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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) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi 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) Jurnal Teknik Indonesia (JU-TI) "Journal of Data Science Journal Majelis Paspama
Hasugian , Paska Marto
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Testing the C45 Algorithm with Rapid Miner for Stock Selection (Case Study: Toko Usaha Muda) Hasugian, Paska Marto
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.
Development of distance formulation for high-dimensional data visualization in multidimensional scaling Marto Hasugian, Paska; Mawengkang, Herman; Sihombing, Poltak; Efendi, Syahril
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8738

Abstract

This research aims to produce a new method called pasca-multidimensional scaling (pasca-MDS) by modifying the multidimensional scaling (MDS) method, the developed model comes as a solution to overcome the problem of data complexity by reducing its description dimension without losing important information. This model, offers an innovative approach in dealing with these problems. Pasca-MDS not only focuses on reducing the dimensionality of data, but also retains the essence of relevant information from each data point. As such, it allows for easier and more efficient analysis without compromising the accuracy of the information conveyed. The main advantage of pasca-MDS lies in its ability to produce simpler visual representations while maintaining the original structure of complex data. This provides clarity and ease in understanding the patterns or relationships hidden within. By using adjustment techniques after the MDS process, this model can provide more optimized results. This process allows the adjustment of data points to achieve a better representation in a lower dimensional space, resulting in a more intuitive and easy-to-understand interpretation. The developed distance formula has the ability to minimize stress compared to other distance formulas in MDS space, with the aim of improving the accuracy of high-dimensional data visualization.
Information Technology Resource Framework Hasugian, Paska Marto
Journal Majelis Paspama Vol. 2 No. 01 (2024): Journal Majelis Paspama, January 2024
Publisher : Journal Majelis Paspama

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Abstract

This research is a literature review that aims to investigate and analyze concepts and frameworks related to information technology resources. Through a literature review approach, this research collects, organizes, and analyzes previous research that has been conducted in this area. The main focus of this research is to gain an understanding of the role, components, and characteristics of the Information Technology Resource framework, as well as its impact on company performance. The method used in this research involved the search and selection of relevant scholarly articles, journals, and publications relating to the topic. After a careful selection process, literature studies that met the inclusion criteria were analyzed in detail, and important relevant information was retrieved for further analysis. The results of this literature review present various existing frameworks in the information technology resources domain. These frameworks cover important aspects such as information technology resource management, integration of information technology in business strategy, information technology performance measurement, and development of information technology competencies in organizations. In this context, this study identifies key concepts, theoretical perspectives, and recent trends in the development of information technology resource frameworks.
Performance of K-Means Algorithm for Ground Acceleration Clustering Siska Simamora; Amran Manalu; Paska Marto Hasugian
Journal Majelis Paspama Vol. 2 No. 2 (2024): Journal Majelis Paspama, July 2024
Publisher : Journal Majelis Paspama

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Abstract

Indonesia is one of the most seismically active regions in the world due to the convergence of the Indo-Australian, Eurasian, and Pacific tectonic plates. This condition exposes the country to frequent earthquakes with varying magnitudes and intensities that may cause severe structural damage and pose risks to human safety. Ground acceleration, particularly Peak Ground Acceleration (PGA), is a key parameter for evaluating earthquake impacts and is strongly influenced by geological conditions, hypocentral depth, and epicentral distance. However, the complexity and large volume of ground acceleration data often hinder manual interpretation. This study applies the K-Means clustering algorithm to classify ground acceleration data obtained from seismic records at several observation points. Prior to clustering, data preprocessing was performed through data cleaning and min–max normalization to ensure quality and comparability across variables. The optimal number of clusters was determined using the Elbow method and Silhouette Score. The results reveal distinct distribution patterns of ground acceleration, which are closely related to local seismic conditions. These findings are expected to contribute to the development of preliminary ground acceleration zonation, providing valuable insights for earthquake hazard mapping and risk mitigation efforts in Indonesia.
Analysis of Mango Leaf Condition Using the C-Means Method Based on Streaming Data Sinaga, Cinthya Agatha; Nainggolan, Herlina Br; Hasugian, Paska Marto
Journal Of Data Science Vol. 3 No. 02 (2025): Journal Of Data Science, September 2025
Publisher : Sean Institute

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Abstract

Efficiency in the agricultural sector is often hampered by conventional and manual plant identification processes. This study implements an automatic mango leaf condition evaluation system capable of live data acquisition, contour-based autocropping, and classification using the C-Means algorithm in a data streaming environment. The system extracts key features such as color (RGB), saturation, and contrast. Numerical data is normalized using Z-Score transformation before being grouped into three categories: Fresh, Sick, and Dry. The results show that the system is able to effectively distinguish biological conditions through automatic mapping. This research provides a responsive solution for real-time plant health monitoring.
Evaluation of Orange Fruit Quality Clustering Using a Real-Time X-Means Algorithm Maria Clodia Purba; Nainggolan, Emma Romasta Naulina; Hasugian, Paska Marto
Jurnal Teknik Indonesia Vol. 5 No. 01 (2026): Jurnal Teknik Indonesia (JU-TI) 2026
Publisher : SEAN Institute

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Abstract

The citrus farming industry faces major challenges in maintaining product quality consistency due to subjective manual sorting processes that are prone to fatigue and have varying standards. This problem results in economic losses due to errors in detecting ripeness levels and physical damage that hinders market competitiveness. This study aims to design and implement an automated citrus fruit quality evaluation system using a real-time X-Means algorithm. The research method begins with visual data acquisition through a camera sensor using the automatic snapshot feature to convert physical objects into digital data. The data then undergoes preprocessing, which includes filtering to remove noise, color (RGB) and texture feature extraction, and normalization using Min-Max Scaling to balance parameter weights. The X-Means algorithm is used because of its ability to independently determine the optimal number of clusters through the evaluation of the Bayesian Information Criterion (BIC) score. The processing results show that the system is able to accurately group oranges into three categories: ripe, which are dominated by bright orange colors; unripe, which are dominated by green colors; and rotten, which are identified through rough textures and dull colors. The integration of this technology ensures that all decision-making occurs quickly and objectively, providing a practical solution for the industry to consistently improve product quality control efficiency in the field.
Real-Time Landmark-Based Face Analysis for Expression and Gender Classification Nababan, Widia Wuduri C.S; Butarbutar, Della Novita; Hasugian, Paska Marto
Journal Majelis Paspama Vol. 4 No. 01 (2026): Journal Majelis Paspama, 2026
Publisher : Journal Majelis Paspama

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Abstract

This research developed a web-based real-time facial analysis system to overcome the challenge of detection accuracy in dynamic video streaming data. Using the face-api.js library with the Tiny Face Detector algorithm and a 68-point landmark model, the system is capable of simultaneously detecting faces, classifying gender, and recognizing seven basic emotional expressions. The main innovation of this system lies in the automatic extraction of five Regions of Interest (ROI) eyes, eyebrows, nose, mouth, and jaw and the presentation of confidence score data in the form of a time series graph. All analysis results are stored in a structured JSON dataset format for further research needs. The implementation results show high performance with an average confidence value above 90% in frontal face conditions and optimal lighting. The system has been proven to maintain detection stability up to a 30 degree face tilt angle and process data without significant latency. Although low light intensity can reduce the confidence value by 15-20%, this architecture proves the effectiveness of complex facial analysis using minimal hardware resources.
ANALISIS KINERJA ALGORITMA RSA PADA ENKRIPSI CITRA DIGITAL BERDASARKAN PARAMETER PSNR DAN MSE Jamaluddin; Manalu, Darwis Robinson; Hasugian, Paska Marto; Simamora, Roni Jhonson
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 12 No. 1 (2026): Volume 12 Nomor 1 Tahun 2026
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v12i1.5420

Abstract

Digital image security is an important issue in this era of increasingly massive multimedia-based data exchange, especially for sensitive information that requires a high level of protection. This study aims to analyze the performance of the Rivest Shamir Adleman (RSA) asymmetric cryptography algorithm in the digital image encryption process based on the Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) parameters, as well as encryption and decryption times. The method used is a quantitative experiment on 30 digital images with varying resolutions (256×256, 512×512, and 1024×1024 pixels) and two RSA key lengths (1024-bit and 2048-bit). The test results show that the MSE value ranges from 0.001068 to 0.002620 and the PSNR value ranges from 75.08 to 78.34 dB, indicating that the decrypted images are of very high quality and close to the original images. However, the computation time increased significantly with increasing resolution and key length, with RSA 2048-bit taking almost twice as long as RSA 1024-bit. These findings show that the RSA algorithm is very effective in maintaining the integrity of digital images, but has limitations in terms of computational time efficiency, especially for high-resolution images. Therefore, a balance between security and performance is needed in practical implementation.
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