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All Journal Informasi Interaktif Jurnal Teknimedia: Teknologi Informasi dan Multimedia
Khoironi, Khoironi
MTI Universitas Amikom Yogyakarta
Computer Science & IT Control & Systems Engineering Engineering

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CLUSTERING DATA NILAI ADAPTIF SISWA MENGGUNAKAN ALGORITMA K-MEANS Khoironi, Khoironi; Kusrini, Kusrini; Arief, Rudyanto
Informasi Interaktif Vol 5, No 2 (2020): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

Student success rates and low student failure rates are a reflection of the quality of education, at this time the value does not determine the success of students in the next stage, but the uniqueness in itself that is represented in each grade they achieve, maybe students fail in mathematics but he succeeded in chemistry. it does not indicate he failed but he has shown its strengths in other respects namely other subjects, therefore this study seeks to find the positive side of students by classifying the value of subjects achieved by implementing the K-Means method in its application which will provide cluster output of each subject. K-Means method was chosen because this method can group items in k groups (where k is the number of groups or clusters desired, so the results of this termination are clusters of student grades grouped by subjects. K-Means is effective for clustering data by showing good accuracy value, this is indicated by the results of evaluations using Bouldin index davies on student data using K-Means which is equal to -1,478.   Keywords:  Cluster, K-Means, Education, Davies-Bouldin. 
Sistem Pakar Diagnosa Penyakit Ginjal dengan menggunakan Algoritma Bayes Khoironi; Abdul Rosyid; Muhammad Azmi
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 1 No. 2 (2020): Desember 2020
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (201.674 KB) | DOI: 10.46764/teknimedia.v1i2.24

Abstract

Expert systems are computer-based systems that use knowledge, facts and reasoning techniques to solve problems that usually only an expert can solve in a particular field. Expert systems provide added value to technology to assist in an increasingly sophisticated information age. This expert system application produces output in the form of possible kidney disease based on the symptoms felt by the user. This system uses the Bayes method. The system will look for the highest probability value, from various possible types of disease based on the information requested by the user and exclude the user. The system for diagnosing kidney disease is determined by determining the type of disease based on the user's symptoms. The resulting Bayes value is between 0 and 1. If the resulting Bayes value is continuous, the higher the certainty that the disease is affected. In fact, if the resulting Bayes value is continuous, the less certain the disease involved is.
Co-Authors Abdul Rosyid Arief, Rudyanto Kusrini, Kusrini Muhammad Azmi