cover
Contact Name
Marsono Marsel.
Contact Email
idss@iocspublisher.org
Phone
+6281381251442
Journal Mail Official
idss@iocspublisher.org
Editorial Address
Romeby Lestari Housing Complex Blok C Number C14, North Sumatra, Indonesia
Location
,
INDONESIA
Journal of Intelligent Decision Support System (IDSS)
ISSN : 27215792     EISSN : 27215792     DOI : -
Core Subject : Science,
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.
Articles 5 Documents
SCHOLARSHIP RECIPIENT SUPPORT SYSTEM WITH A COMPARISON OF WEIGHTED PRODUCT METHODS AND SIMPLE ADDITIVE WEIGHTING METHODS Oktaviani, Oktaviani; Triayudi, Agung; Solihati, Ira Diana
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1, Maret (2020): Exper System, Decision Support System, Datamining
Publisher : Journal of Intelligent Decision Support System (IDSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1489.467 KB)

Abstract

SMA Dharma Karya as educational institutions annually held the scholarships are given to students based on criteria set by the school. However, in selecting the scholarship still use manual feared scholarships target. So the decision support system built in selecting scholarship learners using weighted product. In this study, using the method of weighted product and simple additive weighting as a comparison. From the results of research on the best methods of weighted product that is on the alternative ranking 14 with a total value of 0.0067401308233662 and the best perengkingan SAW method is also on the alternative 14 with a total value of 0.82. The results of a comparison test on the data obtained 263 product value weighted accuracy of 83.03% and a simple additive weighting of 60.45%. Results have the system usability percentage of 85.6% and has been tested BlackBox Addressing that the system can perform properly selecting scholarship recipients.
EXPERT SYSTEM FOR DIAGNOSE DIABETES BY USING THE CERTAINTY FACTOR METHOD Raditya, Muhammad; Fauziah, Fauziah; Winarsih, Endah Tri
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1, Maret (2020): Exper System, Decision Support System, Datamining
Publisher : Journal of Intelligent Decision Support System (IDSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1247.312 KB)

Abstract

Diabetes mellitus is a chronic autonim disease caused by interruption of blood sugar regulation, or commonly referred to as diabetes or diabetes. If the disease is not treated with proper care, it can cause dangerous complications, can even threaten the lives of sufferers. Implementation of expert system for diagnosing diabetes mellitus using a web-based certainty factor aims to explore the symptoms displayed in the form of questions - questions that can diagnose different types of diabetes mellitus. Results from this study is a web-based expert system that can detect whether a person's disease or diabetes mellitus. Based on the manual calculation, showed the highest value of 0.
EXPERT SYSTEM FOR EARLY DETECTION OF BREAST CANCER WITH THE FORWARD CHAINING METHOD Caniago, Diana; Andryana, Septi; Gunaryati, Aris
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1, Maret (2020): Exper System, Decision Support System, Datamining
Publisher : Journal of Intelligent Decision Support System (IDSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (947.672 KB)

Abstract

Breast cancer will be easier to overcome if it is known as early as possible to the importance of self-awareness to perform a routine inspection of BSE. The study presented aims to design a web-based application in the health field in the early detection of breast cancer. Penelian expert system method on this is to use forward chaining to represents the rule and reasoning into a coherent system based on physical symptoms entered. In this system also gets a percentage probability of 72.7%, so it can be quite good. In addition the system can produce two outputs in the form of possibility, the output is both benign and malignant.
IMPLEMENTATION OF CERTAINTY FACTOR METHOD FOR DIAGNOSE PESTS IN EGGPLANT PLANTS Sujudi, Malik Abdul Aziz; Fauziah, Fauziah; Hidayatullah, Deny
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1, Maret (2020): Exper System, Decision Support System, Datamining
Publisher : Journal of Intelligent Decision Support System (IDSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1453.023 KB)

Abstract

Eggplant crop cultivation is often influenced by various factors, factors that often occurs is pests and diseases. Lack of information and still rely on the experience of farmers to deal with pests and disease is a major cause. This problem is particularly serious because the can lead to crop failure. In this research, expert systems to diagnose pests and diseases eggplant created to help farmers cope with the problem a problem that occurs in terngnya garden and provide solutions and suggestions prevention caused by pests and diseases. Certainty factor method is suitable for expert systems to diagnose disease eggplant crop is because these methods produce results of the highest percentage of belief an expert.
IMPLEMENTATION OF CERTAINTY FACTOR METHOD FOR DIAGNOSE TUBERCULOSIS Wilsen, Wilsen; Wahyuddin, Moh. Iwan; Komalasari, Ratih Titi
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 1, Maret (2020): Exper System, Decision Support System, Datamining
Publisher : Journal of Intelligent Decision Support System (IDSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1323.309 KB)

Abstract

Tuberculosis is an infectious disease caused by the bacteria mycobacterium tuberculosis. In 2017 Indonesia entered into the third largest number of TB cases in the world. Lack of public knowledge of the dangers of tuberculosis makes this disease is growing rapidly. This is the main reason why it is necessary to create a system that can diagnose the early symptoms of the disease so that it can assist in tackling tuberculosis early. An expert system is one of the techniques in the diagnosis of disease. This research aims to develop applications early diagnosis of tuberculosis disease system is expected to facilitate the public in the early diagnosis of tuberculosis. The system uses the calculation of symptoms / complaints using CF (certainty factor). Results of testing performed by the system and test method validation black box shows that each feature can work with both the application and the content therein can be trusted. In addition, this system is quite powerful in handling more users are accessing the system simultaneously.

Page 1 of 1 | Total Record : 5