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Ratih Titi Komala Sari
Program Studi Sistem Informasi, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Sistem Pakar Diagnosa Kerusakan VGA dengan Metode Certainty Factor dan Algoritma K-Nearest Neighbor (K-NN) Rizal Maulana Yusuf Effendi; Septi Andryana; Ratih Titi Komala Sari
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 5 No 1 (2021): JANUARI-MARET 2021
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v5i1.168

Abstract

VGA (Video Graphics Array) is a Video adapter which is very useful for improving the performance and quality of the visual process on a computer, but sometimes there is often a malfunction that cannot be identified the type of damage. The problem is the lack of media to identify the damage that occurs during visual processing. Therefore, the authors created an expert system that can diagnose the type of damage to VGA using the Certainty Factor method as a calculation, using UML modeling as the work process flow of the system on the website, and also equipped with the KNN (K-Nearest Neighbor) algorithm as machine learning. so that it can build an expert system with the PHP programming language MySQL database. The method used in testing is the black box method in testing the system used. The results that can be concluded from this study are; 1) The diagnostic system for detecting damage to the VGA uses the K-Nearest Neighbor Algorithm as machine learning and the Certainty Factor Method as a calculation medium in determining the distance from the type of damage and has suggestions for further actions to deal with and prevent the damage from occurring and also has other possible damage things that are similar to the damage suffered can be accessed quickly and easily to understand, in making scientific research carried out sequentially to facilitate the process, and 2) In addition to diagnosing, there are several additional menus that can be accessed such as the Prediction menu which functions to displays the max and min limits of the temperature of a product, Product Info which functions as a quality product recommendation, and a description that contains a post of details of the damage that can be studied and is expected to help users find solutions to their problems.
Aplikasi Perbandingan Pemilihan Guru Private Homeschooling menggunakan Algoritma Simple Additive Weighting (SAW) dan Weight Product Berbasis Web Raka Adji Setiawan; Fauziah Fauziah; Ratih Titi Komala Sari
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 5 No 1 (2021): JANUARI-MARET 2021
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v5i1.195

Abstract

This study aims to compare the selection of private homeschool teachers using the Simple Additive Weighting (SAW) and Weight Product (WP) algorithms, the criteria that have been taken by the author to calculate their weight in selecting private teachers who excel and provide convenience with an assessment based on criteria. In this effort, the authors can build a private teacher selection system with the Simple Additive Weighting (SAW) algorithm to find the total weights of the teacher performance rating for each alternative on all attributes and compare it to the Weight Product (WP) algorithm using the multiplication technique to link the attribute rating. where the attribute type rating must be ranked first with the associated weight attribute. From the results of this study, the authors have described how the design and application of SAW and WP in making a Decision Support System in selecting private homeschooling teachers.
Co-Authors Fauziah Fauziah Raka Adji Setiawan Rizal Maulana Yusuf Effendi Septi Andryana