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Marsono Marsel.
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INDONESIA
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 4 (2022): Desember: Intelligent Decision Support System (IDSS)" : 5 Documents clear
Designing Web-Based Online Mading Application Winarsih; Sutikman
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 4 (2022): Desember: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The development of online magazine information technology in Indonesia has made a lot of progress, this has also been followed by technological developments in reducing paper use. Developments in the dissemination of event information have had a good impact on event organizers because by using e-mading information media, it is easier for people to find event information. Speed ​​in obtaining easy information is one of the main requirements for obtaining information. A web-based online magazine information system is an option that is expected to help people find it easier to find information about an event they want.
Decision support system for lecturer publication mapping using k-means clustering method Sri Sumarlinda; Wijiyanto Wijiyanto; Wiji Lestari
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 4 (2022): Desember: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Publication is an important tridharma activity for lecturers. This study aims to produce a clustering model using the K-Means algorithm which was built for ease of operation of publications. The method used is research and development which includes the stages of data collection, data preprocessing, clustering process and cluster analysis. The input data consists of 87 with 8 attributes, namely the number of journal articles indexed by Sinta, the number of journal articles indexed by Scopus, the number of citations in Scopus, the H-index in Scopus, the number of articles in indexed journals in Google Scholar, the number of citations in Google Scholar, the H-index in Google Scholar and H-index10 in Google Scholar. The K-Means algorithm is used with 3 clusters and 100 epochs. The clustering results are divided into 3 clusters, namely cluster 1 with 17 members, cluster 2 with 32 members and cluster 3 with 38 members. Clustering with 5 clusters produces cluster 1 with 5 members, cluster 2 with 12 members, cluster 3 with 20 members, cluster 4 with 18 and cluster 5 with 32 members. The results of the cluster analysis show that the clustering process with 3 clusters is improved and the academic application is better than clustering with 5 clusters.
Implementation of Artificial Neural Network on Sales Forecasting Application Ketut Jaya Atmaja; Ida Bagus Nyoman Pascima; I Made Dwi Putra Asana; I Gede Iwan Sudipa
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 4 (2022): Desember: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Sales forecasting is an effort to fulfill customer demands. The existence of a sales forecast, can help trade business owners in carrying out stock management to deal with customer demands in the future. Data owned in the past is used in predicting and estimating a condition in the future. Quantitative data used as a reference in the forecasting process can be time series data based on a certain period containing the number of sales. Artificial Neural Networks (ANN) are one of the human efforts to model the way the human nervous system functions in carrying out certain tasks. This modeling is based on the ability of the human brain to organize brain cells called neurons. Neurons are information processing units that are the basis of artificial neural network operations. ANN can be used to solve forecasting problems based on continuous data such as time series data from a sale based on a certain period. The research stages that will be carried out consist of analyzing needs, training the model, testing the model, forecasting sales.
Development of Accounting Information System at BUMDES to Enchance Financial Performance of the Village Rachmat; Michael Octavianus; Muh. Yusuf; Muh. Fahmi Basmar; Siti Nur Asia
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 4 (2022): Desember: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The issue of record management is the most important aspect of preparing financial reports. The application of information technology to the management of village financial reports is crucial to the production of village financial reports that adhere to the ideals of accountability and openness. The financial management process at BUMDes is only visible at the conclusion of a project or the end of the accounting period, i.e. once a year. Consequently, when the director requests periodic or monthly financial statements, the finance department must recap data manually and cannot print financial reports directly. The solution to the aforementioned issues is the design and construction of a financial report information system. This system is supposed to give financial information to the village in a transparent manner and make it easier to manage financial reports. This system manages user data, project data, account data, general journal data, and mandatory reports. The design method utilized in this study is the waterfall method, which takes a methodical and sequential approach to constructing a system. In this system architecture, nine blackbox tests are used to verify that the financial report information system functions have been executed properly and as planned.
Selection of Online Sales Platforms for MSMEs using the OCRA Method with ROC Weighting Bagus Kusuma Wijaya; I Gede Iwan Sudipa; Devi Valentino Waas; Putu Praba Santika
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 4 (2022): Desember: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

MSMEs are required to utilize technology to facilitate sales transactions. Multiple online sales platforms have been made available, but they must be adapted to the needs of MSMEs. The objective of this research is to apply decision support techniques using the Competitiveness Rating Analysis (OCRA) method in the final ranking process combined with the Rank Order Centroid (ROC) weighting technique, with the resulting weight value based on the priority order of the criteria, to assist MSMEs in determining online sales platforms. The research data employs six evaluation criteria: application usability (C1), transaction features completeness (C2), personal data security (C3), simplicity of payment process (C4), ease of delivery process (C5), and partner service fee providing (C6). The selection process conducted on 5 alternative online sales platforms that are widely used by MSMEs, resulting in the ranking of the best alternative online sales platforms: Tokopedia with a value of 0.423, followed by Shoope with a value of 0.207, Instagram with a value of 0.121, Facebook marketplace with a value of 0.109, and WhatsApp as the final ranking order. Identifying the online sales platform can aid MSMEs in determining the most suitable sales platform for promoting greater sales and facilitating transaction processes.

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