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All Journal Jurnal Instrumentasi dan Teknologi Informasi (JITI) Bulletin of Computer Science Research Cerdika: Jurnal Ilmiah Indonesia
Priyangan, Donny Muda
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Public Health Social Sciences

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Sistem Pakar Diagnosis Mood Disorder Pada Anak Menggunakan Pendekatan Dempster-Shafer Theory Priyangan, Donny Muda; Herdiansah, Arief; Mulyana, Iwan; Nurhayati
Bulletin of Computer Science Research Vol. 4 No. 6 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i6.374

Abstract

Mood disorders in children are a serious mental health issue that can have long-term impacts on their emotional, social, and academic development. In Indonesia, the limited availability of mental health professionals, especially in remote areas, hinders the process of fast and accurate diagnosis. Manual diagnosis of mood disorders in children often faces challenges in terms of time, resources, and professional expertise, creating a need for an effective solution to support medical practitioners. This research aims to develop a web-based expert system to detect mood disorders in children using the Dempster-Shafer Theory (DST) approach. DST is chosen as the primary method due to its ability to process ambiguous or incomplete information, enabling the integration of multiple pieces of evidence to generate accurate decisions. The system allows users to perform diagnoses based on input symptoms, accompanied by analysis results and follow-up recommendations. The expert system is developed as a web-based platform to optimize accessibility, allowing users to easily carry out the diagnosis process without time and location constraints. Evaluation of the system shows an accuracy rate of 92.5%, validating the effectiveness of DST in mood disorder diagnosis. This research contributes to supporting early detection of children's mental health issues and facilitates the identification of mood disorders based on the symptoms experienced.
Sistem Pendukung Keputusan Pemilihan Bibit Jagung Unggulan Pada Desa Gumuk Rejo Menggunakan Metode (SAW) Azhari, Amalyanda; Priyangan, Donny Muda
Cerdika: Jurnal Ilmiah Indonesia Vol. 1 No. 5 (2021): CERDIKA: Jurnal Ilmiah Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/cerdika.v1i5.478

Abstract

Corn Seed is a very popular commodity plant planted by farmers especially Indonesia because many people use this plant in addition to its many benefits it is also a food crop. Users usually have difficulty choosing Corn Seeds to be bought because of the many types of Corn Seeds, soil construction, and prices. So we need a decision support system that can help users determine the Corn Seed according to the desired alternatives and criteria. In this study, the method used is Simple Additive Weighting (SAW), providing information and assisting farmers in making decisions about the superior corn seedlings they will use. Corn seeds are very important for us because corn seeds are the main factor and determinant of the success of farmers in Gumuk Rejo village. In making the decision support system application selection of superior corn aunt uses the PHP programming language and uses the MySql database.
Aplikasi Visualisasi Data Berbasis Web dengan Deteksi Otomatis Tipe Data untuk Mendukung Analisis Informasi Priyangan, Donny Muda
Jurnal Instrumentasi dan Teknologi Informasi (JITI) Vol. 7 No. 1 (2025): November
Publisher : Prodi D3 Teknik Elektronika Politeknik Gajah Tunggal

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Abstract

The rapid growth of data-driven decision making requires systems capable of managing and presenting data in an effective, flexible, and user-friendly manner. However, variations in dataset characteristics, such as numerical and categorical data, often pose challenges in selecting appropriate visualization techniques. Therefore, this study designs and develops a web-based data visualization application equipped with an automatic data type detection mechanism. The system is able to identify data types automatically and determine suitable visualization forms, including bar charts, line charts, pie charts, histograms, radar charts, and polar area charts. The developed application allows users to import datasets, monitor data quality, and perform interactive visual analysis. The implementation results indicate that the system can present various types of datasets in a structured manner and assist users in understanding data patterns, trends, and characteristics more quickly and intuitively. Thus, this application supports visual analytics processes and enhances the effectiveness of information analysis.
Co-Authors Azhari, Amalyanda Baehaqi Herdiansah, Arief Nurhayati