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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 157 Documents
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Implementation of data mining to estimate the need for toast bread supply at junction cafe using the multiple linear regression method Situmorang, Sutrisno; Purba, Sartika Dewi; Harahap, Leliana; Sirait, Kamson; Panggabean, Jonas Franky Rudianto
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.248

Abstract

Junction Cafe Medan, which is managed by individuals, has a large supply of bread services with different specifications. The inventory system for toasted bread at Junction Cafe Medan still uses a manual system in data processing. Handling data with this system has several obstacles, including causing shortages and excesses of bread stock, impacting guests due to running out of bread stock, excessive costs incurred for stocking bread, and lack of accuracy in recording incoming and outgoing bread stock resulting in shortages and errors in ending stock inventory. Based on this research problem, a data mining application is needed that is capable of estimating bread supplies at Junction Café Medan, where each Bread inventory data at Junction Café Medan will be calculated using one of the data mining methods that is capable of estimating bread supplies based on bread usage by applying the Regression method Multiple Linear The result of this research is a data mining application that uses the Multiple Linear Regression method which is able to solve the bread stock inventory problem at Junction Cafe Medan by estimating bread stock inventory more quickly and accurately
Mental disorder classification with exploratory data analysis (EDA) Simangunsong, Juanto; Simanjuntak, Mutiara S; Simanjuntak, Nurmala Dewi
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.252

Abstract

Classification of mental disorders is the process of grouping mental disorders into categories based on their symptoms, causes and consequences.  EDA is a data analysis strategy that emphasizes open-mindedness, creativity and diverse perspectives. EDA aims to explore as much data as possible, without imposing previous assumptions or models, until a coherent, coherent story emerges. EDA can help generate new hypotheses, identify patterns and outliers, and uncover underlying structures and relationships in data. This paper shows how EDA can be used to analyze and understand mental disorders data from a variety of sources and perspectives. We used EDA methods to explore the characteristics, prevalence, and distribution of mental disorders, as well as the relationships and interactions between mental disorders and other variables. We also compared EDA results with mental disorder classification systems such as the Diagnostic and Statistical Manual of Mental Disorders (DSM). We show that EDA can provide a more comprehensive and nuanced understanding of mental disorder data, as well as highlight the challenges and limitations of mental disorder classification. We hope this paper will illustrate the potential and benefits of EDA for mental disorders research and practice
Web-based development of room management information system at Universitas Pertahanan using Rapid Application Development Anjani, Prasashti Alya; Saragih, Hondor; Hidayati, Ajeng; Anindito
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.254

Abstract

Unhan RI is an educational institution responsible for facilitating the continuity of student’s academic activites, including the scheduling process that managed by the department’s staff. The scheduling process requires components such as courses, lectures, time slots, and the classrooms. The number of available classrooms at Unhan RI is less than it need. Therefore, a proper scheduling system is necessary to manage scheduling and avoid conflicts between schedule. The development of information management system for administration’s process that are still done manually are needed in this digital era. Because the large and continuously growing amount of data is difficult to process manually. The development is using Rapid Application Development method. This method is chosen because of the requirement time for the developing is short.  By using the room management information system, the process of scheduling courses and managing rooms can be done easily. This system provides information of room availability and ongoing activites, helping to prevent scheduling conflicts.
Comparison of Naïve Bayes Classifier and Support Vector Machine for sentiment analysis on civil military relations conflict among Rohingya refugees as recommendation for defense policy making Putri, Nanda Selviana; Saragih, Hondor; Heikhmakhtiar, Aulia Khamas
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.255

Abstract

This research focuses on the evaluating the performance of various sentiment analysis techniques using the Naive Bayes Classifier and Support Vector Machine in identifying civil-military conflicts among Rohingya refugees. The goal is to assist leaders in formulating defense policies. This research uses text data from news sources on Twitter, with a total of 5018 data that have been processed to become clean data, then divided into 1004 test data and 4018 training data to be classified using the Support Vector Machine and Naive Bayes methods. This research analyzes the sentiment and polarity of public opinion related to the issues that occur in this situation. The results of the sentiment analysis from the two methods are then classified using the Support Vector Machine and Naive Bayes methods, and then compared to determine which method is more effective in capturing the complex dynamics of sentiment. The findings of this research indicate that the Support Vector Machine method has a higher accuracy in identifying sentiments related to the civil-military conflict among Rohingya refugees, with an accuracy of 87.95%, compared to the Naive Bayes Classifier with an accuracy of 85.16%. The analysis results in the form of frequently occurring words in the true positive word cloud, namely apology, human, angry, and solidarity, are handed over to experts to be formulated into recommendation sentences and can be used to assist in the formulation of policies for defense decision-makers in more effectively addressing the Rohingya refugee issue.
Development of agile-based website and field person application for construction project data management Manullang, Jontinus; Sirait, Kamson; Purba, Sartika Dewi; Manik, Aditiarno; Lubis, Harmoko
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.256

Abstract

This research discusses the creation of a website and Field Person application designed to assist the management of construction project data processing. This system allows company leaders to monitor projects in real-time and assist field heads in compiling work reports. The main functions implemented include material management, shopping data, equipment data, work progress data, incoming funds, material usage, material requests, wage requests, and wage payments. This research uses an object-oriented software development methodology with an Agile approach to ensure flexibility and responsiveness to changing user needs, and offers innovative solutions in construction project management by utilizing technology to improve efficiency and accuracy in project data management.
Implementation of AHP method in decision support system for AC brand selection at PT. Gemilang Haris, Muhammad; Zulherry, Andi; Limbong, Isman Efendi; Tanjung, Mahardika Abdi Prawira
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 3 (2024): 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.v7i3.257

Abstract

The selection of the optimal AC brand for PT Gemilang faces complex challenges as it involves the evaluation of various criteria such as quality, cost, energy efficiency, and after-sales service. This research aims to apply the Analytic Hierarchy Process (AHP) method to determine the best AC brand based on these criteria. The AHP method is used to develop a comparison matrix, calculate the weights of criteria and alternatives, and check the consistency of the results. The analysis results show that Brand B has the highest final weight, making it the most optimal choice compared to the other alternatives. The implications of this study show that the AHP method can be effectively used for multi-criteria decision-making in product selection, providing data-driven recommendations and reducing subjective bias in the selection process. This research makes a significant contribution to a more structured decision-making practice at PT Gemilang.
Naïve bayes on diagnostic expert system for menstrual disorders Adie Wahyudi Oktavia Gama; I Nyoman Gde Artadana Mahaputra Wardhiana
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 2 (2023): 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.v6i2.130

Abstract

Menstrual disorders often occur in women in their active reproductive period. This disorder is caused by various factors such as hormonal, ovarian, hypothalamus, and other factors. Thus, it can be stated that the causes of menstrual disorders are very broad and varied. Lack of public knowledge and awareness about women's reproductive health can have serious consequences for sufferers, such as difficulty getting pregnant, infertility, tumors, and even cancer. To be able to help people with menstrual disorders quickly and efficiently, an expert system is needed to make an initial diagnosis of menstrual disorders. In addition to helping the community, expert systems can assist experts or medical personnel in determining the initial diagnosis/anamnesis so that the evaluation of abnormal uterine bleeding can result in appropriate treatment. In this study, researchers built an expert system with the Naïve Bayes web-based method to get an initial diagnosis in the form of a percentage of possible diseases suffered by users based on the selected symptoms. By testing the system, it can be concluded that the system built by applying the Naïve Bayes method can accurately diagnose types of menstrual disorders with a percentage of 84% based on data and symptoms experienced by patients. Based on other tests, the system functions as it should, and the community considers the system acceptable, good, and proper.
Enhancing field project management with agile-based digital tracking and reporting system Manullang, Jontinus; Firdaus, Muhammad Huda; Sigalingging, Lasrida
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 4 (2024): December: Intelligent Decision Support System
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i4.258

Abstract

This study introduces the Project On-site Tracker, a digital solution designed to enhance the efficiency and accuracy of recording and reporting project activities in the field. The research problem addressed the inefficiencies of traditional methods in construction project management, such as delayed data collection and manual reporting processes. The objective was to develop an integrated web and mobile application using Agile methodology, enabling real-time data recording, automatic report generation, and data analysis for informed decision-making. The system design utilized web technologies for backend operations and an Android framework for mobile accessibility, ensuring seamless data management across diverse project environments. Evaluation results demonstrated improved operational efficiency, faster decision-making capabilities, and enhanced transparency in project management processes. The implications suggest that adopting agile development methodologies in information systems can significantly improve responsiveness to user needs and project adaptability. This digital solution not only streamlines project management workflows but also lays groundwork for future enhancements in integrating advanced analytics and expanding compatibility with existing management systems.
Implementation of simple additive weighting in determining employee performance based on android at BSI Bank KCP Perbaungan Tanjung, Mahardika Abdi Prawira; Syafii, Rahmad
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 4 (2024): December: Intelligent Decision Support System
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i4.261

Abstract

This study aims to develop and implement a Decision Support System (DSS) based on the Simple Additive Weighting (SAW) method for employee performance evaluation at BSI Bank KCP Perbaungan. The main problems faced by the bank are subjectivity and inefficiency in performance evaluation using manual methods. With this Android-based DSS, employee performance evaluations can be carried out more objectively and transparently, based on criteria such as productivity, work quality, attendance, and teamwork ability. This study involves data collection through observation and interviews with bank management to determine the weights of the criteria used in performance evaluation. The SAW method is then applied to process employee performance data and generate a final score used to identify the best employees. The results show that the SAW method is effective in improving the accuracy and speed of performance evaluations. The implementation of the Android-based DSS simplifies management in handling employee data and generating real-time performance reports. This study concludes that the use of the SAW method in an Android-based DSS can reduce subjectivity in evaluations and improve decision-making efficiency at BSI Bank KCP Perbaungan.
Prediction of price decrease in used cars using decision tree in Habib Car Showroom Ardiansyah, Muhammad; Tanjung, Mahardika Abdi Prawira
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 4 (2024): December: Intelligent Decision Support System
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i4.262

Abstract

This study aims to predict the decline in the price of used cars using the Decision Tree method at the Habib Car Showroom. The main problem at the Habib Car Showroom is that there is no system that can predict the price of cars at the Habib Car Showroom. With this research, the prediction of car prices at the Habib Mobil Showroom will be more objective and very helpful for the Habib Car Showroom. This study predicts through criteria and any damage to the cars at the Habib Car Showroom, such as year of manufacture, engine condition, and body condition. Furthermore, this Decision Tree method is useful for calculating how much the price will drop through the damage to the car that will be seen in the condition of the damage. This study will produce objective and accurate results according to the damage to the car or not damaged to the car, and this study can help the Habib Car Showroom predict prices easily, objectively, and accurately.

Page 13 of 16 | Total Record : 157

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