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All Journal Jurnal Teknik Informatika UNIKA Santo Thomas KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science MEANS (Media Informasi Analisa dan Sistem) Bulletin of Information Technology (BIT) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal ABDIMAS Budi Darma Ulead : Jurnal E-pengabdian Blend Sains Jurnal Teknik Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat Pascal: Journal of Computer Science and Informatics
Siagian, Edward Robinson
Universitas Budi Darma, Medan
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Social Sciences Other

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Journal : Pascal: Journal of Computer Science and Informatics

 1 
Application of Bayes' Theorem Method to Diagnose Miscarriage in Pregnant Women Siagian, Edward Robinson
Pascal: Journal of Computer Science and Informatics Vol. 1 No. 02 (2024): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

The expert system for diagnosing the causes of miscarriage in pregnant women is an expert system designed as a tool to diagnose the type of food that causes miscarriage. Computer programs intended as a provider of tools in solving problems in certain areas of specialization such as miscarriage problems in pregnant women. This knowledge is obtained from various sources including books and the internet related to the causes of miscarriages. The knowledge base is arranged in such a way into a database with several tables of food types and tables of effects to facilitate the performance of the system in drawing conclusions in this expert system using Bayes' theorem. This expert system will display a selection of symptoms that can be selected by the user, where each effect selection will read the user to the next effect choice until the final result is obtained. In the final result, the expert system will display a selection of user effects, types of foods that cause miscarriage, and solutions.
Optimizing Campus Promotion Routes Through the Application of Dijkstra’s Algorithm Siagian, Edward Robinson; Rajagukguk, Denni M Rajagukguk; Panjaitan, Muhammad Iqbal
Pascal: Journal of Computer Science and Informatics Vol. 2 No. 02 (2025): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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This study aims to optimize campus promotion routes using Dijkstra's algorithm to increase efficiency in time and cost. By applying this method, the shortest and fastest paths to target promotion locations can be optimally determined. Data were obtained through geographical mapping of schools and road accessibility. The implementation of Dijkstra’s algorithm was analyzed in terms of effectiveness and efficiency compared to conventional methods. This study is expected to contribute to enhancing the effectiveness of campus promotion strategies through route optimization.
A SAW-Based Decision Support System for Selecting Final Project Topics in the Informatics Management Department at STMIK Mulia Darma Siregar, Kristian; Siagian, Edward Robinson; Tampubolon, Kennedi
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 01 (2025): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Selection of Final Project Topics is a crucial stage in the academic process, as it significantly affects the smoothness of project preparation and completion. However, the determination of final project topics often remains subjective and does not systematically consider students’ academic abilities. This study aims to design and develop a Decision Support System for selecting final project topics for students in the Informatics Management Department using the Simple Additive Weighting (SAW) method. The SAW method is employed to evaluate and rank alternative topics based on several criteria, including supporting course grades, student interest, programming skills, system analysis and design capabilities, and the availability of supervising lecturers. The results indicate that the SAW method can provide objective and transparent recommendations for final project topics. Based on the calculation, alternative A4 achieved the highest preference score of 0.962, making it the most recommended final project topic. Therefore, the developed system is expected to assist both students and academic staff in making more effective and structured decisions regarding final project topic selection.
Co-Authors , Sony Bahagia Sinaga Armansyah Ritonga Chandra Frenki Sianturi Dahwila Syapnika Doansi Tarihoran Efori Buulolo Fince Tinus Waruwu Ginting, Fransiskus Ikwan Ikwan Indah Lestari Lumban Gaol Ira Sarifah Rangkuti Kennedi Tampubolon Kevin Yanto Sarumaha Kristian Siregar Manalu, Mamed Rofendi Maringan Sianturi Monang Juanda Tua Sihombing Muhammad Syahrizal Murdani Nelly Astuti Hasibuan Panjaitan, Muhammad Iqbal Purba, Elvitrianim Rajagukguk, Denni M Rajagukguk Riswan Limbong Sembiring, Abdul Sani Siburian, Henry Kristian Siddik Karo-Karo Sinaga, Sony Bahagia Sinurat, Sinar Tamba, RL. Harmadi Tamba, RL. Harmady Zainab Hasibuan