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The Journal of Information Technology, Computer Science, and Electrical Engineering
Published by Yayasan Sinergi Multidimensi Kreatif
ISSN : -     EISSN : 30464900     DOI : https://doi.org/10.30596/jitcse
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The Journal of Information Technology, Computer Science, and Electrical Engineering (JITCSE) is a premier publication dedicated to advancing research and innovation at the intersection of these dynamic fields. With a focus on cutting-edge developments and emerging trends, JITCSE serves as a vital platform for scholars, researchers, and practitioners to share their latest findings and insights. Covering a broad spectrum of topics including software engineering, artificial intelligence, network security, digital systems, and renewable energy, JITCSE showcases rigorous and impactful research that drives technological progress forward.
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Articles 198 Documents
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Educating on Mobile Computing and Security Practices Yusfrizal Yusfrizal; Heri Gunawan; Yahya Tanjung
Journal of Information Technology, computer science and Electrical Engineering Vol. 1 No. 3 (2024): October 2024
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v1i3.153

Abstract

With the increasing popularity of mobile devices, it has become essential to educate college and university students about mobile computing and security. This paper introduces eight course modules on mobile computing and security that we designed to integrate seamlessly into a computer science curriculum. These modules were showcased during a faculty workshop, where feedback was gathered through survey questionnaires and participants' reflective narratives. The evaluation results from the workshop are analyzed and discussed in this paper. These modules are adaptable for educators teaching mobile application development, cyber security, or other related subjects.
Hybrid Analysis Approach for Detecting Mobile Security Threats Yusfrizal Yusfrizal; Mutiara Sovina; Faisal Amir Harahap; Ivi Lazuly
Journal of Information Technology, computer science and Electrical Engineering Vol. 1 No. 3 (2024): October 2024
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v1i3.154

Abstract

As technology continues to advance rapidly, smartphones are becoming increasingly powerful, drawing a large number of users with innovative features provided by mobile operating systems like Android. However, the security vulnerabilities of these systems make Android devices frequent targets for hackers and cyber criminals. As a result, research on effective and efficient mobile threat analysis has become a critical topic in the field of cyber security, employing methods such as static and dynamic analysis. This paper proposes a hybrid approach that combines static and dynamic analysis to detect security threats and attacks in mobile applications. The proposed method integrates data states and software execution along critical test paths. Initially, static analysis is used to identify potential attack paths based on Android APIs and existing attack patterns. This is followed by dynamic analysis, which executes the program along these paths within a focused scope to determine the likelihood of an attack by comparing detected paths with known attack patterns. In the runtime phase of dynamic analysis, the approach reports types of attack scenarios related to confidential data leakage, such as web browser cookies, while ensuring no actual critical or protected data on mobile devices is accessed.
The Impact of Traffic in the Medan Industrial Estate on the Social and Economic Community of Amplas Village, Percut Sei Tuan, Deli Serdang Regency, North Sumatra Ardiles Hasianta Meka; Abdi Sugiarto; Wahyu Hidayat
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.155

Abstract

This study aims to analyze the impact of traffic in the Medan Industrial Estate on the quality of life of the community in Amplas Village, Percut Sei Tuan, Deli Serdang Regency, North Sumatra. The research method uses a descriptive qualitative approach to understand the traffic impact of the Medan Industrial Estate (KIM), which includes in-depth interviews and questionnaires involving respondents from the local community. The results showed that the presence of industry had a positive impact on the community's economy, with 70.78% of respondents expressing improvements in economic structure and 100% of respondents agreeing that industry has reduced the unemployment rate through job creation. However, negative impacts such as air pollution and noise due to increased traffic are also felt significantly, which has the potential to reduce the quality of life of the community.The results showed that 75.60% of respondents reported an increase in income, but they also faced challenges such as congestion that led to an increase in business operating costs and a decrease in property values. Public perceptions of environmental safety and comfort indicate concern about the risk of accidents and health impacts due to pollution. This study recommends the need for more comprehensive traffic planning and attention to the environmental impact of industrial activities. It is hoped that with the right mitigation measures, the quality of life of the people in Amplas Village can be improved without sacrificing sustainable economic growth.
Application of Business Intelligence to support decision making in determining competent laws in the culinary sector in Deli Serdang Regency using the decision tree algorithm. Muhammad Irsyad; Darmeli Nasution
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.156

Abstract

This study examines the application of Business Intelligence (BI) in identifying high-potential culinary Small and Medium Enterprises in Deli Serdang Regency. By using the Decision Tree algorithm, a prediction model is built based on historical sales data, business characteristics, and business environment factors. The results of the model evaluation show that Decision Tree is able to classify competent Small and Medium Enterprises. Key factors that influence the success of Small and Medium Enterprises, such as product quality, marketing strategy, and access to financing, were successfully identified through decision tree analysis. This study concludes that the application of BI with the Decision Tree algorithm can be an effective tool for stakeholders in supporting the development of Small and Medium Culinary Enterprises in Deli Serdang Regency
Improving the Accuracy of Small and Medium Enterprise Sales Predictions in Deli Serdang Regency by Implementing Business Intelligence Using the Decision Tree Algorithm M Dico Triyadi; Darmeli Nasution
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.157

Abstract

This study focuses on improving the accuracy of sales prediction in Small and Medium Enterprises in Deli Serdang Regency through the application of Business Intelligence (BI). By using the Decision Tree algorithm, a prediction model is built based on historical sales data, seasonal factors, and macroeconomic variables. The evaluation results show that the developed model is able to predict sales with the right accuracy. In addition, this model also successfully identifies key factors that influence sales, such as price, promotion, and economic conditions. This study concludes that the application of BI can be an effective tool for Small and Medium Enterprises in making better decisions and increasing competitiveness.
STUDENT PERCEPTION OF THE ADVANTAGES AND CHALLENGES OF USING CHATGPT (ARTIFICIAL INTELLIGENCE) FOR ACADEMIC ASSIGNMENTS Rajali Saragih; Juliandri; Nuranisah
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.158

Abstract

The presence of Artificial Intelligence (AI) has an influence on various areas of life. One of the products of AI is ChatGPT which is a product of a non-profit company, namely OpenAI which was established in 2015. The presence of ChatGPT has received various responses from the public, especially in the academic field who debate the use of ChatGPT. The use of ChatGPT is feared to threaten academic integrity, while on the other hand, there are those who argue that ChatGPT can facilitate work in the academic world. This research aims to explore students' perceptions of the advantages and challenges of using Artificial Intelligence (AI), especially ChatGPT, in completing academic assignments. As one of the AI technologies based on natural language processing, ChatGPT has been widely used to support various academic needs, such as information searching, essay preparation, and idea development. The main advantages identified include time efficiency, ease of access to information, and increased productivity. However, the challenges faced include the risk of plagiarism, lack of mastery of the material, and potential dependence on technology. This study uses a survey method to collect data from students of the computer systems study program of the University of Panca Budi Development. The results showed that students had diverse views, with most appreciating the benefits, but still worried about the impact on academic ethics and the development of critical thinking skills. This finding is expected to be a reference for educational institutions in formulating policies for the ethical and effective use of AI technology in the learning process.
Implementation of Deep Learning CNN Algorithm for Classification of Gas Station Digitization Inventory Devices Doli Sawaluddin; Zuhri Ramadhan
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.159

Abstract

The process of digitizing gas station devices requires careful data validation, especially on device images that are often subject to input errors. To overcome this, this research proposes the use of Convolutional Neural Network (CNN) algorithm with transfer learning technique. The pre-trained CNN model will be used to classify the device images into 13 classes. For the sake of development flexibility, the data is divided into 2 separate models.
Design and Build a Network Monitoring System Using Nagios at PT. Telkom Access Muhammad Tri Madja Pandia; Fachrid Wadly
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.160

Abstract

The implementation of an effective network monitoring system is very important for companies to maintain service performance and availability. This research aims to design and implement a network monitoring system using Nagios at PT. Telkom Access. The research methodology includes direct observation, interviews with related parties, and literature studies. The results of the study show that the implementation of Nagios in PT. Telkom Access enables real-time monitoring of network devices and servers, provides early notifications of potential problems, and facilitates rapid response to disruptions. The system is integrated with the Ubuntu Server 22.04 operating system and utilizes the Nagios plugin to monitor various performance parameters. In conclusion, Nagios provides reliable and effective solutions to increase service availability, optimize network performance, and ensure customer satisfaction at PT. Telkom Access.
ARRANGEMENT OF THE CAMPUS AREA OF PANCA BUDI DEVELOPMENT UNIVERSITY IN FLOOD PREVENTION IN THE RAINY SEASON Dian Syahputra; Abdi Sugiarto
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.161

Abstract

The arrangement of the Panca Budi Development University (UNPAB) Campus area in preventing flooding in the rainy season is an important issue that must be considered to maintain the smooth running of lecture activities and the comfort of the campus environment. This study aims to analyze and design flood mitigation solutions by applying the concept of Integrated Water System Management (IWSM) which can effectively manage rainwater flow. IWSM is a holistic approach that integrates green infrastructure and technology to manage stormwater, reduce runoff, and improve water quality. The method used in this study is a qualitative approach with a descriptive analysis of the existing conditions of the campus and the potential for the application of IWSM. The results of the study show that the implementation of IWSM on the UNPAB campus can reduce flood risk by improving the drainage system, increasing green open space, and utilizing rainwater harvesting technology. In addition, these solutions also contribute to groundwater management and create a greener and more sustainable environment. This study recommends regular maintenance of water infrastructure and increased awareness and participation of the academic community in maintaining the sustainability of the IWSM system on campus.
Production of Lactuca sativa with Variations in Liquid Organic Fertilizer Concentration as an Ecoenzyme Derivative in a Hydroponic System Mara Antero Siregar; Najla Lubis; Ruth Riah Ate Tarigan
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 1 (2025): February-May 2025
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i1.162

Abstract

Lettuce (Lactuca sativa L.) is a type of horticultural plant that has high nutritional content and economic value, with good prospects for development. Lettuce is an annual plant that is easy to cultivate in various types of land and has a wide market. The research was conducted to determine the response of lettuce plant production (Lactuca sativa L.) to the application of lemna leaf compost enriched with goat manure and the use of variations of liquid organic fertilizer as ecoenzymes derivative in a hydroponic system. This research used a factorial Randomized Complete Block Design (RCBD) consisting of 2 factors with 5 treatments and 3 replications. The first factor was the variation of liquid organic fertilizer from ecoenzymes at 5 levels: P0 = AB Mix (control), P1 = POC 1 (Pure EE), P2 = POC 2 (EE + egg shells + pineapple), P3 = POC 3 (EE + moringa leaves + insulin leaves), P4 = POC 4 (EE + guava leaves + sweet potato leaves + long bean leaves), P5 = POC 5 (EE + water spinach + baby corn). The second factor was the concentration of ecoenzyme at 3 levels: E0 = 0%, E1 = 25%, E2 = 50%. The observed parameters in this research included plant height (cm), number of leaves (leaves), fresh weight per plant (g), stem diameter (cm), plant weight per plot (g), and root length (cm). The results showed that POC 5 (EE + Water Spinach + Baby corn) provided fairly good results, ranking second after AB Mix, in terms of plant height (cm), fresh weight per plant (g), stem diameter (cm), plant weight per plot (g), and root length (cm). This indicates that a combination of more diverse and natural organic materials can optimally support plant growth.

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