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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal KomtekInfo
Safitri, Wifra
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Analysis of the Perception of Coming Communities Against Local Wisdom Mamdani's Fuzzy Inference System (FIS) Method safira, silky; Safitri, Wifra
Jurnal KomtekInfo Vol 6 No 2 (2019): Jurnal KomtekInfo, 2019
Publisher : Lembaga Penelitian Dan Pengabdian Masyarakat UPI-YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v6i2.907

Abstract

Logika fuzzy dianggap mampu untuk memetakan suatu input kedalam suatu output tanpa mengabaikan faktor – faktor yang ada. Logika fuzzy sangat fleksibel dan memiliki toleransi terhadap data-data yang ada. Dengan menggunakan logika fuzzy, akan dihasilkan suatu model dari suatu sistem yang mampu memperkirakan bagaimana persepsi masyarakat pendatang terhadap kearifan lokal. Faktor – faktor yang mempengaruhi dalam menentukan persepsi masyarakat pendatang terhadap kearifan lokal dengan logika fuzzy salah satunya adalah Sikap masyarakat pendatang. Kehidupan sosial budaya masyarakat ditunjukkan dengan banyaknya kaitan terhadap kehidupan sosial lainnya, seperti ideologi, pola hidup, dan ekonomi. Ini berarti perubahan kehidupan sosial budaya yang satu akan berpengaruh terhadap kehidupan social budaya yang lain. Sistem ini dibuat agar masyarakat dapat mengetahui, mempelajari serta megkaji ragam kearifan local, mengkaji peran penduduk pribumi dan pendatang dalam melestarikan kearifan lokal dan mengkaji stategi penduduk pribumi dan pendatang dalam membatasi konflik dan lain sebagainya dengan menerapkan metode fuzzy mamdani diharapkan dapat memberikan keputusan yang baik dalam menanggapi persepsi masyarakat pendatang terhadap kearifan lokal Di Kinali Pasaman Barat.
Fuzzy Neural Network (FNN) Pada Proses Identifikasi Penyakit ISPA Saputra, Dhio; Yanto, Musli; Safitri, Wifra; Mayola, Liga
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3020

Abstract

ISPA is a disease that can affect anyone from children, adolescents, adults, and even the elderly. The causes experienced by sufferers of this disease are quite simple, such as fever, runny nose, and cough. The discussion in this paper describes the process of ISPA disease identification by developing a Fuzzy Neural Network (FNN) model. The process will be optimized using Fuzzy Logic to form rules for the diagnostic process, then proceed with an Artificial Neural Network (ANN). This model can maximize the performance of ANN in the identification process so that the output given is quite precise and accurate. The results provided by Fuzzy Logic can describe the clarity of the rules in diagnosis by presenting several rules (rules) that are presented from the Fuzzyfication process to the Defuzzyfication process. The output obtained from the ANN process also shows quite perfect results with an average error value based on MSE of 0.00912 and accuracy value of 91.96%. With these results, it can be stated that the FNN model can be used in the ISPA diagnosis process so that the presentation of this paper aims to provide an alternative in the identification process
Co-Authors Mayola, Liga safira, silky Saputra, Dhio Yanto, Musli