Journal Of Data Science

Analysis Of The Use Of Information Technology In Rural Communities

Astri Astri — 2024-09-10

This study aims to analyze the use of Information Technology (IT) in rural communities. Amidst rapid technological developments, rural communities have also begun to adopt IT, although they still face various obstacles such as limited infrastructure and low digital literacy. Through literature studies and previous research, it was found that the use of IT has had a significant impact on rural communities, including social, economic changes, and access to health and education services. However, greater efforts are still needed to increase IT adoption in rural areas and overcome existing obstacles. Further research is also needed to better understand the factors that influence IT adoption and its long-term impact on rural development. Thus, this study is expected to provide valuable insights for policy makers, practitioners, and academics in efforts to improve digital inclusion and the welfare of rural communities.

Application Of C4.5 Algorithm In Disease Classification

Sipra Barutu — 2024-09-12

In the modern era, information and communication technology (ICT) has a significant impact on the health sector, one of which is through the application of artificial intelligence (AI) for disease diagnosis. The C4.5 algorithm, one of the popular classification algorithms, shows great potential in helping doctors classify diseases more accurately and efficiently. Research shows that the C4.5 algorithm is able to achieve a high level of accuracy in classifying various types of diseases, such as diabetes mellitus, heart disease, and lung disease. Its advantages include ease of interpretation, resistance to data noise, and efficiency. However, its application also has several challenges, such as the availability of quality data, complex interpretation of results, and the potential for overfitting. Nevertheless, the C4.5 algorithm offers great potential to improve the quality of patient diagnosis and care. Further research is needed to overcome the challenges and improve the effectiveness of the C4.5 algorithm in disease classification, such as the development of anti-overfitting techniques, optimal attribute selection methods, and application to more types of diseases. With continued research and development, the C4.5 algorithm can become a valuable tool for doctors and other medical personnel in fighting disease.

Designing A Web-Based Information System At SMP Negeri 1 Kualuh Hilir

Eva Rifka Sinaga — 2024-09-18

The rapid development of information technology in the era of globalization has brought significant changes in various fields, including education. SMP Negeri 1 Kualuh Hilir, as an educational institution, requires a web-based information system to facilitate easy and flexible access to information for students, teachers, and parents. This study aims to design and implement a web-based information system with the integration of the Internet of Things (IoT) concept for smart trash management, using the MQTT protocol and the WeMos D1 (R2) microcontroller. The research methodology includes literature studies, observations, needs analysis, hardware and software design, implementation, and system testing and evaluation. The results of the study indicate that the developed system and tools function well, with positive assessments from trials and adequate evaluation results.

Decision Making Techniques For Selecting Female Dormitory Supervisors Using The Technique Method For Others Reference By Similarity To Ideal Solution

Billy Siallagan — 2024-09-30

The female student dormitory at Santo Thomas Catholic University Medan serves as a temporary residence for female students who come from outside Medan. Dormitory supervisors play an important role in the management and supervision of the dormitory, ensuring the safety and well-being of residents. However, the selection of new coaches faces obstacles, such as lack of qualifications and potential conflicts of interest. To address these issues, this research applies the Technique for Order Preference by Similarity to Ideal (TOPSIS) method as a decision-making tool. This method allows the comparison of alternatives to prospective coaches based on set criteria. The results show that the TOPSIS method is effective in determining suitable candidates for female dormitory coaches, thus supporting the establishment of a safe and supportive environment for female students. This research emphasises the importance of a transparent selection process and oversight mechanism to prevent conflicts and ensure the integrity of the candidate.

K-Means Clustering of Student Mid-Term and Final Exam Score Data

Nella Ane Br Sitepu — 2024-09-30

Clustering is a method in data mining that aims to group data based on similar characteristics. This research utilises the k-means clustering algorithm to group students based on their UTS and UAS scores, making it easier for lecturers to identify students' academic abilities. With the application of this method, it is expected to form groups of students who are intelligent, less intelligent, and moderate. In addition, this research also addresses the challenges in observing student grades which are often done manually, resulting in wasted time and effort. Through the k-means clustering approach, this research aims to improve the quality of education by providing insight for education managers in mapping student learning outcomes. The k-means method used includes determining the cluster centre point and calculating the distance between data, which is repeated until convergence is achieved. The results show that this method is effective in identifying student achievement patterns, providing a basis for decision-making to improve academic achievement in higher education.