Article Per Year (5 Year)
p-Index From 2020 - 2025
1.066
P-Index
This Author published in this journals
All Journal Jurnal Komputer, Informasi dan Teknologi Jurnal Komputer Indonesia
Suryana , Eko
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Komputer Indonesia

 1 
Application of the Naive Bayes Method in Expert Systems for Diagnosing Gingivitis Fernando, Rendy; Suranti , Dewi; Suryana , Eko
Jurnal Komputer Indonesia Vol. 1 No. 2 (2022): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v1i2.24

Abstract

The number of program activities at the Beringin Raya Health Center in Bengkulu City is sometimes not proportional to the number of doctors in the puskesmas, so not all patients can have health consultations, especially about gingivitis. Gingivitis is a disease caused by a bacterial infection which causes the gums to swell due to inflammation. Therefore we need an application that can help the process of diagnosing gingivitis based on the symptoms experienced by the patient, so that the initial diagnosis experienced by the patient can be known. The expert system for diagnosing gingivitis at the Beringin Raya Nursing Health Center in Bengkulu City was made using the PHP programming language and MySQL database, which can be accessed online via the https://sistempakargingivitis.my.id/ link. The expert system for diagnosing gingivitis in the treatment of Beringin Raya, Bengkulu City, has implemented the Naive Bayes Method to represent, combine, and propagate uncertainty, which has several intuitive characteristics according to the way of thinking of an expert. The training data used is 11 data which is used as the basis for the probability value of each symptom in the disease to carry out a consultation diagnosis. Based on the consultation with the selected symptoms, namely G1, G2, G3 and G4, the diagnosis of Nonvital Teeth disease (Dead Teeth) was obtained with a bayes value of 0.2045454541875. Based on the system testing that has been done, it can be concluded that the functionality of the application has been running well and this expert system can provide consulting results based on the symptoms selected by the user through the stages of the Naive Bayes method
Application of the Forward Chaining Method in Building a Student Counseling Expert System at SMAN 03 Bengkulu City Adriansyah, David; Asnawati, Asnawati; Suryana , Eko
Jurnal Komputer Indonesia Vol. 1 No. 1 (2022): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v1i1.26

Abstract

Implementation of guidance and counseling in schools has a very important role in realizing students as individuals who are independent, responsible, creative and productive workers. Guidance and counseling for students is needed in making appropriate choices or to solve problems faced by students. The student counseling expert system at SMA Negeri 3 Bengkulu City was created to facilitate the counseling process for students in schools based on the problems and symptoms experienced by students. This expert system adopts the knowledge of the BK teacher, where there are 25 problems that often occur in schools. In the process of diagnosing the results of student consultations, the application will select the problems experienced by students, then choose the symptoms experienced by students, thus displaying the possible percentage level of the problem. The student counseling expert system at SMA Negeri 3 Bengkulu City was created using the Visual Basic .Net programming language. Based on the tests that have been carried out, the functionality of the student counseling expert system at SMA Negeri 3 Bengkulu City runs as expected, and the application is able to display the results of student counseling consultations through the possible percentage levels of problems and symptoms experienced by students.
Co-Authors Adriansyah, David Asnawati Asnawati Fernando, Rendy Handayani, Elya Imansyah, Dwi Ristika, Ristika sapri sapri Suranti , Dewi Windarman, Windarman