https://ejurnal.jejaringppm.org/index.php/jitcsa <table border="0" width="100%"> <tbody> <tr> <td align="justify" valign="top"><strong>ISSN Print (2964-3139) based on Decree Number 29643139/II.7.4/SK.ISSN/01/2023 dated January 18, 2023;</strong> <p><strong>ISSN Online (2985-5330) based on Decree Number 29855330/II.7.4/SK.ISSN/02/2023 dated February 15, 2023</strong></p> <p><strong>URL : <a href="https://ejurnal.jejaringppm.org/index.php/jitcsa">https://ejurnal.jejaringppm.org/index.php/jitcsa</a></strong></p> <p><strong>The International Journal of Information Technology and Computer Science Applications (IJITCSA)</strong> is an information technology and computer science publication. Applications from both fields for solving real cases are also welcome. The JITCSA accepts research articles, systematic reviews, literature studies, and other relevant ones. The IJITCSA focuses on several fields of science, including information technology and the like and computer science fields such as artificial intelligence, data science, data mining, machine learning, deep learning, and the like. <br /><br />IJITCSA is published three times a year, in January, May, and September. The first issue in January 2023 had eight articles.</p> </td> </tr> </tbody> </table> Jejaring Penelitian dan Pengabdian Masyarakat en-US International Journal of Information Technology and Computer Science Applications 2964-3139 <h1>Attribution 4.0 International</h1> <div id="deed-body"> <h2 id="rights">You are free to:</h2> <ol> <li><strong> Share </strong> — copy and redistribute the material in any medium or format for any purpose, even commercially.</li> <li><strong> Adapt </strong> — remix, transform, and build upon the material for any purpose, even commercially.</li> <li>The licensor cannot revoke these freedoms as long as you follow the license terms.</li> </ol> <h2 id="terms">Under the following terms:</h2> <ol> <li class="cc-by"><strong> Attribution </strong> — You must give <a id="src-appropriate-credit" href="https://creativecommons.org/licenses/by/4.0/#ref-appropriate-credit"> appropriate credit </a> , provide a link to the license, and <a id="src-indicate-changes" href="https://creativecommons.org/licenses/by/4.0/#ref-indicate-changes"> indicate if changes were made </a> . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.</li> <li><strong> No additional restrictions </strong> — You may not apply legal terms or <a id="src-technological-measures" href="https://creativecommons.org/licenses/by/4.0/#ref-technological-measures"> technological measures </a> that legally restrict others from doing anything the license permits.</li> </ol> <h2 class="b-header has-text-black padding-bottom-big padding-top-normal" style="font-weight: bold;">Notices:</h2> <p>You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable <a id="src-exception-or-limitation" href="https://creativecommons.org/licenses/by/4.0/#ref-exception-or-limitation"> exception or limitation </a> .</p> <p>No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as <a id="src-publicity-privacy-or-moral-rights" href="https://creativecommons.org/licenses/by/4.0/#ref-publicity-privacy-or-moral-rights"> publicity, privacy, or moral rights </a> may limit how you use the material.</p> </div> https://ejurnal.jejaringppm.org/index.php/jitcsa/article/view/181 <p>This paper provides a comprehensive review of current database systems and data warehousing technologies within the healthcare sector, emphasizing their roles in supporting forecasting and analytics. The objective is to describe, analyze, and evaluate the key features of these systems, particularly focusing on the essential functions of data storage and data integration in managing complex healthcare data environments. Recognizing that efficient data storage is fundamental to effective database management, the paper examines prevalent challenges within current healthcare systems, including issues related to data infrastructure, security, and interoperability. It further investigates how these challenges impact the reliability and accessibility of data crucial for informed decision-making. In addition to highlighting the difficulties, this review delves into the benefits and drawbacks of various data integration strategies. It discusses how advanced integration techniques can enhance data accuracy, streamline real-time access, and bolster analytical capabilities, while also addressing potential risks such as integration complexity and security vulnerabilities. By synthesizing the latest trends and research in database management, this paper aims to offer valuable insights for healthcare practitioners, IT professionals, and researchers. Ultimately, it seeks to guide the development of more secure, efficient, and resilient data management strategies that can better support healthcare analytics and forecasting in an increasingly data-driven industry.</p> <p><input id="ext" type="hidden" value="1"></p> Bikash Ram Suman Copyright (c) 2025 Bikash Ram Suman https://creativecommons.org/licenses/by/4.0 2025-05-08 2025-05-08 3 2 48 53 10.58776/ijitcsa.v3i2.181 https://ejurnal.jejaringppm.org/index.php/jitcsa/article/view/197 <div><span lang="EN-US">Public safety and order are crucial aspects of social and economic life, especially in densely populated urban areas. High crime rates can undermine the sense of security and quality of life within society. Therefore, a deep understanding of crime distribution patterns is essential for designing effective prevention strategies. This study aims to map crime risk zones in Indonesia using the Agglomerative Clustering method, by integrating socio-economic and demographic variables. This method was chosen for its ability to group data based on similarity of characteristics, making it easier to identify areas with high-risk levels. The results show the formation of four main clusters that reflect crime risk distribution in Indonesia. The first cluster includes several provinces with similar crime patterns, while the other clusters reflect significant differences in crime patterns, particularly in Jakarta, which has very distinct criminal characteristics. This mapping provides valuable insights for the planning of more efficient, data-driven crime prevention policies. The research is expected to provide a strong foundation for policymakers and law enforcement agencies to formulate more targeted strategies to combat crime in Indonesia.</span></div> Tb Ai Munandar Khairunnisa Fadhilla Ramdhania Copyright (c) 2025 Tb Ai Munandar https://creativecommons.org/licenses/by/4.0 2025-07-16 2025-07-16 3 2 54 65 10.58776/ijitcsa.v3i2.197 https://ejurnal.jejaringppm.org/index.php/jitcsa/article/view/200 <p>Data is becoming a valuable resource for organisations in a variety of industries today, including education. Educational institutions are constantly gathering massive volumes of data from many sources. XYZ University (XYZU), one of the higher educational institutions, has issues with its current data infrastructure, which slows down its decision-making. The existing system relies on reporting and analytics that are derived directly from operational applications, which leads to data silos and discrepancies. To address these issues, this paper proposes a data architecture that combines data from several source applications to facilitate integrated reporting. The paper explores the background and problems in terms of data storage, management, and use of enterprise data, followed by a problem statement, a discussion of data integration, and a proposed technical architecture.</p> Lê Thắng Thục Copyright (c) 2025 Lê Thắng Thục https://creativecommons.org/licenses/by/4.0 2025-08-02 2025-08-02 3 2 66 70 10.58776/ijitcsa.v3i2.200 https://ejurnal.jejaringppm.org/index.php/jitcsa/article/view/203 <p><em>The covid-19 pandemic has forced the way businesses run, including the offline apparel store that needs to shift their business to an online shopping platform. This also means that the volume of unstructured data that needs to be analyzed has increased significantly. This unstructured data should be analyzed accurately to help businesses in decision-making and solve their problems such as understanding customer satisfaction levels and evaluating marketing approaches. One way to utilize unstructured data is by using text analytics, the data like customer reviews from the online shopping platform and social media can be integrated and analyzed using a sentiment analysis approach in order to gain a better understanding of customer satisfaction levels. Furthermore, web analytics can also be utilized to evaluate the current marketing approach and how to maximize the marketing strategy for the business.</em></p> Bayani Krisanto Agustin Alon Dakila Ting Althea Keenan Dolores Copyright (c) 2025 Bayani Krisanto Agustin, Alon Dakila Ting, Althea Keenan Dolores https://creativecommons.org/licenses/by/4.0 2025-08-13 2025-08-13 3 2 71 77 10.58776/ijitcsa.v3i2.203 https://ejurnal.jejaringppm.org/index.php/jitcsa/article/view/205 <p><em>Tesla Inc. is frequently regarded as a pioneer in the fields of big data analytics and artificial intelligence. They generate, collect, and analyse a large amount of data every day for a better decision-making for their business and for their self-driving car. However, a little effort was put into marketing. Customer segmentation and customer retention are noticed to be the problems Tesla Inc. should take into consideration. Therefore, the data that is relevant to solve these problems is extracted from various websites and social media platforms by using the text-scrapping technique. Web analytics of Tesla’s official website is studied to analyse the demographic and geographic details of the audiences. Geospatial analysis is also carried out to further analyse the top 5 countries the audiences are coming from. Customers' reviews that were collected undergoes sentiment analysis to determine whether it is positive, neutral, or negative. Text analytics is done in the later stage by gathering all the visualisations into an interactive dashboard and coming up with a possible solution.</em></p> Mulya Firmansyah Copyright (c) 2025 Mulya Firmansyah https://creativecommons.org/licenses/by/4.0 2025-08-20 2025-08-20 3 2 78 85 10.58776/ijitcsa.v3i2.205