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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 157 Documents
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The Application of C4.5 Algorithm to Prediction Sales at PT. Sumber Sayur Segar Fadhila Fadhila; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 1 (2022): March: 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.v5i1.45

Abstract

Fresh vegetables, fruits and fresh meat are one of the basic needs for human life. The need for fresh vegetables, fruits and meat is one of the most important factors for buyers before making a purchase transaction. Likewise with the needs of fresh vegetables, fruit and meat needed by restaurants, cafes, hospitals, hotels and so on. With the increasing number of requests from customers for the needs of fresh vegetables, fruit and meat, companies engaged in the supply and sale of these necessities need to record sales transactions so that there are no stock vacancies and excess stock of goods. Therefore, companies must be more careful in providing fresh vegetables, fruits and meat which are in great demand, so it needs a data processing in the form of data mining using the C4.5 algorithm. In this study, the predicted sales transactions are the last three months of January, February and March 2021. Then for the sales prediction criteria used are in the form of price, type of goods, type of unit and month of sale so that from these criteria can be obtained sales transactions that are selling or not selling. Data mining is a process of mining important information from a very large data. While the C4.5 algorithm is a data classification that has numeric and categorical attributes, where the results of the classification process in the form of rules can be used to predict the value of discrete type attributes from new records. The system was built using the PHP programming language and MySQL as the database. This study obtained predictive results which were implemented in the form of a decision tree, namely the category of types of vegetables belonging to the best-selling sales transactions.
Expert System to Diagnose Eye Disease Due to Frequently Using Computer with Bayes Theorem Method Taozara Laia; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 1 (2022): March: 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.v5i1.46

Abstract

Eye disease due to frequent use of computers is one of the dangerous diseases in health because if not treated quickly it will result in blindness. These eye diseases can be diagnosed through the symptoms that arise in humans or through their clinical picture, through these symptoms an expert system can be made to make a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The expert system made in carrying out the diagnosis uses the Bayes theorem method to calculate the probability of an event occurring based on the influence obtained from the results of observations and experts. The system was built using PHP and MySQL programming as a database. The method used for tracing is Bayes' theorem. While the results of the diagnosis will inform about the results of the diagnosis containing a list of symptoms entered, information on the results of the rules regarding the eye disease suffered and information about possible treatments that can be carried out as well as treatment solutions.
Expert System Diagnosing Eye Diseases Using WEB-Based Forward Chaining Method Ficeroy Derio
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1 (2020): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Health is very important for humans and also very important for the health of the five human senses, especially the sense of sight, namely the eyes. Eyes are windows to the world¸ this sentence seems to be the most appropriate to describe how important eyes are to human life. Often people ignore disturbances or complaints about their sense of sight and people think these complaints can go away on their own. Of course these complaints are early symptoms of eye disease. Because the above treatment is rare with some of its limitations, it is considered less helpful in solving existing problems, finally the idea arises of how the public knows eye diseases and their causes and how to overcome these diseases experienced in the eye without having to be an expert.
Expert System Disease Diagnosis and Drug Relation Amor Pharmacy Ilyas Ilyas
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1 (2020): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The development of information and communication technology today has a major influence on various aspects of life, even human behavior and activities now depend a lot on information and communication technology. One example is the use of expert system-based technology. The development of expert system-based applications has been in great demand since 1950, with a fairly wide coverage area. Expert systems in organizations are aimed at adding value, increasing productivity and managerial areas that can draw conclusions quickly. In this study an application was developed "Expert System for Disease Diagnosis and Drug Relation". This application was built to be an alternative in diagnosing a type of disease based on the symptoms felt by the user, so that the user finds a solution to the problem at hand. From the results of tests carried out using the black box method, it can be concluded that this application can function well. And can provide convenience for users in diagnosing diseases and recommending what drugs are suitable for people with the disease.
Development of Android-Based Expert System to Diagnose Faults on Computer Devices Nafis Akhsan
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1 (2020): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Repairing damage to computer equipment can be difficult if the exact cause of the problem is not known. Therefore, it is necessary to diagnose the cause of the damage first before carrying out repairs. Diagnosis of the cause of the damage can be done using the help of an expert system application. By using an expert system application, one can easily analyze the cause of the damage like when consulting with an expert. In addition, with the application of an expert system, one can also learn to find out the patterns or paths of diagnosing a problem on the computer. Therefore, this study aims to develop an expert system application to perform diagnostics to repair damage to a computer or PC. The type of research conducted is Research and Development (R&D). The R&D process uses a linear or waterfall sequential method which includes the stages of needs analysis, design, implementation, and testing. The expert system application is built to work on an android smartphone device. In order to produce a good application, this study uses the ISO 9126 standard as a standard for the level of application feasibility. The ISO 9126 standard used covers aspects of functionality, reliability, maintainability, portability, and usability. In order to produce a good application, this study uses the ISO 9126 standard as a standard for the level of application feasibility. The ISO 9126 standard used covers aspects of functionality, reliability, maintainability, portability, and usability. In order to produce a good application, this study uses the ISO 9126 standard as a standard for the level of application feasibility. The ISO 9126 standard used covers aspects of functionality, reliability, maintainability, portability, and usability.
Expert System for Diagnosing Skin Diseases Using the Forward Chaining Method Anindita Dhiaksa
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1 (2020): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Puskesmas is one of the most important places in daily life. The puskesmas always records and manages patient data for treatment and provides a consultation service for patients with specialist doctors. the opportunity for patients to consult for skin diseases, but this is deemed less effective, and takes a lot of time while many patients who want to seek treatment are immediately examined. To overcome this problem, a solution is given by building an Expert System for Diagnosing Skin Diseases using the Forward Chaining Method. Where this system is expected to help effectiveness in handling patient consultations and does not interfere with the time of patients queuing for treatment to be immediately treated by doctors. Consultation for patients is provided to give patients the opportunity to help identify and overcome a symptom of a disease without having to come to the puskesmas to queue and can prevent the symptoms of the disease quickly.
Expert System Detection of Cataract Using Production Rules Priska Ambarsari
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1 (2020): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Eyes are one of the five very important senses. If the eye is disturbed, it will inhibit human activities. Eye detection as early as possible will help the public to know the disease. However, patients often cannot consult an ophthalmologist because the doctor cannot be found. The cataract detection expert system was built to help the public and eye doctors to detect cataracts at an early stage. Cataract is one of the eye diseases that causes blindness. Cataracts have symptoms of blurred vision, sensitivity to light, difficulty seeing at night and other symptoms. These symptoms were processed using the IF-THEN production rule and reasoning using conjunctive syllogisms and ponent mode to determine the diagnosis of the type of cataract suffered by the patient. This expert system is able to predict cataract disease accurately. Based on Azwar's criteria and testing by ophthalmologists as experts and 30 users, it shows that the system built tends to be moderate.
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.

Page 3 of 16 | Total Record : 157

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