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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Puji Susanti
Universitas Darwan Ali, Sampit
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Penerapan Fuzzy Mamdani Dalam Pemilihan Murid Teladan Pada Sekolah Paud Harmony Kotawaringin Timur Puji Susanti; Sherly Mudrika Bahri
Journal of Information System Research (JOSH) Vol 2 No 2 (2021): Januari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (624.011 KB)

Abstract

Fuzzy logic is a method used to map an input space into an output space. Fuzzy logic theory is known as fuzzy set (fuzzy set). One of the applications of Fuzzy is used to facilitate the selection of exemplary students. Previously, this school had difficulty in reviewing students' achievements and examples. To solve this problem, a Decision Support System (DSS) was applied using the Fuzzy Mamdani method. Fuzzy method is more effective than manual selection because it doesn't take long. This study will discuss the use of the fuzzy mamdani logic method in determining the category of (i) model or non-exemplary students at HARMONY Sampit PAUD School, East Kotawaringin. The problem to be solved is how to determine students (i) Exemplary or Not Exemplary in Study Group B by using three input variables, namely Report Card Value, Attendance and Attitude Value. The first step in solving the problem in determining the student (i) model or not using the fuzzy mamdani method is to determine the input and output variables which are firm sets. The second step is to change the input variables into fuzzy sets with the fuzzification process, then the third step is processing the fuzzy set data. And the last or fourth step is to change the output into a firm set by defuzzification with the centroid method, so that the desired results will be obtained in the output variable. The results of the calculation using the fuzzy mamdani method for the variable value of report cards 4, the variable value of attendance value 2, the value of attitude 4 is 3.5
Perbandingan Algoritma K-Means Dan K-Medoids Untuk Pemetaan Hasil Produksi Buah-Buahan Eka Prasetyaningrum; Puji Susanti
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6477

Abstract

In general, in 2019-2020 fruit production in Kotawaringin Timur district has decreased. Based on the data on fruit production, the amount of fruit production decreased, resulting in scarce fruit stocks and expensive fruit prices. Based on these problems, fruit production will be grouped according to the type of production in East Kotawaringin district using data mining techniques with clustering techniques using the K-Means algorithm and K-Medoids algorithm in order to optimize and increase fruit production. The results of grouping fruit production will be divided into 3 clusters, namely the highest cluster, the medium cluster, and the lowest cluster, making it easier for the Food and Agriculture Security Service in East Kotawaringin district to calculate and increase agricultural yields, especially in the horticulture sector. Based on the test results using data in 2019-2022, totaling 29 data in the Rapidminer application version 9.9 by comparing the DBI (Davies Bouldin Index) values of the two algorithms with so that the conclusion in determining the best value for the number of clusters (K) is that the fourth experiment shows 0.296 DBI (Davies Bouldin Index) values with six clusters. If the DBI value is smaller or closer to 0, then the cluster results obtained are more optimal. The results obtained in the K-Means algorithm get a smaller DBI (Davies Bouldin Index) value with a value of 0.296 while the K-Medoids algorithm results with a DBI (Davies Bouldin Index) value of 0.507. The best algorithm for clustering fruit production in Kotawaringin Timur district is the K-Means algorithm based on the DBI values obtained.
Co-Authors Prasetyaningrum, Eka Sherly Mudrika Bahri