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Ronal Watrianthos
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Professional Organization - Ikatan Ahli Informatika Indonesia (IAII) / Indonesian Informatics Experts Association Jalan Jati Padang Raya No. 41 Jati Padang Pasar Minggu 12540 South Jakarta - Indonesia http://iaii.or.id/
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Journal of Systems Engineering and Information Technology
Published by Organisasi Profesi IKATAN AHLI INFORMATIKA INDONESIA
ISSN : -     EISSN : 2829310X     DOI : https://doi.org/10.29207/joseit.*
Core Subject : Science,
Computer Science & IT
International Journal of Systems Engineering and Information Technology (JOSEIT) is an international journal published by Ikatan Ahli Informatika Indonesia (IAII / Association of Indonesian Informatics Experts). The research article submitted to this online journal will be peer-reviewed. The accepted research articles will be available online (free download) following the journal peer-reviewing process. The language used in this journal is English. JOSEIT is a peer-reviewed, blinded journal dedicated to publishing quality research results in Computers Engineering and Information Technology but is not limited implicitly. All journal articles can be read online for free without a subscription because all journals are open-access.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol 3 No 1 (2024): March 2024" : 5 Documents clear
A Survey of Approaches for Designing Course Timetable Scheduling Systems in Tertiary Institutions Musa, Usman Bala; Oyelakin, Akinyemi Moruff
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 3 No 1 (2024): March 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v3i1.5609

Abstract

Scheduling the course schedule in tertiary institutions is a complex and crucial task. Past studies have pointed out that when scheduling is performed effectively, it influences students' learning experiences, faculty workloads, and overall institutional efficiency. It has also been argued that in the allocation of courses, classrooms, and faculty members, various constraints, preferences, assumptions, dependencies, and objectives must be taken into consideration. This article reviewed different approaches that have been employed in designing course schedule scheduling systems with particular reference to tertiary institutions. Relevant articles were sourced from notable research repositories using identified keywords. The articles obtained were categorized according to the different methods that were used to solve the scheduling problems of course schedules in higher institutions. The review evaluated how each approach addresses the challenges in course time table scheduling. Thereafter, the paper discussed the advantages, limitations, and suitability of these scheduling techniques time-tabling. Additionally, real-world implementations in various tertiary institutions are mentioned. By discussing the strengths and weaknesses of different methodologies in this work, this survey is believed to be a valuable resource for future studies in the area of course scheduling in tertiary institutions.
A Bibliometric Analysis of Health-Based Gamification Jawaril Haq Al-Azkiya; Dhea Maulida Rahmah
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 3 No 1 (2024): March 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v3i1.5629

Abstract

Gamification, the application of game design elements in non-game contexts, has emerged as a promising strategy to promote positive behavior change. Although gamification has shown potential in various domains, including healthcare, a comprehensive analysis of the existing literature is needed to map research trends, influential works, and future directions in the field of health-based gamification. This study used a bibliometric analysis approach, using PoP software for data extraction, VOSviewer for visualization, and Mendeley for reference management. Relevant publications on health-based gamification were identified through a comprehensive search across multiple databases. The extracted data was analyzed to examine temporal trends, thematic clusters, influential authors, and citation patterns. The analysis revealed a steady growth in articles related to health-based gamification, with contributions from researchers in different disciplines. The key thematic groups included gamification applications in mHealth, physical activity interventions, serious games, and adherence. Influential authors and highly cited studies were identified, highlighting foundational work and seminal contributions. This bibliometric study offers a comprehensive overview of the health-based gamification literature, underscoring its interdisciplinary nature and diverse research topics. The findings highlight the potential of gamification in promoting positive health behaviors and facilitating patient engagement. Identified research gaps and emerging trends provide valuable information for future studies, fostering innovation and collaboration in integrating gamification principles into healthcare interventions.
Comparative Analysis of Muslim Clothing Sales Predictions Using the C4.5 Method and Linear Regression Alpa Gustiana
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 3 No 1 (2024): March 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v3i1.5678

Abstract

This study aims to develop a sales data prediction model using the machine learning method. Sales are an important indicator in the business world because they can provide information about company performance, market trends, and support better decision-making. However, accurate and reliable prediction of sales data is often a complex challenge. In this study, the researchers collected historical sales data from Farhan Stores that included information about time, product, category, and price. This study also aims to apply data mining techniques to predict sales of Muslim clothes at Farhan stores using the C4.5 algorithm and the linear regression algorithm. The prediction method is used in this study and the calculations are performed using Google Collab. The results of the research that was conducted to predict sales of robes and shirts at Farhan Stores show that the best-selling item during the sales period from January to July 2022 was Sabiyan robes, which were the most sold item or can be said to be the Best Seller item at Farhan Stores. In this study, the parameters MAE (Mean Absolute Error), MSE (Mean Squared Error), and the R2 score are used to evaluate prediction performance. In the linear regression algorithm, the MAE value is 43,633.21, the MSE value is 4,005,924,352.66, and the R2 score is 0.94. Whereas in the C4.5 algorithm, the MAE value was 44,823.96, the MSE value was 50,233,775.14, and the R2 score was 0.94.
Summarization and Classification of Sports News using Textrank and KNN Falahah
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 3 No 1 (2024): March 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v3i1.5706

Abstract

The news summary process is critical in the news analysis process. However, there are frequently barriers to the summary process, such as the large number of news articles and the requirement for news classification. The goal of this study is to develop a news summary and categorization model that will be extremely valuable in the news analysis process. Textrank is the suggested summarizing approach, and KNN will be utilized for news classification. The resulting model can be used to automatically summarize and group news, making content analysis easier. Sports news will be used as the study object from July to August 2023, and the supervised category will be used to identify whether the news comprises sports news in three branches, soccer, badminton / tennis, or basketball. Classification is carried out using the KNN algorithm by training the model using 500 categorized news data. Modeling using k = 3 and k = 5 shows that the precision is around 0.9866 and 0.9666 respectively. The model's implementation on unknown text demonstrates that the model can properly predict text categories as long as the news content falls into the three specified categories, but fails for news content that does not fall into these categories.
Web Mining for Enhanced Academic Visibility and Engagement Analysis Based on Visitor Data Yuhefizar, Yuhefizar; Putra, Roni
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 3 No 1 (2024): March 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v3i1.5713

Abstract

With online platforms that transform scholarly communication, academic journals must strategically amplify their digital footprint. This study demonstrates the value of using web analytics and time series modeling to uncover nuanced online readership trends and rhythms. Using the case of the Review of Rekayasa Sistem dan Teknologi Informasi/System Engineering and Information Technology (RESTI) Journal website's 2023 visitor data, we employ visual and ARIMA time series analysis to delineate engagement patterns aligned with academic cycles. The results reveal pronounced seasonal fluctuations, with the participation peaking in October and November, coinciding with increased research dissemination. Fitting an ARIMA model to daily new visitor data indicates positive autocorrelations, suggesting that the engagement effects persist on days. The model provides a predictive baseline for evaluating outreach initiatives. The study offers strategic information on aligning content planning with reading engagement rhythms. At the methodological level, the integration of data mining, predictive modeling, and information retrieval techniques establishes a versatile framework for investigating evolving scholarly communication dynamics in the digital age. The study also emphasizes meticulous data preparation and model diagnostics. The analytical approach presented provides actionable intelligence on trends in the use of academic portals online. This has far-reaching implications for journals seeking to strategically enhance their digital presence amidst increasing competition. With the proliferation of electronic resources, these techniques will only grow in importance for assessing and amplifying the impact of online scholarly platforms.

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