Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika
yenni, yusli
STKIP PGRI Sumatera Barat
Computer Science & IT

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

Found 2 Documents
Search

 1 
LOGIKA FUZZY MENENTUKAN JUMLAH PRODUKSI BERDASARKAN PERSEDIAAN DAN JUMLAH PERMINTAAN yenni, yusli
Jurnal EDik Informatika Vol 3, No 2 (2017)
Publisher : STKIP PGRI Sumatera Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (278.492 KB) | DOI: 10.22202/ei.2017.v3i2.2247

Abstract

The complicated to determine total of product will be production with stock, make the process of decision be slowly. The purpose of this research for implementated fuzzy logic Mamdani method for determine the total of production basis on the total of stock and the total of request at OSI Electronics Batam, Corp and description of accuracy level. The first process analyze the corporation data with total 12 data start from January – December 2015. The data will be processed using MATLAB application with first step is fuzzyfication defene the membership function. There are 2 information as fuzzy input request and stock and will be processed using triangle and trapezoid membership function. Next step is implicated all rules and this research using 26 rules, rule compositions and the last step is defuzzyfication using bisector method. The accuracy using fuzzy logic that was built were  91,67% and error 9,37%.
PENERAPAN LOGIKA FUZZY UNTUK PENYALURAN RASKIN BAGI MASYARAKAT KURANG MAMPU DI KECAMATAN SAGULUNG yenni, yusli; Diana, Nia
Jurnal EDik Informatika Vol 4, No 2 (2018)
Publisher : STKIP PGRI Sumatera Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (239.985 KB) | DOI: 10.22202/ei.2018.v4i2.2942

Abstract

This research aims to implement fuzzy logic to determine acceptance Beras Miskin and describe the level of accuracy. implement some of the possibilities in the selection of poor rice Admission for people less able to match. In this study, to analyze Logiak fuzzy using MATLAB software Help. There are 7 information used as input fuzzy. Input fuzzy model using triangular and trapezoidal membership functions to construct fuzzy rules on the 87 data, so there are 54 fuzzy rules. Having obtained fuzzy rules of inference process is then performed and defuzzification. Inference is the method mamdani. Results defuzzification is the value for Determining Acceptance Beras Miskin divided into two categories: Receiving and Not Receiving. Fuzzy model that has been built will be testing the model by determining the level of accuracy and error of the model. With the results of 95.4% with an error of 4.6%.
Co-Authors Diana, Nia