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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
 1 
Search results for , issue "Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)" : 5 Documents clear
Implementation Of Data Mining In Determining Sales Pattern Of Snack Products Using Apriori Algorithm (Case Study: PT Siantar Top Tbk) Siti Patimah; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

PT Siantar Top.Tbk is a company engaged in snack manufacturing which is located at Jl Raya Medan Tebing Tinggi, Ujung Serdang, Tanjung Morawa, Deli Serdang Regency, North Sumatra. In the sales transaction data processing process at PT Siantar Top Tbk, it has not been able to provide accurate information about the pattern or relationship of a set of items purchased by customers. So that the company has difficulty knowing every product that is sold, because the sales data is always increasing, but the company does not understand how to manage the sales data of these snack products. Because the snack product sales data is only archived and not managed by the company to get new results. The purpose of this research is to design and build a priori algorithm in determining sales patterns. This system is designed using UML and is built with the programming languages ​​PHP, HTML, CSS, Javascript and Mysql as the database. Then the determination of the sales pattern of snack products that are successful every month at PT Siantar Top Tbk using the Apriori algorithm. A priori algorithm is a data mining technique to find associative rules between a combination of items.
Application of Data Mining in Determining Sales Patterns at 212 Mart Supermarkets in Lubuk Pakam Using the Apriori Algorithm Anzelia Anzelia; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Data mining is a search and analysis on a very large database so that an interesting pattern is found with the aim of extracting information and knowledge that is accurate and potential, as well as understandable and useful from a large database. In this final project, one of the data mining techniques is implemented, namely the a priori algorithmcan define the rule pattern of the data set. The data in this study aims to determine the pattern of sales at 212 mart supermarkets in Lubuk Pakam. This research is obtained from the results of transaction data in the form of consumer purchase receipts, the data used are 10 transaction data with 43 total products. From the results of manual calculations, there are 23 rule association results in accordance with the minimum limit values ​​for support and confidence that have been determined and the highest analysis results are found in french fries and chitato with a minimum support of 30% and 100% confidence. The results of the data mining process obtained can be used for the arrangement or arrangement of layout patterns that are adjusted to the association rules to suit consumer purchasing patterns.
Decision Support System for Selection of Thesis Advisors Supervisors Thesis Advisors according to the Field of Science Using the AHP Method Jelita Sari Simanungkalit; Hengki Tamando Sihotang
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Thesis is a scientific work and a condition that must be taken in order to achieve a bachelor's degree. Thesis supervisors play an important role because they have the responsibility and ensure that students are able to compile the thesis properly so that it is ready for testing and quality. In higher education, a system is needed that can help and ease a job, especially in the selection of thesis supervisors. In selecting the thesis supervisor, it is still based on subjectivity, which causes the title submitted by students to not match the field of science of the thesis supervisor so that the lecturer appointed to guide the topic of the title submitted by students has a different field of expertise from the student's title. In this determination, there are sometimes less than optimal decisions where the appointed lecturer is not in accordance with the thesis topic proposed by the student. This system is made using the AHP method so that the programmed system can be carried out more effectively. AHP method is one of the methods used in decision support systems with the calculation process by comparing each criterion.
Prediction of 2020 Mobile Sales Trends Using the Weighted Product Method Devi Permata Sari Sianturi; Jijon Raphita Sagala
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Mobile is a communication tool that has the ability like a computer with a variety of functions that is easy to carry anywhere and anytime.The current trend of cellphones is marked by the emergence of increasingly sophisticated types, models and brands with increasingly diverse features such as games, music, cameras, videos and social media. Therefore, nowadays there are many cellphone shops that sell cellphones, in addition to that the development of cellphones has made choosing a cellphone a long and complicated process to produce the best choice that suits your needs. This study aims to produce a decision for the selection of mobile phones using the weighted product method. Weighted product uses the multiplication technique to relate the attribute rating, where the rating of each attribute must be ranked first with the weight of the attribute concerned to produce the largest value that will be selected as the best alternative. The application of the Weighted Product method uses criteria, namely camera (C1), ram (C2), rom (C3), price (C4), weight (C5), and battery (C6). The results of this study indicate that the recommended alternative is A3, namely OPPO type OPPO A9 2020 with a V value of 0.093.
Decision Support System for Web-Based Employee Candidates at PT.Indomarco Prismatama Using the ELECTRE Method Raudhatul Hasanah Sinaga; Murni Marbun
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Indomaret or PT.Indomarco Prismatama is one of the largest franchised minimarket companies in Indonesia which is engaged in services and sales. Indomaret is a subsidiary of the Salim Group. The number of Indomaret Stores continues to grow, so PT.Indomarco Prismatama will need a lot of employees so PT.Indomarco has opened job vacancies to meet the specified number of employees. In recruiting prospective employees, Indomaret takes a long time to recruit prospective employees because they have to make decisions fairly and appropriately. The purpose of this study is to design and build a decision support system for recruitment of prospective employees. This system is designed using UML and is built with the programming languages ​​PHP, HTML, CSS, Javascript and MySql as the database. Then determine the prospective employees who successfully passed the selection of employee admissions at PT.Indomarco Prismatama using the ELECTRE method. The ELECTRE (Elimination and Choice Expressing Reality) method is one of the methods of ranking concept decision making, namely by using pairwise comparisons between alternatives on the appropriate criteria. The research result obtained is the decision to determine the applicants who successfully passed the selection. Of the 5 samples of potential applicants, namely A1, A2, A3, A4 and A5 the applicants who successfully passed were A5 because they had the highest score compared to the other samples.

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