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Journal of Intelligent Decision Support System (IDSS)
Published by Institute of Computer Science
ISSN : 27215792     EISSN : 27215792     DOI : -
Core Subject : Science,
Computer Science & IT
An intelligent decision support system (IDSS) is a decision support system that makes extensive use of artificial intelligence (AI) techniques. Use of AI techniques in management information systems has a long history – indeed terms such as "Knowledge-based systems" (KBS) and "intelligent systems" have been used since the early 1980s to describe components of management systems, but the term "Intelligent decision support system" is thought to originate with Clyde Holsapple and Andrew Whinston in the late 1970s. Examples of specialized intelligent decision support systems include Flexible manufacturing systems (FMS),intelligent marketing decision support systems and medical diagnosis systems. Ideally, an intelligent decision support system should behave like a human consultant: supporting decision makers by gathering and analysing evidence, identifying and diagnosing problems, proposing possible courses of action and evaluating such proposed actions. The aim of the AI techniques embedded in an intelligent decision support system is to enable these tasks to be performed by a computer, while emulating human capabilities as closely as possible.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
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Search results for , issue "Vol 3 No 2 (2020): June: Intelligent Decision Support System (IDSS)" : 5 Documents clear
Application of an Expert System for Disease Identification in Rice Plants Using the Certainty Factor Method Naufal Irwan
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 2 (2020): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Rice disease is a biotic stress that can reduce yields and can even cause crop failure. Therefore, to get optimum yields in rice cultivation, it is necessary to control disease. Disease is controlled with an Integrated Disease Management (IPM) approach which is integrated into the PTT model. The lack of experts is also a constraint on agriculture. An expert system application is needed to replace the shortage of experts. The application of an expert system for identifying diseases in rice plants applies the Certainty Factor method in determining the identification results. Several supporting tools are also used, such as PHP as a programming language, MySQL as a database, and XAMPP as a local server. The results of functional testing on the application have been running 100% and the calculation of the level of validity of the results is in accordance with the results of the experts. In user testing, 82.67% said it was good, 14.67% said it was sufficient, and 2.67% said it was not enough. Based on these results, the application of an expert system for identifying rice plant diseases has been well received.
Gastric Acid Diagnosing Expert System Using Certainty Factor Method Dimas Prasetyo
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 2 (2020): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Ulcer disease or stomach acid is a psychomatic disease (disease of the mind and body) or it could be an infectious disease caused by bacteria that cause infection in the stomach. Acid reflux can also occur due to irregular eating patterns. At least sufferers are aware about maintaining their diet and choosing food to reduce symptoms of stomach acid. In this case the author tries to create an existing system by proposing an expert system system to diagnose gastric acid disease using the certainty factor method. The certainty factor method is a method to prove whether a fact is certain or uncertain. The main goal in designing this system is to determine the symptoms of gastric acid and how to treat it.
Design and Build an Expert System in the Diagnosis of Ear, Nose and Throat Diseases by Using the Certainty Factor Method Indra Kurniawan
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 2 (2020): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Symptoms of ENT disease (Ear, Nose and Throat) are often underestimated by some people. Even though these symptoms may refer to a serious ENT disease. Therefore, this final project aims to implement an expert system with the Certainty Factor (CF) method in cases of early diagnosis of ENT disease. The ENT diseases in question are otitis externa, otitis media, pharyngitis, tonsillitis, sinusitis and allergic rhinitis. odor, headache / swallowing, decreased hearing function, coughing, fever, sore throat and snoring sleep. Furthermore, for each of these symptoms, an expert CF value was searched. After that, rules are formed according to the symptoms of ENT diseases that refer to certain ENT diseases. Then the user test will produce the user's CF value, so that the final CF value will be used as a value in making decisions from sequential CF calculations between user CF and expert CF and knowing the level of diagnosed disease, namely the level of symptoms or the acute level.
Diabetes Mellitus Detection Expert System Using a WEB-Based Naïve Bayesian Approach Suardin Yakup
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 2 (2020): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Health is the most important factor in a person's life. If health has been disturbed (sick) then a person's activities will be disrupted. Today, many diseases have a large number of sufferers and are even effective killing machines. One of them is diabetes mellitus, which is a disease with the highest number of patients, which is as many as 230 people. In Indonesia alone, the number of diabetic patients reached 4.5 million people in 1995 and it is estimated that by 2025 there will be 12.4 million people with diabetes and ranks fifth in the world. This increasing number every year is not supported by an increase in the number of specialist doctors who can treat this disease, so that many sufferers are not diagnosed with diabetes. Advances in the world of technology really help the modern world to detect or predict something that will happen. One of them is an expert system used to detect a disease in medicine. The relationship between expert systems and Islam is explained in many ways in the Qur'an, especially in Surah Al-Hasyr verse 18. The word Nadhar means reason or thought. Reasoning activities are related to the brain or reason. In the context of science, nadhar can be interpreted as an expert system. Because both of them have the benefit of knowing things that will happen or for predicting and even detecting things that will happen. Intellect can determine the goodness or badness of something that is non-physical, while the expert system is used to detect or determine the presence or absence of diabetes mellitus in a person.
Decision Support System for Elective Course Selection Using the TOPSIS Method Ari Rahayu
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 2 (2020): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The Information Systems Study Program, Faculty of Da'wah and Communication, UIN Raden Fatah Palembang, is one of the study programs that offers elective courses in the high semester, namely between semesters six and seven with various advantages, making it difficult for students to make choices according to their interests and talents. In line with that, more and more elective courses are being offered as alternative choices. They are Geographic Information System (GIS), Advanced IS Analysis and Design, Data Mining and Warehouse, as well as Sillation Modeling in even semesters and Decision Support Systems, Multitier, Mobile Programming, and Artificial Intelligence as alternatives that the Study Program offers in odd semesters. In connection with this problem, Then a Decision Support System for the Selection of Elective Courses is designed so that students can determine the choice of elective courses appropriately according to their interests and talents. The method used for the Elective Course Selection Decision Support System is the Technique Order Preference by Similarity To Ideal Solution (TOPSIS) method. This method was chosen because it is able to choose the best alternative from a number of alternatives, in this case the alternative in question is the best choice of courses based on the specified criteria. The results of the process of implementing the TOPSIS method can sort alternatives from the largest value to the smallest value, so that elective courses are produced as solutions and suggestions for decision making for students

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