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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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The utilization of drone emprit in seeing the trend of increasing oil fuel through social media data Wahyuddin S; Zul Rachmat; Abdillah Abdillah; Andi Irfan; Muhammad Idris
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.v6i3.156

Abstract

This study investigates the use of drone emprit as a tool to monitor the trend of increasing fuel prices through analysis of data obtained from social media platforms using twitter. The aim of this study is to develop a new approach in understanding and forecasting fuel price fluctuations by utilizing widely available data on social media. The research combines drone emprit technology to get a visual picture of the situation at various fuel distribution sites, and integrates it with text and sentiment analysis taken from social media platforms. The methodology used includes visual data collection using drone emprit, collection of text data from social media platforms, and integrated data processing and analysis. The results of this study are expected to provide deeper insights into the factors influencing fuel price increases, including social and economic factors reflected in online conversations. By combining visual data and text analysis, the study contributes to the development of new methodologies for understanding and forecasting economic trends using innovative data sources.
The influence of system quality, information quality, and service quality on the net benefit of academic information systems with user satisfaction as an intervening variable Ivana Melinda; Amelia Setiawan; Samuel Wirawan; Hamfri Djajadikerta
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

Abstract

The increasing interest of young people to occupy tertiary institutions of education, the higher the level of competition that exists. Therefore, every tertiary institution is competing to improve the quality of education by developing Student Portal. This study aims to determine how the influence of system quality, information quality, and service quality on net benefits mediated by student portal user satisfaction. This research was conducted by collecting 59 primary data of respondents through a questionnaire. The analytical test tool used SmartPLS v.3.2.7 with the SEM (Structural Equation Modeling) analysis method. The results of this study indicate that the quality of information and service quality has an influence on student portal user satisfaction, user satisfaction has an influence on net benefits, while the effect of system quality on user satisfaction cannot be proven statistically. In this situation, system quality, information quality, and service quality have a weak effect on net benefits with user satisfaction as a mediating variable
Prototype temperature monitoring system for medicine refrigeration in the pharmaceutical installation Willy Willy; Haryono Haryono; Handri Santoso; Ito Wasito
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.v6i3.159

Abstract

Patient safety in a hospital is a healthcare service that is safe and non-harmful to patients. All components of healthcare services (doctors, nurses, and other health teams) in hospitals must be aware of and care about patient safety while in the hospital. One of the most important components is monitoring the temperature of the medicine refrigeration. Human resources or work overload often leads to the need for more monitoring of the temperature of medicine refrigeration. Therefore, IoT technology can be the solution to assist in monitoring the temperature of the medicine refrigerator. The method used in this study is observation. Based on the conducted research, it is proven that the IOT system for temperature monitoring can reduce missed temperature records. The results of this study indicate that the DHT22 sensors have good accuracy as they remain within the accuracy range of the room thermometer used as a reference,  with a temperature reading accuracy of ±1oC and a maximum temperature measurement limit of 70oC. The data collection process uses the ESP8266 as the microcontroller, which is then connected to the DHT22 module as a temperature and humidity sensor and sends a database every 30 seconds. The real-time temperature and humidity measurement results can be viewed through mobile apps using the Flutter programming language and the website. If the temperature exceeds 8oC, the fan LED will automatically turn on and send notifications to WhatsApp registered using Python and Twilio. Furthermore, the existing data can be analyzed using a machine learning model, enabling the prediction of when the refrigerator will be damaged as a preventive measure
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.
Decision Support System to assess customer satisfaction using Analytical Hierarchy Process Andriani, Wresti; Gunawan, Gunawan; Anandianskha, Sawaviyya
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: 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.v6i4.163

Abstract

Transportation is an important aspect of mobility or global movement and activities. As public transportation that can be accessed online by the public, Gojek and Grab types of transportation provide transportation services and are growing rapidly. At the time of Covid 19 around 2020, online transportation was very important and much sought after. More and more online transportation companies are appearing, especially in Tegal City, so that there are more service offerings that consumers can use. User or consumer satisfaction measurements were carried out using Fuzzy Logic Method Analytical Hierarchy Process (AHP) on 200 consumers who used Gojek or Grab or other online transportation for 3 to 4 months in 2022 in Tegal City. The results obtained by customers or consumers were satisfied with Gojek transportation at 45%, with male consumers at 67%, and Grab at 37%, with male consumers at 65%, followed by other online transportation (X and Y). These results can be used as an option for consumers who expect the best service.
Exploratory Data Analysis (EDA) methods for healthcare classification Dhany, Hanna Willa; Sutarman, Sutarman; Izhari, Fahmi
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: 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.v6i4.165

Abstract

The recovery and rehabilitation of individuals, helping them regain their physical and mental well-being. Healthcare offers comfort and relief for patients with serious or terminal illnesses, focusing on improving their quality of life and managing symptoms. It plays a role in educating individuals about health risks, disease prevention, and healthy lifestyles. Healthcare contributes to medical research and innovation, leading to advancements in treatments, medications, and medical technologies. Here are some common results and findings that can be obtained through EDA in healthcare data about EDA can reveal the age, gender, and other demographic information of patients. This information is essential for understanding the population served by a healthcare facility. EDA can help identify the prevalence of different diseases or conditions within a patient population. This can assist in resource allocation and healthcare planning. EDA can show how disease rates or healthcare utilization patterns change over time. For example, it can highlight seasonal variations in the incidence of certain diseases. EDA can be used to analyze healthcare data geospatially to identify regions with higher disease prevalence, helping in targeted interventions.
Analysis streaming application viewership with EDA Permana, Aminuddin Indra
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: 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.v6i4.166

Abstract

Streaming applications require a high amount of bandwidth to deliver high-quality media content to users. However, bandwidth is not always available or consistent, especially in remote or congested areas. This can result in buffering, lagging, or poor quality of the streaming content, which can frustrate users and affect their satisfaction and retention. Streaming applications need to minimize the delay between the source and the destination of the media content, especially for live or interactive streaming. However, latency can be affected by many factors, such as network congestion, server load, routing, encoding, etc. Predictive analysis can help to forecast the future outcomes or behaviors of the streaming data, such as the demand, the popularity, the retention, the churn, etc. For example, one can use predictive analysis to estimate the optimal pricing strategy for a streaming service, or to predict the likelihood of a viewer to cancel their subscription. Streaming application with EDA can also help to detect and resolve any issues or errors that may affect the streaming quality, such as network congestion, server load, device compatibility, etc. Streaming application with EDA can help to understand and predict the user behavior, such as the viewing duration, frequency, preference, rating, feedback, etc., of the media content consumed by the users.
Optimizing Urban Traffic Management Through Advanced Machine Learning: A Comprehensive Study Izhari, Fahmi; Dhany, Hanna Willa
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: 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.v6i4.167

Abstract

Urban transport networks are vital components of modern societies, influencing efficiency and safety. This research explores the potential of traffic data as a crucial information source for forecasting and interpreting traffic problems. Using advanced data processing, statistical analysis, and classification algorithms, the study aims to identify and forecast traffic scenarios. With an interdisciplinary approach integrating computer science, statistics, and transportation engineering, the research emphasizes a holistic perspective on traffic concerns. The study involves outlier detection, label encoding, and cutting-edge technologies like GridSearchCV and ensemble modeling. Inspired by flash flood susceptibility research, machine learning models, particularly LightGBM and CatBoost, are applied to predict traffic situations. DecisionTreeClassifier and CatBoostClassifier emerge as top performers, achieving remarkable accuracies. The evaluation goes beyond accuracy, emphasizing the nuanced understanding of algorithm strengths and limitations for effective urban transportation network management
Analysis Of Salary Of Permanent Employees And Contract Employees On The Medicom Campus Using The K – Means Algorithm Harahap, Leliana; Purba, Sartika Dewi; Situmorang, Sutrisno; Panggabean, Jonas Franky R; Sirait, Kamson
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: 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.v6i4.168

Abstract

The Medicom campus is a place of work that provides jobs to the community. In work, employee status cannot be separated, namely permanent employees and contract employees. In employee status, employee salaries can be determined. In determining employee salaries, there are several problems that can disrupt employee performance at work. For this reason, a method is needed to determine employee salaries. One method that can be used is the K-Means Clustering Algorithm. Which is considered quite effective in determining the suitability of salaries for permanent employees and contract employees. By creating clusters to make it easier for finance workers to record and determine and adjust employee salaries based on their status.

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