Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Jurnal Teknik Informatika (JUTIF)
Jati Sasongko Wibowo
Program Studi Teknik Informatika, Universitas Stikubank, Indonesia
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
COVID-19 DIAGNOSIS EXPERT SYSTEM WITH CERTAINTY FACTOR METHOD Novia Nur Arifah; Jati Sasongko Wibowo
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.365

Abstract

Covid-19 is a new type of virus that is currently a pandemic in almost all countries. The limitations of experts for diagnosis and recommending rapid action to patients who are diagnosed positively, as well as the limitations of the expert area in the environment wh ere the Covid-19 outbreak occurred. This expert system aims as an early diagnosis system for Covid-19 so that patients can receive treatment immediately, and help stop the wider spread of the virus. Using predetermined parameters and there is also a system that can later make it easier for users to find out the diagnosis of Covid-19 caused by the coronavirus. The method used for this expert system research is Certainty Factor (CF). This method aims to showed how much the confidence value is based on the clinical parameters given by MYCI. The advantage of the Certainty Factor method is that it can be measured something that is certain or uncertain. And to maintain accuracy, Certainty Factor can only process two data. The Expert System uses the Certainty Factor (CF) method to diagnose Covid-19 disease, starting with the collection of symptom data and giving confidence values by the expert on each symptom, then the symptom data input stage from the user and the system will calculate based on the Certainty Factor rule, multiplying the weight value namely user CF and expert CF, combining the results of the multiplication of each symptom, so that a percentage of confidence is obtained as the final diagnosis result. After calculating the accuracy test of the 3 rule system with 99% positive Covid-19 results, 48% most likely Covid-19 and 29% negative Covid-19.
DECISION SUPPORT SYSTEM FOR DETERMINING CUSTOMER FEASIBILITY TO GRANT CREDIT ON SAVING AND LOAN COOPERATIVES USING COMPARISONS OF TOPSIS AND SAW METHOD Dian Ayu Wigasari; Jati Sasongko Wibowo
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.369

Abstract

Cooperative is one of the institutions engaged in the financial sector with the business of providing savings and loan funds to its members to improve the welfare of the community's economy however currently there are still many errors that occur in the calculation process and it takes a very long time, so we need a system that can simplify the selection process in determining a decision. This research aims to support a decision support system for determining the eligibility of customers by comparing the two, so that it can be determined which method is more relevant to be implemented in the case of customers selection in grant credit. In its application, this research uses a comparison of two methods, namely the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW) methods. At the system design stage, the design model and system development flow are used as an illustration in the operation of the decision support system that has been carried out based on system analysis. Based on the results of the research and discussion, it can be concluded that the comparison of TOPSIS and SAW methods has inequality in the final results that can be seen from the ranking process. The test results show that the SAW method produces a value of 0.82% for customers named lintang with the highest, while TOPSIS with a value of 0.65% for highest value, so that the SAW method is more recommended in providing solutions to the decision support system.
Co-Authors Dian Ayu Wigasari Novia Nur Arifah