikan dampak positif berupa peningkatan kompetensi digital, kreativitas mengajar, serta motivasi guru untuk terus berinovasi dalam pembelajaran. Dengan demikian, pelatihan ini berkontribusi nyata terhadap peningkatan kualitas pendidikan di SD Negeri 203 Sihombu dan dapat dijadikan model kegiatan serupa di sekolah lainnya.
Best Cluster Optimization with Combination of K-Means Algorithm And Elbow Method Towards Rice Production Status Determination Hasugian, Paska Marto; Sinaga, Bosker; Manurung, Jonson; Al Hashim, Safa Ayoub
International Journal of Artificial Intelligence Research Vol 5, No 1 (2021): June 2021
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.292 KB) | DOI: 10.29099/ijair.v6i1.232

Abstract

Indonesia is the third-largest country in the world with rice production reaching 83,037,000 and became the highest production in southeast Asia spread in several provinces in Indonesia The problem found that such product has not been able to cover the needs of Indonesian people with a very high population so that in the research conducted information excavation to generate potential to the pile of data that has been described and analyzed by BPS with clustering topics. Clustering will help related parties, especially the ministry of agriculture, in determining land development priorities and can minimize the shortage of rice production nationally. Grouping process by involving the K-means algorithm to group rice production with a combination of the elbow method as part of determining the number of clusters that will be recommended with attributes supporting the area of harvest, productivity, and production. Method of researching with data cleaning activities, data integration, data transformation, and application of K-means with a combination of elbow and pattern evaluation. The results achieved based on the work description with a combination of K-Means and elbow provide cluster recommendations that are the best choice or the most optimal is iteration 2 which is the lowest rice production group with a total of 22 provinces, rice production with a medium category of 9 and production with the highest category with 3 regions
Co-Authors Agustinus Parmazatule Laia Al Hashim, Safa Ayoub Alex Rikki Amran Manalu Angelia M Manurung Anju Eliarsyam Lubis Annas Prasetio Arvind Roy Batubara, Muhammad Iqbal Betti Mastaria Br Sembiring Bobby Aris Sandy Bosker Sinaga Bosker Sinaga, Bosker Sinaga Br Ginting, Anirma Kandida Br Sembiring, Betti Mastaria Cinthya Agatha Sinaga Damianus Daha Devlin Iskandar Saragih Dewi Lasmiana Panjaitan Dharma Rajen Kartighaiyab Dharma Rajen Kartighaiyan Efendi, Syahril Emma Romasta Naulina Nainggolan Endang Utari Endra A.P Marpaung Fenius Halawa Ferdiansyah, Rahmat Fristi Riandari Fristy Riandari Giawa, Martinus Hanum, Rahmadiah Harefa, Ade May Luky Harpingka Sibarani Hasugian, Penda Sudarto Hengki Tamando Sihotang Herman Mawengkang Hidayati, Wenika Hutahaean, Harvei Desmon Hutahaean, Harvei Desmon Insan Taufik Ira Mayang Sari Jijon R. Sagala Jijon R. Sagala Jijon Raphita Sagala John Foster Marpaung Kristian Siregar Logaraj Logaraj Logaraj, Logaraj Logaraz Logaraz Lubis, Anju Eliarsyam Makmur Tarigan Manurung, Jonson Martinus Giawa Mathelinea, Devy Maya Theresia Br. Barus MIFTAHUL JANNAH Nababan, Adli Abdillah NASUTION, ATIKA AINI Ndruru, Risnamawati Nera Mayana Br.Tarigan Nico Setiawan Nurayni Sinabang Pandi Barita Nauli Simangunsung Penda Sudarto Hasugian Penda Sudarto Hasugian Poltak Sihombing Prawita Ardella R. Mahdalena Simanjorang Rahmat Ferdiansyah Riana Risnamawati Ndruru Ritha Zahara Tarigan Rizki Manullang Romanus Damanik Romauli Sianipar Sandy, Bobby Aris Sethu Ramen Sethu Ramen, Sethu Ramen Setiawan, Nico Siagian, Novriadi Antonius Sihotang, Jonhariono Sijabat, Petti Indrayati Simamora, Siska Simangunsong, Pandi Barita Nauli sinaga, lotar mateus Sinaga, Sony Bahagia Sinaga, Sony Bahagia Sinta Novianti, Sinta Sipayung, Sardo Sipayung, Sardo Pardingotan Siregar, Vanessa Sitanggang, Sarinah Situmorang, Caesar Juanda Theodorus Sri Wahyuni TONNI LIMBONG Uzitha Ram Vanessa Siregar Venentius Purba Vina Winda Sari Wenika Hidayati Widia Putri Yosapat Sembiring Yuda Perwira Yusi Tri Utari Panggabean