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Jurnal Teknik Informatika C.I.T. Medicom
Published by Institute Of Computer Science
ISSN : 23378646     EISSN : 2721561X     DOI : -
Core Subject : Science,
Computer Science & IT
The Jurnal Teknik Informatika C.I.T a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
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Search results for , issue "Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS)" : 5 Documents clear
Implementation of the breadth-first search method on forward-chaining inferences to diagnose autism disorders in children Dodi Nofri Yoliadi
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.339.pp58-72

Abstract

Autism is a type of mental disorder that can affect children as young as three years old, but can affect children from birth. This mental disorder is characterized by social relationships, culture, verbal and non-verbal communication, imagination, and a single attractive object. By using the Autism Disorder Diagnostic Expert System, we hope that most people will be able to attempt an autism diagnosis without an expert. This system works by answering all system questions. The "forward chaining" method is a way of drawing conclusions that starts with facts and tests hypotheses toward conclusions. To test the hypothesis, begin matching facts or statements with IF. The forward chaining method searches for a solution to a problem. The forward chaining inference and breadth first search methods were used to design this system, as well as Microsoft Access for database management systems and Visual Basic Language Programming. The expected outcome is that all users, particularly parents, will be able to easily assess the possibility of their child developing autism symptoms from an early age. The output of the system is whether there is a possibility of autism in a child based on the facts and symptoms given to the system.
Comparison of distance metric in k-mean algorithm for clustering wheat grain datasheet Suraya Suraya; Muhammad Sholeh; Dina Andayati
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.408.pp73-83

Abstract

One of the data mining models is clustering, clustering models can be used to create groupings of data. Clustering is done by creating groups of data that are close to each other. The research was conducted by clustering wheat seed datasheets.  The wheat grain datasheet contains various types of wheat data.  The purpose of this research is to create a clustering model. The algorithm used is the K-means algorithm and a comparison is made with several distance Metric algorithms. The datasheet used was tested with the K-means algorithm and tested the clustering value (k) ranging from k = 2 to k = 6. Comparison of clustering results with K-means is also done by comparing with distance metric algorithms, namely Euclidean distance, Manhattan distance, and Chebychev distance.  All testing processes are evaluated, and the evaluation is done to select many good groupings. The evaluation process is carried out using the Davis-Bouldin method. The results of the grouping that has been done, each seen Davis Bouldin evaluation. The evaluation value of Davis Bouldin is sought from the smallest value and if the evaluation result is negative, the value is solved. The research method used is Knowledge Discovery in Database (KDD). The results showed that the same datasheet and using the K-means algorithm and the same evaluation resulted in different evaluation values. The Euclidian, Manhattan, and Chebychev algorithms produce the best k value of 2, The conclusion of the wheat seed datasheet clustering research produces a value of k = 2
Classification of restrictions on community activities level in the covid-19 pandemic using fuzzy logic Abidatul Izzah; Ratna Widyastuti; Zulfa Khalida
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.454.pp108-117

Abstract

Indonesia is facing a second wave of Covid-19 cases in mid-2021. In that time, the increase reached 381 percent or almost 5 times. Therefore, the government announced the Enforcement of Restrictions on Community Activities. This is determined by the government for each city in Indonesia so it cannot be predicted by the general public. Actually,  The Restrictions on Community Activities status level determines the risk of a region's economic activities. Therefore, we need a method that can help to categorize the level of PPKM in an area based on available daily data. Thus, this study aims to create a rule model based on Fuzzy Tsukamoto logic that can help determine the level of risk of an area. Based on data on Covid-19 patients in Malang District, East Java has formed 6 fuzzy variables, each of which has 4 fuzzy sets, and 15 rules that can be used as a classification model. From the results, we obtained an accuracy value of 80%. This shows that the generated rule can properly classify the daily Covid-19 data to then estimate the next restrictions level.
Decision support system for selection of exemplary students using the analytical hierarchy process (AHP) method Susana Dwi Yulianti; Rini Nuraini; Mohammad Imam Shalahudin; M. Hadi Prayitno
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.461.pp96-107

Abstract

The problem that occurs in determining exemplary students is the length of the process of determining the assessment of exemplary students, this is due to the fact that each teacher must first select potential exemplary students. After obtaining the names of prospective new model students, the selection of model students is carried out by an assessment team from the school. The purpose of this study is to select exemplary students at the end of each semester using the Analytical Hierarchy Process method. Based on the results of the assessment using the Analytical Hierarchy Process method, the first model student was obtained by Budi Riantono with a value of 0.250949, the second model student was obtained by Putri Azzahra with a value of 0.235755, the third model student was obtained by Akhmad Wijayanto with a value of 0.204881. The results of calculations between manual calculations and calculations using a web-based application show no difference in value and ranking. Then a web-based application is made based on the results of manual calculations using the Analytical Hierarchy Process method that has been made.
Comparative analysis of the sensitivity test of the SAW and WP methods in scholarship selection Wiwit Supriyanti
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.471.pp84-95

Abstract

Decision-makers frequently use the MADM (Multiple Attribute Decision Making) method to assist in solving decision-making issues. This approach can use a variety of algorithms, including Simple Additive Weighting (SAW) and Weighted Product (WP). The challenge in this research is determining which of the SAW and WP approaches is more pertinent or acceptable for solving scenarios involving scholarship recipient selection. Five factors were taken into consideration when deciding who would receive a scholarship: academic achievement index (GPA), parents' income, past accomplishments, participation in student organizations, and the number of parents' dependents. A sensitivity test, which involves altering the weight of each test method's criterion and then comparing the percentage change between the two ways, is one method that can be used to gauge the effectiveness of the MADM method. The SAW method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.95. The WP method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.12. The total change in the findings of the sensitivity test for the SAW method is 7.64%, compared to 2.06% for the WP method. Thus, it can be inferred that the SAW approach is thought to be pertinent for addressing the issue of choosing scholarship applicants.

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