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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 12 Documents
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Search results for , issue "Vol 6 No 3 (2023): September : Intelligent Decision Support System (IDSS)" : 12 Documents clear
Measurement Of Customer Satisfaction Using Fuzzy Service Quality Method At PT.ABC Helmi Kurniawan
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 3 (2023): September : 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.v6i3.160

Abstract

Customer satisfaction is obtained by someone when they feel satisfied or dissatisfied based on a comparison of product or service performance with their expectations. This factor is very crucial in assessing whether an industry, especially the service industry, is successful or not. The quality of customer satisfaction can be assessed through the difference between customer expectations and perceptions. PT. ABC effectively provides information to customers about the evaluation of the quality of services provided by its employees, as well as the factors that have an influence on the level of customer satisfaction in using these services. This study aims to measure and evaluate the quality of service with the Service Quality method, namely comparing customer expectations and perceptions. For this reason, Service Quality consists of five main dimensions, namely tangibles (physical factors), reliability (reliability), responsiveness (responsiveness), assurance (certainty), and empathy (empathy). The results showed that the service quality of PT.ABC is close to 7. This proves that PT.ABC must improve the quality of its services so that customers feel very satisfied. The highest factor is the factor that most influences customer satisfaction and has the highest gap, which is the assurance factor.
Decision making for network security with simple additive weighting method Andi Zulherry
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 3 (2023): September : 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.v6i3.162

Abstract

In an increasingly complex digital era, network security has become a crucial aspect in maintaining data integrity, confidentiality, and availability. Effective decision-making methods to select the right network security solution are becoming increasingly important. This article describes the application of the Simple Additive Weighting (SAW) method as a support tool in the context of decision-making for network security. In the presented case study, three network security solutions are evaluated based on four important criteria: data encryption level, threat detection, access management, and network performance. The SAW method is used to assign weights to each criterion and generate a ranking of solutions based on the final score. The results show that SAW provides a clear and structured view of the network security solution that best fits the user's needs and priorities. The conclusion of this research is that the SAW method can be used as a useful tool in making informed decisions in the context of network security. SAW allows organizations to adjust their priorities by setting the appropriate criteria weights, thus enabling the selection of solutions that are best suited to the unique needs of each organization. In an era of ever-evolving cyber threats, the ability to make effective decisions in the face of security challenges is becoming increasingly important, and the SAW method can be a valuable tool in achieving that goal.

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