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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 47 Documents
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Use of Geographic Information System (GIS) in Decision Support System for Optimal Location Selection for Opening Ayam Geprek Branch Offices 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.v15i1.163

Abstract

Determining the optimal location for opening Ayam Geprek branch offices in Medan City faces complex challenges as it must consider various demographic and economic factors. This research aims to develop a decision support system using Geographic Information System (GIS) that is effective in identifying strategic locations for business expansion. The research method involved analyzing data on population density, accessibility, and culinary competition, which were then integrated in the GIS to generate a map of optimal locations. The results of the analysis showed that the GIS was able to identify several potential locations that met strategic and economic criteria, and had a positive impact on local economic development. The implications of this research show that the use of GIS not only facilitates the business decision-making process, but also contributes to the sustainability and inclusiveness of economic development in the area
Prediction analysis condition animal use algorithm (SVM+KNN) Dhany, Hanna Willa; Izhari, Fahmi
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 2 (2024): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i2.173

Abstract

This research focuses on the development of a prediction model. Condition animals use Support Vector Machine (SVM) and K-nearest neighbors (KNN) algorithms. In animal husbandry and health animals, the ability to monitor and analyze condition health in real-time animal monitoring is essential to ensure welfare and productivity. Animals. The SVM and KNN algorithms were selected Because of their advantages in classification and regression tasks. The dataset used covers various health parameters for animals, such as temperature body, heart, diet, daily activity, and health data historical. This study shows that SVM and KNN algorithms are very accurate high in predicting the condition of healthy animals, with SVM achieving an accuracy of 97.63% and KNN achieving an accuracy of 97.16%. This prediction model allows detection early detection of health problems in animals so that the breeder and doctor animals can take action preventive and curative more quickly. The results of this study indicate that The combination of SVM and KNN can provide better predictions. Accurate and reliable, which ultimately will increase the health and well-being of animals.
Application of KNN Algorithm for Credit Risk Analysis in Savings and Loan Cooperatives Vandika, Arnes Yuli; Pannyiwi, Rahmat
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 2 (2024): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i2.174

Abstract

Credit risk assessment is a major challenge in the management of savings and loan cooperatives, especially when traditional methods are often affected by subjective biases and limitations in analyzing data systematically. This research aims to apply the K-Nearest Neighbors (KNN) algorithm in predicting credit risk accurately and efficiently, with a focus on analyzing borrowers' demographic features and credit history. The research methodology involved primary data collection from savings and loan cooperatives, descriptive statistical analysis, and performance testing of the KNN model using evaluation metrics such as accuracy, precision, recall, and F1-score. The analysis showed that the KNN algorithm achieved an accuracy of 85%, with high recall, indicating the model's ability to detect credit risk consistently. This research makes theoretical contributions by strengthening evidence of the effectiveness of machine learning in financial risk management as well as practical implications in the form of increased efficiency and objectivity in credit decision making. For broader generalization, future research is recommended to use more diverse datasets and explore other more complex algorithms. In addition, ethical aspects such as algorithm transparency and personal data protection should be the main concerns in field implementation.
Application of Analytic Network Method for Employee Bonus Determination Process Sianipar, Baringin; Ndaraha, Juandi; Marpaung, Ramadina
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 2 (2024): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i2.179

Abstract

Employee bonus system is one of the important strategies in human resource management (HRM) to improve employee motivation, performance, and loyalty. However, many companies face challenges in creating a fair, transparent, and effective bonus system, mainly due to reliance on traditional assessment methods that are subjective. This research aims to develop an employee bonus model based on the Analytic Network Process (ANP) method that is able to capture the relationship between criteria holistically. The research method involves data collection through observation, interviews, and literature study, and data analysis using ANP to evaluate criteria such as target achievement, productivity, work quality, initiative, teamwork, and attendance. The results showed that ANP was effectively able to produce objective and transparent prioritization calculations, with employee A03 (Dermawan) identified as the highest bonus recipient with a final score of 0.1632 (32.64%). The implications of this research suggest that the application of ANP can help companies design a more fair and strategic reward system, thereby increasing employee confidence in the bonus system. However, this research is limited to one case study and has not evaluated the long-term impact of the developed model. Future research is recommended to expand the coverage to various industry contexts and integrate advanced analytic technologies to improve the accuracy of the model.
The Use of Smart and Topsis Methods in Decision Making Systems for Prioritizing Screen Printing Production Panggabean, Jonas Franky R; Harahap, Leliana; Sirait, Kamson; Situmorang, Sutrisno; Purba, Sartika Dewi
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 2 (2024): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i2.181

Abstract

Prioritization in screen printing production is a challenge for companies to improve efficiency and product quality, especially in conditions involving various conflicting criteria. This research aims to develop a decision-making system that can optimize the prioritization of screen printing production by using the SMART method for criteria weighting and the TOPSIS method for alternative analysis. The SMART method is used to assign weights to relevant criteria, while the TOPSIS method is used to evaluate and rank alternatives based on the relative distance to positive and negative ideal solutions. The results show that alternative B has the highest ranking with a preference index value of 0.587, which reflects the optimal combination of cost, time, quality, market demand, and resources. The implication of these findings is that combining the two methods can provide more objective and measurable decisions in the management of screen printing production, but further testing is needed on a wider scale and by considering dynamic external factors. This research opens up opportunities for the development of more adaptive systems in production decision-making in the screen printing industry.
Optimization of Bread Inventory Requirement Estimation Using Multiple Linear Regression Method at Coffeebox Medan Lubis, Harmoko; Manik, Aditiarno; Sitorus, Ade Sartika
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 2 (2024): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i2.185

Abstract

Proper bread inventory management is very important to avoid shortages or waste of stock at Coffeebox, which has been experiencing problems in estimating inventory needs due to manual data management. This study aims to develop a bread inventory requirement estimation model using the multiple linear regression method with bread ordering and bread sold variables. The data used consists of 29 observation samples which are processed through regression calculations to obtain regression coefficients and linear equations. The results showed that the resulting model has the formula Y = 3.152506333 + 0.03249542 X₁ + 0.012684868 X₂, with an estimated bread inventory requirement of 107 boxes based on daily demand and sales data. The implication of these findings is that multiple linear regression models can be used to optimize stock management and improve operational efficiency at Coffeebox. This study has limitations in terms of the variables used, so future research is recommended to expand the model by considering other external variables or using more complex methods such as machine learning algorithms to improve prediction accuracy.
Roland Barthes Semiotics Analysis of Human Interest Works at The Beauty Of Photography Exhibition Herry, Herry; Enrieco, Edward; Lukman , Lukman; Paksi, Yudha Febri Al
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 2 (2024): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i2.188

Abstract

This research is titled Roland Barthes Semiotics Analysis of Human Interest Work at The Beauty of Photography Photo Exhibition. The purpose of this study is to determine the influence of human interest aspects on photojournalism at The Beauty of Photography photo exhibition. In selecting photo objects for the collection of respondents taken from photos by students as photo exhibition participants at the time of the photo exhibition. The theory used and considered relevant in this research is Roland Barthes Theory. The method used in this research uses a descriptive qualitative interpretive study method with a critical paradigm. This study found that the meaning of connotation is found in the photos analyzed and that the results of the photos can be understood not only by looking at the photos, but there are ways of reading certain photos so that the message received is in accordance with what the photographer wants to convey.
The Influence of CSR Communication on Legitimacy, Trust and Reputation of BPJS Ketenagakerjaan Radisatra, Brian; Ganiem, Leila Mona
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 1 (2025): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i1.199

Abstract

This study analyzes the impact of CSR communication on corporate legitimacy, trust, and reputation at BPJS Ketenagakerjaan using a quantitative approach with SEM-PLS. A total of 315 participants were selected through purposive sampling. The findings show that CSR communication significantly influences corporate legitimacy (β = 0.948, p < 0.001), trust (β = 0.990, p < 0.001), and reputation (β = 0.678, p < 0.001). Corporate legitimacy mediates the link between CSR communication and reputation (β = 0.423, p < 0.001), while corporate trust does not (β = 0.129, p = 0.078). Theoretically, this study supports legitimacy and social exchange theories, highlighting that transparent CSR communication enhances trust and reputation in public institutions. It also underscores the role of corporate legitimacy in strengthening reputation. From a managerial perspective, transparency in CSR communication, value-driven messaging, and proactive CSR programs are crucial. BPJS Ketenagakerjaan should integrate CSR into its communication strategy to improve public perception and credibility
Customer Engagement Through Instagram Quiz Content by BPJS Ketenagakerjaan Aji, Arfanul; Ganiem, Leila Mona
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 1 (2025): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i1.200

Abstract

This study explores the effectiveness of Instagram-based interactive quizzes in enhancing public engagement with BPJS Ketenagakerjaan. Employing a quasi-qualitative method within a constructivist paradigm, the research investigates how quiz content contributes to user interaction, social security awareness, and audience comprehension. Data were collected through interviews, observations, and engagement rate (ER) analysis between quiz and non-quiz content in 2024. The findings show that quizzes significantly outperform non-quiz content in engagement, with the highest ER reaching 16.29% in October. Key factors influencing engagement include the relevance of quiz themes, interactivity, timing of posts, and incentive offerings. Interviews with six participants—comprising field workers, office employees, and academics—reveal that quizzes are seen as entertaining, informative, and motivating due to their rewards and interactive nature. Additionally, quizzes were found to enhance engagement across cognitive (understanding), affective (emotional connection), and behavioral (information-seeking) dimensions. Social-level effects were also observed, with participants sharing information from the quizzes, creating a ripple effect of public awareness. The study concludes that interactive Instagram quizzes are an effective digital communication strategy for increasing public engagement and understanding of BPJS Ketenagakerjaan’s programs. It recommends diversifying quiz formats, aligning content with trending topics, strengthening incentives, and incorporating follow-up engagement tools such as live Q&A sessions and discussion forums.
Optimization of Weapon Management in the Warehouse of the Indonesian Defense University Using Web-Based QR Code Technology Fadhil, Muhammad Fadhil; Putra, I Made Aditya Pradhana; Setyawan, Muhammad Iqbal; Herris, Fhatur Robby Tanzil; Zhafirah, Findi; Firdaus, Eryan Ahmad
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 1 (2025): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i1.202

Abstract

This study aims to develop a weapon management system in the warehouse of the Indonesian Defense University using QR code-based technology integrated into a web application. This system is designed to address various challenges of conventional management, such as slow recording processes, human error, and data discrepancies, which frequently occur in weapon inventory management. QR code technology enables automated data entry, tracking, and reporting processes, enhancing efficiency, accuracy, and data security. The Agile methodology is applied in the development of this system, covering several stages, including planning, sprint development, iterative testing, and refinement. This system provides key features such as weapon recording using QR codes, student data management, weapon borrowing and returning, and inventory report generation. Testing results show that this system successfully minimizes recording errors and accelerates operational processes. This research significantly contributes to creating a professional, transparent, and accountable weapon warehouse management model, which can serve as a reference for the development of similar systems in other defense environments.

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