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All Journal Journal of Intelligent Decision Support System (IDSS) TOFEDU: The Future of Education Journal
Ramadhan, Nuzul
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Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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The Design and Implementation of the Secretariat Website of the Tanjungbalai City Regional Representative Council: An Analysis within the Framework of Field Work Practice Sinaga, Muhammad Nabil; Ramadhan, Nuzul
The Future of Education Journal Vol 4 No 2 (2025)
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v4i2.471

Abstract

In this research, the design and implementation of the website of the Regional People's Representative Council (DPRD) of Tanjungbalai City is used as an analysis in the framework of Field Work Practice (PKL). The main objective of this research is to improve the availability of information and communication between the DPRD of Tanjungbalai City and the community through a digital platform. The research method includes the interface design phase using HTML and CSS and the application of web technologies to create a responsive and functional DPRD website. Analyzing user requirements, user interface design and integration of features that support transparency and audience. The results of this research are expected to increase the effectiveness of communication and public understanding of DPRD of Tanjungbalai City activities and strengthen DPRD's relationship with its constituents through the use of information technology.
Naïve bayes algorithm for early diagnosis of non-communicable diseases Ramadhan, Nuzul; Ramli, Rakhmat Kurniawan
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 3 (2025): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i3.306

Abstract

Non-communicable diseases such as heart disease, diabetes mellitus, hypertension, stroke, asthma, rheumatism, and GRED are still the main causes of illness and death in Indonesia. This problem is more serious in rural areas with limited health services, such as Lubuk Palas Village, Asahan Regency, which faces obstacles in distance, road infrastructure, and a limited number of medical personnel, so early diagnosis is often neglected. This research aims to apply the Naïve Bayes method in a non-communicable disease diagnosis expert system and develop web and mobile-based applications to support the community and medical personnel in early detection. The research method combines primary data from observations and interviews with health workers and secondary data from medical literature. Each symptom is given a probability weight of 0.00–1.00 according to medical consultation, then processed using the Naïve Bayes algorithm with two approaches, namely direct calculation and gradual filtering. The results show that the system produces a posterior probability of 99.32% in the heart disease scenario with typical symptoms and 90.00% in the stroke scenario with partial symptoms. The findings of this research are that the application of two Naïve Bayes inference pathways is proven effective in producing an initial diagnosis that is adaptive to variations in symptoms, relevant for rural conditions with limited health services, and capable of providing fast, practical, and widely accessible medical decision support.
Co-Authors Ramli, Rakhmat Kurniawan Sinaga, Muhammad Nabil