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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 5 No 2 (2022): June: Intelligent Decision Support System (IDSS)" : 5 Documents clear
Analysis of Financial Annual Reports for Bankruptcy Predictions Using Altman Z-Score Method Kasman Wicaksono; Purnawarman Musa; Apriana Anggraeini Bangun; Octarina Budi Lestari; Witari Aryunani; Sigit Sukmono
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: 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.v5i2.79

Abstract

The study focused on comparisons to investigate a company's financial health situation in diagnosing early bankruptcy of tobacco-producing companies using the Altman Z-Score formula. The bankruptcy risk predictions were analyzed from 2013 to 2018 on the Indonesia Stock Exchange website. The investigative data obtained at the www.idx.co.id website address used annual financial statement data from three tobacco companies in Indonesia for six consecutive years. Research illustrates that from 2013 to 2018, tobacco-producing companies are in the healthy and low-risk category. The total variable is the key to changing its health condition if it changes its value. Therefore, the results of this study can analyze the company, especially financial statements, for information on fulfilling its obligations to investors and creditors and managing assets to increase sales in generate profits.
Prediction of Extreme Sea Water Waves at Ancol Beach Using ID3 Algoritma Algorithm Arum Budi Harti; Dionysius Hendard Christianto; Renata Nabillah; Mutiara Oktavia
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: 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.v5i2.80

Abstract

Ocean waves are natural events where water waves gradually move up and down. This regular rise and fall of water is one of the important aspects of transportation, predicting potential trade disasters and tsunamis in water areas. Know the data The future beyond the level of ocean waves can bring great benefits smoothly Transport and trade of territorial waters. Future data can be obtained from forecasts with certain algorithms. The ID3 algorithm is one of the most common learning algorithms. Used to create a decision tree or decision tree. The result of this analysis is a decision tree that can be used for classifying sea level using an accuracy of 88%.
Usability Evaluation Using Heuristic Method Against NELPIN Website Zaidan Husin; Wenny Eka Maulitya; Sifa Urrohmah
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: 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.v5i2.86

Abstract

The wealth of marine resources in Indonesia is known to be very abundant, especially in fishery products, but until now many fishermen have not been maximal in carrying out fishing activities. Therefore, related parties have launched the NELPIN website which can make it easier for fishermen to carry out fishing activities. To prove that the website can provide convenience to its users, it is necessary to evaluate the usability to test the NELPIN website using the Heuristic method. The system itself needs to be evaluated so that it can be seen whether the system is functioning as desired and errors or deficiencies in the system can be identified and corrected as quickly as possible. The data from this research will be obtained from filling out a questionnaire containing questions regarding usability aspects to evaluate whether the NELPIN website provides convenience for its users or not. Then the results of filling out this questionnaire will be analyzed to draw conclusions and the researchers will provide suggestions that the NELPIN website development team might use to make improvements to the usability of the website.
A Decision Support System To Determine The Best Natural Feed For Fish Cultivation Using Topsis Method Abdul Malik; Ester Frescila Simbolon; Lukman; Tiara Adinda
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: 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.v5i2.87

Abstract

Natural feed in the cultivation of carp (Cyprinus carpio) is a very important effort to do so that the cultured fish can breed quickly and of course in good health. Sometimes carp cultivators are confused about deciding which natural feed is good. This study aims to select the best natural carp feed using a Decision Support System (DSS) with the TOPSIS method. This method uses an alternative approach to the ideal solution called preference value. In this study using several criteria, namely C1: Protein; C2 : Fat; C3 : Carbohydrates; C4 : Feed Prices; C5: Yes. From the calculations performed using the TOPSIS method, the highest preference level with a value of 1 is A1. The results of the Decision Making System with the TOPSIS method from natural selection of carp that can be used by farmers, namely earthworms.  
Evaluation Of Marine Economic Literature Usability Website Using Heuristic Method Sufadlan Nugraha; Putri Ivana Anggraeni M
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: 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.v5i2.88

Abstract

In the current era of globalization, all fields are experiencing advances in information technology, including the marine and fisheries aspects. One of the results obtained from this progress is the presence of a website suhana.web.id which is engaged in marine economic literacy, but in its use the website apparently still has several shortcomings such as content updates that are not carried out optimally and regularly. Seeing these problems, the researcher aims to conduct an evaluation on the website by using the heuristic evaluation method in order to provide recommendations. In applying the heuristic method, the author involves three evaluators who are experts in the field of web programming and interface design. The results of the calculation of several problems in this evaluation are the high level of problems found in the Aesthetic and Minimalist Design aspects with a figure of 38%.

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