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Journal of Computer Science Advancements
Published by Yayasan Adra Karima Hubbi
ISSN : 30263379     EISSN : 3024899X     DOI : https://doi.org/10.70177/jsca
Core Subject : Science,
Computer Science & IT
Journal of Computer Science Advancements is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of science, engineering and information technology. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the Journal of Computer Science Advancements follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2024)" : 5 Documents clear
The Impact of Implementing Blockchain Technology in Learning on Data Security and Integrity Adhicandra, Iwan; Kaaffah, Faiz Muqorrir; Maharaja, Chandra Halim; Sabri, Sabri
Journal of Computer Science Advancements Vol. 2 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i1.927

Abstract

The application of blockchain technology in learning has great potential to improve data security and integrity. Because blockchain is a decentralized technology that uses block chains to record and secure transactions in a transparent and permanent manner, it offers an excellent solution to address security and data integrity issues. This research was conducted with the aim of improving the security and integrity of student data. Student data can be stored in a distributed manner with blockchain. No one can change or delete it without their permission. This goal also includes increasing transparency and accountability of the learning process to ensure that the data used in the learning process is accurate data. The method used in this research is a quantitative method. This method is a way of collecting numerical data that can be tested. Data was collected through distributing questionnaires addressed to students. Furthermore, the data that has been collected from the results of distributing the questionnaire will be accessible in Excel format which can then be processed using SPSS. From this research carried out, researchers can obtain research results that blockchain technology is used to protect educational data by locking the learning history of the learning management system (LMS), so that assessments can be carried out effectively and allow all parties involved to access and verify information safely while ensuring data integrity and validity. Based on the results of this research, it can be concluded that the application of blockchain technology can help improve the security and integrity of student data, such as academic, financial and personal data, in the learning context. By using blockchain, students have complete control over their data and ensure that bad people cannot misuse or access it. Apart from that, blockchain technology can also increase transparency and accountability in the classroom.
Design Android-Based Mobile Food Vendor Location Search Application Bintang, Nadia; Sumpena, Sumpena; Setiawan, Wawan; Raharja, Agung
Journal of Computer Science Advancements Vol. 2 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i1.1071

Abstract

The development of culinary business in Indonesia is progressing from time to time. This was helped by the development of increasingly rapid technology. Non-formal business actors also develop, especially mobile food vendors. The author wants to create an application that can improve the competitiveness of mobile food vendors by providing information that is easily obtained by the public to find out information and locations of mobile food vendors that can be accessed via mobile devices connected to the internet. This research offers an android application that can track the presence of traders in realtime making it easier for users to find food vendors around them using the Location Based Service (LBS) method using Global Positioning System (GPS) technology. In addition, this application also uses Google Maps API technology for map and Firebase needs for database needs.
Implementation of Competency-Based Curriculum in Improving the Quality of Education in Schools Lature, Yohanna; Waruwu, Lestari; Waruwu, Lenis Mahayati; Zalukhu, Cisrad Anda Nita
Journal of Computer Science Advancements Vol. 2 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i1.1084

Abstract

The aim of this research is to evaluate Curriculum Effectiveness: Understanding the extent to which a competency-based curriculum can improve the quality of education by measuring student learning outcomes, level of mastery of material, and students' ability to apply the knowledge and skills they learn. This research uses qualitative/quantitative methods with a descriptive approach. Some of the instruments used in this research are student portfolios, practical exams, formative assessments. The researcher's data collection techniques used interviews, questionnaires, classroom observations, classroom observations, document analysis, exams and assessments, focus group discussions, and reflective notes. This research shows that the implementation of Competency-Based Curriculum (KBK) in the context of school education requires the active involvement of teachers in preparing more contextual learning that is oriented towards skills development. Students are expected to become successful, honest, disciplined, and responsible individuals. However, the quality of education in Indonesia still requires many improvements, including the implementation of appropriate policies as an alternative solution to educational problems. Relevant KBK programs with initiatives for training education personnel include participation in various places, development of family planning organizations, and utilizing the education process to address educational gaps. The importance of administrative support, resource availability, and continuous evaluation and assessment are key to the successful implementation of KBK. Parental and community involvement are also crucial in supporting the implementation of KBK, which ultimately positively impacts the quality of education, student motivation, and alignment with local needs.
Implementation of the Shortest Path Method with Excel Solver to Optimize Goods Delivery Routes Muyammina, Ittrotul; Safira, Aulia; Hozairi, Hozairi
Journal of Computer Science Advancements Vol. 2 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i1.1137

Abstract

The shortest path solver is a program that aims to find the route with the lowest total edge weight between two points in a graph. Commonly used algorithms include Dijkstra for graphs with non-negative edge weights, Bellman-Ford for graphs with negative edge weights, and Floyd-Warshall for finding the shortest path between all point pairs. Its application is wide, ranging from navigation systems, computer networks, to logistics and games. The process of using it involves creating a graph model , selecting the appropriate algorithm, running a solver, and analyzing the results. A practical example shows how the Dijkstra algorithm can be used to determine the shortest route between cities in a road network , with effective and accurate results . The shortest path solver proves to be a versatile and essential tool for solving a wide range of problems in a variety of fields. This research uses quantitative methods with an experimental approach to test the effectiveness and efficiency of using the shortest path method with Solver Excel in optimizing goods delivery routes. The research object is the delivery route from the warehouse to several delivery destinations, with a sample of 10 routes that are most frequently used and have the highest delivery volume. Primary data was obtained through direct observation and interviews with company logistics managers. The results of this study show that the use of shortest path method with Excel Solver is effective in optimising the route of delivery of goods, reducing the cost and time of delivery by 15% and 10%. Although there are limitations for large networks, this tool remains useful and flexible. This implementation can be a reference for other companies to improve their logistics efficiency.
Implementation of Agent Systems in Big Data Management: Integrating Artificial Intelligence for Data Mining Optimization M, Amril Huda; Simamora, Rani; Ulwi, Krim
Journal of Computer Science Advancements Vol. 2 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i1.1210

Abstract

Background: The rapid growth of data generated across various domains necessitates advanced methodologies for effective data management and extraction of meaningful insights. Traditional data processing techniques often struggle with the volume, variety, and velocity of big data. The integration of Agent Systems and Artificial Intelligence (AI) presents a promising approach to address these challenges by enhancing the efficiency and effectiveness of data mining processes. Objective: This study aims to explore the implementation of Agent Systems in big data management, focusing on how the integration of AI can optimize data mining operations. By leveraging the capabilities of intelligent agents, we seek to improve the accuracy, speed, and scalability of data analysis. Methods: A hybrid research methodology was employed, combining a systematic literature review with an empirical case study. The literature review analyzed previous research on Agent Systems, AI, and big data management to identify key trends and challenges. The empirical case study involved deploying an AI-integrated Agent System within a large-scale data environment to evaluate its performance. Key performance indicators (KPIs) such as processing time, accuracy, and scalability were measured and analyzed. Results: The findings indicate that the integration of AI within Agent Systems significantly enhances the data mining process. The system demonstrated a reduction in processing time by 40%, an increase in data analysis accuracy by 25%, and improved scalability, handling larger datasets more efficiently compared to traditional methods. These improvements were attributed to the autonomous and adaptive nature of agent systems, which enabled dynamic data processing and real-time decision-making. Conclusion: The study concludes that the implementation of AI-integrated Agent Systems in big data management offers substantial benefits, including optimized data mining performance. This integration facilitates more efficient and effective data analysis, which is crucial for organizations dealing with large volumes of data. Future research should focus on further refining these systems and exploring their application across different sectors.

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