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Jurnal ICT : Information and Communication Technologies
Published by Marq & Cha Institute
ISSN : 20867867     EISSN : 28089170     DOI : https://doi.org/10.35335/jict
Core Subject : Economy, Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Mechanical Engineering
Jurnal ICT : Information and Communication Technologies (p-ISSN: 2086-7867) is a scientific journal and open access journal published by Pusat Penelitian Teknoligi, Marqcha Institute, Indonesia. Jurnal JICT covers the field of Informatics, Computer Science, Information Technology and Communication.It was firstly published in 2010 for a printed version. The aims of Jurnal JICT are to disseminate research results and to improve the productivity of scientific publications. Jurnal JICT is published two times a year (April and October).
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 61 Documents
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Decision Support System For Selection Of Drug Supplier With Weighted Product Method Sastra Wandi Nduru; Harmoko Lubis
Jurnal ICT : Information and Communication Technologies Vol. 13 No. 1 (2022): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (260.769 KB) | DOI: 10.35335/jict.v13i1.33

Abstract

Supplier data is seen from historical orders to suppliers about company addresses, prices, variants of drugs owned and drug quality, and supported by the Weighted Product method to support the decision of which supplier to choose to be a priority. The result of this research is a program to rank and determine supplier selection at GrandMed Hospital. The decision support system for determining supplier selection using the Weigthed Product method at GranMed Hospital has been able to be built using UML and made with the Visual Basic 2008 programming language
Decision Support System Of AMIK Medicom Promotion Strategy Determination Using AHP Method sutrisno situmorang; Jontinus Manullang
Jurnal ICT : Information and Communication Technologies Vol. 13 No. 1 (2022): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.367 KB) | DOI: 10.35335/jict.v13i1.34

Abstract

Every year, both public and private universities carry out campus promotion activities to introduce and find prospective new students. In carrying out this promotion, appropriate promotional media are needed such as: brochures, banners, football/volleyball, educational exhibitions, electronic media, through radio and social media, such as Facebook and Instagram. The main priority of the promotion is getting students according to the capacity that has been provided and getting students according to the promotion target. Therefore we need the right promotional media. In decision making, the researcher uses the AHP (Analytical Hierarchy Process) method. The AHP (Analytical Hierarchy Process) method is used to determine the weight of the criteria, the working principle of AHP is to simplify a complex problem that is structured, strategic, and dynamics into their parts and organize them in a hierarchy. Then the importance of all variables is given a subjective numerical value about the relative importance of these variables compared to other variables. The results of the assessment weights are two, namely feasible and not feasible.
Accounting Information System for Palm Production Results at Cost of Goods Sold at Ptpn IV (Persero) Medan Tarmika
Jurnal ICT : Information and Communication Technologies Vol. 13 No. 2 (2022): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.223 KB)

Abstract

PTPN IV is a State-Owned Enterprise (BUMN) engaged in the agro-industry business. PTPN IV (Persero) Medan manages plantations and manages palm oil commodities which includes managing areas and plants, gardens, seeds and maintenance of yielding plants, managing commodities into industrial raw materials. An accounting information system is a system that aims to collect and process data and report information related to financial transactions in a company. The important role of information systems in the business activities of a company is no longer in doubt. Supported by a good information system, a company will have a competitive advantage so that it can compete with other companies. The calculation of the cost of goods sold for palm oil production at PTPN IV (Persero) still uses a semi-computerized system so that errors often occur in calculating the cost of goods sold, a computerized system is needed so that transactions run well. This information system was built using the Visual Basic programming language and SQL Server as the database
Geographical Information System for Telkomsel Grapari Locations for Mkios in Medan City Suyanto Agus Irawan
Jurnal ICT : Information and Communication Technologies Vol. 13 No. 2 (2022): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (468.247 KB) | DOI: 10.35335/jict.v13i2.82

Abstract

Currently the information data about the location of Grapari Telkomsel for MKIOS in Medan City has not been inventoried in a spatial-based web information system, the mapping data for the location of Grapari Telkomsel for MKIOS are still using Microsoft Word and have not been programmed. For this reason, the authors created a solution with a Geographic Information System, which is an information system that is used to enter, process, and produce geographically or geospatially referenced data, to support decision making in a plan. In this final project, we created a Geographic Information System (GIS) for Processing Telkomsel Grapari Location Data for MKIOS in the Medan City Region. This information system will later have a visualization in the form of a web that is used to map the location of Grapari Telkomsel for MKIOS in the Medan City Region. In the development of the Telkomsel Grapari Regional Data Processing system for MKIOS in the Medan City Region, PHP and MySql programming languages ​​were used as database systems
Optimizing Convolutional Neural Networks for Cancer Biomarker Identification in Genomic Data: Challenges and Future Directions Lubis, Harmoko
Jurnal ICT : Information and Communication Technologies Vol. 14 No. 2 (2023): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v14i2.134

Abstract

Genomic analysis has become a major focus in cancer research to identify biomarkers that are important for more precise diagnosis and therapy. However, a major challenge in genomic analysis is the complexity and high dimensionality of genomic data, which requires sophisticated analysis approaches. This study aims to develop a deep learning model based on Convolutional Neural Networks (CNNs) that can recognize cancer biomarker patterns from genomic data with high accuracy. Relevant genomic data were collected and processed, then used to train CNNs models using optimization and regularization techniques. The CNNs model was then evaluated using validation data to measure its performance. The evaluation results show that although the model has improved in reducing the loss value, the accuracy obtained is still not optimal. The model is not fully able to identify cancer biomarker patterns accurately from the available genomic data. This research provides an important foundation for further development in genomic data analysis using deep learning. Suggestions for further research include the use of more representative data, optimization of model architecture, data augmentation, regularization, and external validation to improve model performance in cancer biomarker identification.
Development of Quantum Cryptography Algorithm for Data Security in Digital Communication System Prabukusuma, M. Azhar
Jurnal ICT : Information and Communication Technologies Vol. 14 No. 2 (2023): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

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

Abstract

Data security in digital communication systems is becoming increasingly important given the threat of increasingly sophisticated cyber-attacks. The use of classical cryptography commonly used today faces significant challenges from the emergence of quantum computing. This research aims to develop and test a quantum cryptography algorithm specifically designed to enhance data security in digital communication systems. The research approach involves quantum key generation, quantum encryption using quantum principles such as superposition and entanglement, and testing the algorithm's robustness against quantum and other attacks. The application of the quantum cryptography algorithm in the Secure Messaging application case study resulted in a high level of security and efficiency in the use of computing resources. Robustness testing also showed that the algorithm is able to withstand various types of attacks, including sophisticated quantum attacks. The results of this research have far-reaching implications in improving the privacy and security of user data in digital communications. The next step is to develop and implement this algorithm on a wider scale, as well as evaluate the performance and efficiency of the algorithm for practical use in various contexts.
Development of Quantum Algorithms for Neural Network Optimization in Big Data Analysis Nurhayaty, Maria; Manullang, Jontinus
Jurnal ICT : Information and Communication Technologies Vol. 14 No. 2 (2023): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v14i2.136

Abstract

This study explores the development and implementation of quantum annealing algorithms for optimizing neural networks in big data analysis. The background highlights the computational challenges faced by traditional optimization techniques in handling large-scale datasets and the potential of quantum computing to overcome these challenges. The research objective is to demonstrate the effectiveness of quantum annealing algorithms in improving training time, convergence rates, and predictive accuracy of neural networks. Methodologically, the study employs a quantitative approach, utilizing simulation experiments and empirical data analysis to evaluate the performance of quantum-enhanced optimization techniques. The results indicate significant reductions in training time, accelerated convergence rates, and improved predictive accuracy, showcasing the potential of quantum computing to enhance machine learning models for big data analytics. These findings have implications for various industries reliant on data-driven decision-making, paving the way for transformative developments in computational intelligence and quantum-enhanced machine learning.
Use of Differential Evolution Algorithm for Parameter Optimization in Weather Prediction Models Permana, Nana Yudi; Sari, Deassy Ratna Juwita
Jurnal ICT : Information and Communication Technologies Vol. 14 No. 2 (2023): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v14i2.137

Abstract

This research aims to optimize the parameters in a weather prediction model using the Differential Evolution (DE) algorithm, with a focus on improving the accuracy of more reliable weather predictions. The main problems faced in developing weather prediction models are model complexity and uncertainty in parameterization. The DE method is used to adjust the complex parameters in the model, resulting in a significant improvement in weather prediction accuracy based on evaluation using observational data. The implications of this research are that it makes a valuable contribution to our understanding of parameter optimization in weather prediction, as well as improving our ability to predict atmospheric conditions more accurately and reliably.
Optimization of K-Means Algorithm for Big Data Clustering Using Computational Distribution Approach Sari, Deassy Ratna Juwita; Permana, Nana Yudi
Jurnal ICT : Information and Communication Technologies Vol. 14 No. 2 (2023): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v14i2.138

Abstract

In the growing digital era, big data clustering becomes a major challenge in data analysis, especially with the well-known K-Means Algorithm that has limitations in dealing with large-scale data. This study aims to optimize the K-Means Algorithm for big data clustering with a computational distribution approach, to improve clustering efficiency and accuracy. We use the computational distribution approach to process data in parallel across multiple computing nodes, optimize memory usage, develop an intelligent cluster center selection algorithm, and optimize communication between nodes. The implementation of this optimization method successfully improves the efficiency and accuracy of big data clustering, reduces execution time and memory consumption. The practical implications include better business decision making and more effective marketing strategies based on more precise customer data analysis.
Decision Support System for Determining Marketing Strategy Using SWOT and AHP Methods Prabukusumo, M. Azhar
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 1 (2024): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i1.162

Abstract

In the competitive global business era, determining an effective marketing strategy is crucial for companies. This research integrates SWOT (Strengths, Weaknesses, Opportunities, Threats) and Analytic Hierarchy Process (AHP) methods to develop a decision support system in this context. The objective is to identify internal and external factors that affect the performance of manufacturing and service companies, and rank strategic priorities based on the relative weight of each SWOT factor using AHP. By analyzing case studies of several companies in the manufacturing and service industries, the results show that advanced production infrastructure and efficient supply chain management dominate as major internal strengths, while raw material price fluctuations and market competition as significant external threats. The implication is that international expansion strategies and improvements in digital service capacity are key in responding to current global market dynamics. This research not only provides new strategic insights for practitioners, but also provides a theoretical foundation for the development of more advanced analytical methodologies in corporate strategic analysis.

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