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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
Integration Of Pca And K-Means Clustering For Staple Food Segmentation In Support Of National Food Policy Sipayung, Sardo; Hasugian, Paska Marto
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15343

Abstract

This study aims to develop cross-provincial staple-food segmentation by integrating Principal Component Analysis (PCA) and K-Means to support policy formation. The dataset comprises 2023 staple-food consumption for 34 Indonesian provinces across six indicators from BPS/SUSENAS. All indicators were standardized using z-score, reduced via PCA, and the resulting component scores were used as inputs to K-Means. Three components (PC1–PC3) explained 73.86% of the variance and captured shifts between sweet/animal-based vs. plant foods, fatty or animal-based grains, and the energy contribution of fat. The optimal number of clusters was determined as k = 3, yielding Silhouette = 0.466 and DBI = 0.733, indicating sufficiently compact and well-separated groups. The results reveal three segments: the first group consists of 11 provinces that are predominantly plant-based with low sugar and low animal-based consumption; the second group includes 13 provinces characterized by high animal-based and high-fat consumption; and the third group comprises 10 provinces with low-fat diets and fresh plant-based consumption. Stability checks on initialization and a leave-one-feature-out procedure confirmed consistent assignments. This fills an empirical gap: to our knowledge, no prior research integrates PCA with K-Means for cross-provincial staple-food segmentation in Indonesia while also reporting internal validation. Practically, the study provides operational segmentation to support food-security interventions moving beyond composite indices toward actionable targeting for production support, supply/price stabilization, and improved nutritional access thereby reframing IKP/FSVA from index-ranking to evidence-based segmentation.
Co-Authors Agustinus Parmazatule Laia Al Hashim, Safa Ayoub Alex Rikki Amran Manalu Angelia M Manurung Anju Eliarsyam Lubis Annas Prasetio Arvind Roy Baehaqi Batubara, Muhammad Iqbal Betti Mastaria Br Sembiring Bobby Aris Sandy Bosker Sinaga Bosker Sinaga, Bosker Sinaga Br Ginting, Anirma Kandida Br Sembiring, Betti Mastaria Butarbutar, Della Novita Cinthya Agatha Sinaga Damianus Daha Darwis Robinson Manalu 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 Jamaluddin 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 Maria Clodia Purba Martinus Giawa Maya Theresia Br. Barus MIFTAHUL JANNAH Nababan, Adli Abdillah Nababan, Widia Wuduri C.S Nainggolan, Emma Romasta Naulina Nainggolan, Herlina Br 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, Cinthya Agatha 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