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Pendampingan Teknis Laboratorium Komputer dalam mendukung Pelaksanaan UTBK PPG di Universitas Katolik Santo Thomas Medan Sipayung, Sardo Pardingotan; Hasugian, Paska Marto; Limbong, Tonni; Batubara, Muhammad Iqbal; Siagian, Novriadi Antonius
ULEAD : Jurnal E-Pengabdian Volume 5 Nomor 1 Juli 2025
Publisher : Fakultas Ilmu Komputer, Universitas Katolik Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/ulead.v5i1.5117

Abstract

Kegiatan ini bertujuan untuk meningkatkan kesiapan laboratorium komputer Fakultas Ilmu Komputer Universitas Katolik Santo Thomas dalam mendukung pelaksanaan UTBK PPG. Permasalahan utama yang dihadapi meliputi keterbatasan perangkat, jaringan yang belum optimal, serta minimnya kompetensi teknis tenaga laboran. Metode yang digunakan mencakup survei awal, pelatihan teknis, simulasi UTBK, optimalisasi perangkat dan jaringan, serta penyusunan SOP. Hasil kegiatan menunjukkan peningkatan signifikan pada aspek kesiapan perangkat, kemampuan tenaga teknis, dan kelancaran sistem saat simulasi. Kegiatan ini menghasilkan laboratorium yang lebih siap, SDM yang terlatih, serta SOP standar untuk pelaksanaan UTBK. Pendampingan teknis terbukti efektif dalam meningkatkan dukungan infrastruktur asesmen berbasis komputer di perguruan tinggi.
Testing the C45 Algorithm with Rapid Miner for Stock Selection (Case Study: Toko Usaha Muda) Paska Marto Hasugian
Journal Of Data Science Vol. 1 No. 02 (2023): Journal Of Data Science, September 2023
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/jds.v1i02.2836

Abstract

One of the keys to the success of a retail company is good stock management. Intuition-based methods are often not enough because customer demands are always changing. This research concentrates on the use of the C4.5 decision tree algorithm on the RapidMiner platform to optimize the selection of goods in the Toko Usaha Muda. This algorithm is used to predict future stock requirements by looking at previous sales patterns in stores and historical sales data. The results show a significant increase in the accuracy of stock predictions and a decrease in the probability of loss due to excess or stockouts. This implementation not only enhances the operations of the Toko Usaha Muda, but also provides a framework that other retail businesses can use to increase their profits through better stock management.
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), Agustus 2025
Publisher : SEAN Institute

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

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.
Co-Authors Agustinus Parmazatule Laia 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 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 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 Muhammad Iqbal Nababan, Adli Abdillah NASUTION, ATIKA AINI Ndruru, Risnamawati Nera Mayana Br.Tarigan Nico Setiawan Nurayni Sinabang Pandi Barita Nauli Simangunsung Panggabean, Yusi Tri Utari Penda Sudarto Hasugian Penda Sudarto Hasugian Prawita Ardella R. Mahdalena Simanjorang Rahmat Ferdiansyah Riana Risnamawati Ndruru Ritha Zahara Tarigan Rizki Manullang Romanus Damanik Romauli Sianipar Safa Ayoub Al Hashim 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 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