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All Journal Jurnal INKOM ComTech: Computer, Mathematics and Engineering Applications
Nina Sevani
Krida Wacana Christian University
Computer Science & IT Engineering Mathematics

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Web-Based Decision Support Systems Application of Stock Recommendation Using Bayesian Methods Nina Sevani; Maria Ariesta
INKOM Journal Vol 8, No 1 (2014)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.inkom.302

Abstract

We propose an application that can support traders by providing recommendation about the right stock transaction. The expected impact from this application is to reduce the risk of loss, even achieve the maximum profit for traders who use this application. Recommendation that resulted by application is based on Bayesian methods calculation and four technical analysis indicators that most commonly used by stock experts, i.e. Bollinger Bands, Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), and Stochastic Oscillator. Methodology used in this paper consists of data collection, data analysisa, application design, implementation, and testing. From the results of application testing, the accuracy of the application is 87,37%.
Using Certainty Factor Method to Handle Uncertain Condition in Hepatitis Diagnosis Aprilia Eka Saputri; Nina Sevani; Fajar Saputra; Richardo Kusuma Sali
ComTech: Computer, Mathematics and Engineering Applications Vol. 11 No. 1 (2020): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v11i1.5903

Abstract

The research aimed to develop a web-based application using the certainty factor. The use of this certainty factor method allowed processing the data based on the degree of confidence from the experts and the users. The users inputted their symptoms each with the level of confidence. The inference engine drew some conclusions based on the matching process between the input and the rules in the knowledge-based. For every matching pair, the system would calculate the certainty factor. The knowledge-based was developed through discussion with three specialist physicians and literature in some previous studies. The evaluation of the system involved three specialists for validation testing and 51 respondents for BlackBox testing. The final result is displayed in the form of a percentage for each hepatitis type, explanation of first aid for hepatitis, and referral hospital for hepatitis patients. The result shows that the error rate in the diagnosis process is under 36%. Most of the respondents think that the quality of the system is good overall.
Co-Authors Aprilia Eka Saputri Fajar Saputra Maria Ariesta Richardo Kusuma Sali