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JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Published by Lumina Infinity Academy
ISSN : -     EISSN : 30903939     DOI : -
Core Subject : Economy, Science, Education, Engineering,
Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering
JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture The Journal of Information Technology Applications in Education, Economy, Health and Agriculture (JITEEHA), published by the Lumina Infinity Academy Foundation, was established in January 2024. JITEEHA is a rigorously reviewed, double-blind peer-reviewed journal committed to publishing high-quality articles. The focus of the journal encompasses the innovative application of information technology across various sectors including educational technology and management, economic systems, business, finance, healthcare, and agriculture. JITEEHA is published triannually, with issues released in February, June, and October each year. The journal aims to provide a platform for academics, researchers, and practitioners to disseminate their findings and contribute to the advancement of knowledge in these critical fields. This journal is published three issues per year, in February, June, and October.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 25 Documents
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User Experience Analysis in Website-Based Digital Invitation Design Suksmawati, affi Nizar; Peldon, Tshering
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
Publisher : Lumina Infinity Academy Foundation

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Abstract

Human-Computer Interaction (HCI) studies how humans interact with computer technology, focusing on interface design that allows users to communicate and operate computer systems effectively and intuitively. The goal is to enhance user experience, productivity, and satisfaction through approaches that consider users' needs, preferences, and abilities. A digital invitation is created digitally, usually in electronic formats such as email, text messages, social media posts, or websites. Digital invitations can be images or text sent to guests via digital platforms, often accompanied by RSVP links or additional information. Creating and using digital invitations addresses various limitations of traditional physical invitations, such as accessibility issues, delivery costs and time, and environmental impact. This research involves creating a prototype of a digital invitation using design platforms like Canva and collecting and analyzing online questionnaire data to assess user efficiency, flexibility, and satisfaction. The results show that digital invitations have many advantages, including cost efficiency, reduced environmental impact, ease of management, and higher interactivity than physical invitations. The conclusion of this study emphasizes the importance of interactive and user-friendly design, as well as high user satisfaction with digital invitations. Recommendations include further development of interactive features, enhanced data security, testing on various devices, and promotion and education on the benefits of digital invitations.
Evaluation of Reading Interest Based on Octalysis Gamification Fairuzabadi, Ahmad; Rahman, Afida
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
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Abstract

An abstract is often presented separate from the article, so it must be able to In the rapidly evolving information and technology era, literacy remains a crucial factor for a competitive and innovative society. Despite its significance, Indonesia faces a severe literacy challenge, evidenced by low reading interest and poor performance in international assessments like PISA. This issue is exacerbated by data from UNESCO and global literacy rankings, revealing that only a minimal fraction of the population engages in regular reading. With the advent of Industry 4.0, the ability to access and analyze information through reading has become increasingly vital. This study aims to address this challenge by leveraging gamification to enhance reading motivation and engagement. Specifically, it employs the Octalysis Framework by Yu-kai Chou to design a gamified system tailored to intrinsic user motivations. The research has three main objectives: identifying user profiles using Octalysis to understand individual reading motivations; designing and implementing gamification elements in the "Codex Horizon" app, including points, achievements, and community features; and evaluating the effectiveness of these elements in increasing reading engagement. The study seeks to provide insights into how gamification, grounded in Octalysis Framework, can be utilized to improve literacy in Indonesia, offering practical guidance for developers, educators, and policymakers.
Designing e-Learning Applications Using the Octalysis Gamification Framework Fitriana Kadir, Shaifany; Auwal Salisu, Imam
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
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Abstract

In the digital era, information technology has penetrated various aspects of life, including education, with e-learning and gamification becoming increasingly popular approaches. Gamification in e-learning utilizes game mechanics to increase user motivation and participation in digital learning. The Hedonic-Motivation System Adoption Model (HMSAM) is an important evaluation model for assessing the effectiveness of gamification with a focus on hedonic motivations such as satisfaction and engagement. This study aims to explore the application of HMSAM in evaluating gamification-based e-learning applications, as well as understanding the influence of elements such as Epic Meaning, Accomplishment, and Social Influence on user motivation. This evaluation is expected to produce effective strategies to improve the learning experience and maximize the use of e-learning applications. The research methods include a literature study on Design Principles and the Octalysis framework, the development of Android-based mobile applications using Android Studio and Firebase, and application evaluation using HMSAM. The results of the study are expected to provide important contributions to the design of more effective and enjoyable e-learning applications.
Analysys of Consumer Buying Behavior of Goods and Services Using The Naïve Bayes Method and Clustering Study in The Computer Service Shop Fahmi, Muchammad Alvi Nur; Marisa, Fitri; Conteh, Alusine
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
Publisher : Lumina Infinity Academy Foundation

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Abstract

Based on the observation results at Anik Komputer as a company providing computer, printer, and other device services, online sales results have a significant influence on revenue generation. Therefore, it is necessary to know the most significant factors that influence consumers to buy goods and services online. This study aims to identify factors that influence purchasing decisions, evaluate consumer behavior patterns, and propose strategic steps based on web intelligent. The analysis method uses Data Mining with the Naïve Bayes and Clustering algorithms. The results of this study indicate that the factors that influence purchasing decisions at Anik Komputer are price, customer reviews, and stock availability. Customer segmentation based on purchasing patterns through Clustering analysis produces three main segments, namely loyal customers (30% of total customers) who contribute the most to total sales of 40%, price sensitive customers (50% of total customers) who contribute 45% to sales, and new customers (20% of total customers) who contribute 15% to sales. This analysis provides deeper insight into consumer behavior that can be applied in intelligent web-based marketing strategies to increase the effectiveness and efficiency of online sales.
Data Mining Application for Classification of Online Transportation Customer Satisfaction Using C4.5 Algorithm Wardhani , Arie Restu; Irawan, Ryan Avrilio; Marpaung, Fhadillah Ain; Saputra, Idris Ivan; Maukar, Anastasia L
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
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Abstract

In the era of increasing business competition, transportation companies are required to enhance the efficiency and effectiveness of their services. One method that can be employed to optimize fleet management is through Data Mining analysis. This study focuses on optimizing Ojek online transportation services using the C.4.5 Algorithm method. The aim of this research is to group customers and areas based on service demand patterns, thus improving fleet distribution and reducing waiting times. The data used in this study includes location, demand, and trip frequency information. The analysis results show that the C.4.5 algorithm method effectively groups the data, providing optimal fleet distribution and enhancing service performance. This research demonstrates that applying data mining through the C.4.5 algorithm method can be an effective strategy for improving management and operational efficiency in Ojek online transportation services, offering competitive advantages in service efficiency and customer satisfaction.
Application of the Naive Bayes Algorithm to Predict The Purchase Decisions Puspitarini, Erri Wahyu; Masdiyanto, Andreas; Kiyosaki, Robert Baz; Hakiki, Sudrajad; Conteh, Alusine; Wafa, Fachrian Muhammad Ahzami
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 2 (2024): June
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This study applies the Naive Bayes algorithm to predict the decision to purchase used motorcycles based on attributes such as model, year of manufacture, price, engine capacity, and transaction results. Utilizing the Gaussian Naive Bayes approach for continuous data, this research aims to develop a reliable predictive model and understand the most significant attributes influencing purchasing decisions. The test results show that the predictive model achieves an accuracy rate of 75%, indicating the effectiveness of the Naive Bayes algorithm in handling data classification. This study provides insights that can help industry players enhance their sales strategies based on accurate data analysis.
Clustering Of Informatics Students Based On Understanding The Material Using The K-Means Method Irmayanti, Meiselina; Prasetyo, Naufal Ibra; Bria, Dionisia Kasilda; Paratu, Jeki Bani; Hanfiro, Pauline
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 2 (2024): June
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Abstract

The level of student understanding in coursework is a crucial determinant of academic success, reflecting both teaching quality and the effectiveness of applied learning methods. In the context of Informatics, challenges often stem from the complexity of subjects such as algorithms, programming, and data analysis, which require analytical and in-depth comprehension. However, differences in learning abilities, backgrounds, and styles often result in varying levels of understanding among students. This study investigates the application of k-means clustering as an innovative method to analyze academic data and classify students based on their understanding of course materials. By utilizing data such as exam scores, quiz results, and classroom engagement, k-means clustering identifies patterns in students’ comprehension levels, offering educators insights to tailor teaching strategies effectively. The findings of this study are expected to aid educators in designing targeted interventions, enhance learning processes, and support an inclusive and effective academic environment.
PREDICTION OF INFORMATICS ENGINEERING STUDENTS' GRADUATION USING THE NAIVE BAYES METHOD BASED ON VALUES ASSIGNMENTS AND ATTENDANCE Akhdan, Farrel Muhammad Raihan; Koten, Antonius Suban; Bouk, Anggela M; Rozi, Fatchulloh Reza Ar; Agustina, Rini
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 2 (2024): June
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Abstract

Student graduation is one of the indicators of the success of the educational process in higher education. This study aims to predict the graduation of students in the Informatics Engineering study program using the Naive Bayes method, by considering the Final Semester Exam (UAS), Mid-Semester Exam (UTS), assignments, and attendance as the main variables. The Naive Bayes method was chosen because of its simplicity in handling multivariable data and its ability to produce accurate classification models.
Determining Potential Players For The Indonesian Senior National Team In The 2026 World Cup Qualifications Using K-Means Risnanto, Slamet; Alfian, Fikri; Faiz, Moh Imam; Nizar, Moh.; Widarti, Dinny Wahyu
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 3 (2024): October
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Football is a very popular sport, and the Indonesian National Team is the pride of the Indonesian people. In an effort to improve team performance, especially in facing the 2026 World Cup qualifiers, optimal player selection is a major challenge. This study applies data mining technology to determine potential players who can strengthen the Indonesian Senior National Team. Player data is taken from the Transfermarkt site which includes attributes such as player market value, club, and league. The methods used include data collection, data cleaning and normalization, and analysis using the K-Means clustering algorithm. The analysis process successfully grouped players into four clusters based on their potential. Players in clusters 1 and 3 have high potential to fill the main lineup, while players in cluster 0 show long-term development prospects. Visualization and manual evaluation support the interpretation of the results for strategic decision making. This study shows that the use of data mining can improve efficiency and accuracy in player selection, providing a more objective data-based approach. However, this study has limitations, such as the lack of consideration of non-technical factors. With the addition of data from other sources and the use of additional algorithms, this method can be further developed to support the performance of the Indonesian National Team optimally in the future.
Sentiment Analysis of Comments on Higher Education Social Media Using Naïve Bayes Algorithm Salisu, Imam Auwal; Ramadhan, Irzal Raisya; Matdoan, Sakina; Arifin, Zainal; Praseptiawan, Mugi
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 3 (2024): October
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The rapid development of information technology has driven the widespread use of social media across various aspects of life, including the academic environment. Social media platforms, such as Instagram, have become popular channels for disseminating information and fostering interactions between individuals and groups. With the growing number of users, sentiment analysis on social media is essential to understand public perceptions and responses to specific issues. Higher education institutions play a strategic role in creating a positive image through social media. Social media provides opportunities for universities to convey achievements, academic activities, and other information effectively to a broader audience, enhancing their reputation in the public eye. Moreover, Instagram serves not only as a communication tool but also as an educational medium capable of increasing student engagement through relevant and informative content. Technically, the Naïve Bayes algorithm is well-known for its speed and efficiency in sentiment analysis. This probability-based method leverages historical data to predict positive, negative, or neutral sentiments, offering competitive accuracy even when handling large datasets. This study aims to apply the Naïve Bayes algorithm for sentiment analysis of comments on the Instagram account of Widyagama University (@uwg.malang) as a case study. The research is expected to provide valuable insights for developing effective communication strategies and serve as a reference for other higher education institutions or organizations in utilizing analytical technologies for strategic purposes.

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