Jurnal Informatika Kaputama (JIK)
Vol 5, No 1 (2021): Volume 5, Nomor 1 Januari 2021

PENGGUNAAN NEURO FUZZY PADA SISTEM MONITORING KETINGGIAN AIR SUNGAI

Tamaji Tamaji (Universitas Widya Kartika)
Yoga Alif Kurnia Utama (Unknown)



Article Info

Publish Date
12 Jan 2021

Abstract

Flood is a natural phenomenon that usually occurs in an area that is often flowed by rivers. The impact of flooding can be reduced if the community is better prepared to face the coming flood. One of the solution is to create a flood early warning system. In this study, the concept of early warning system is a river water level sensor that consist of 2 conductor plates that will produce a capacitance value when drowned into the water with a certain depth. These water level measurement values will use 3 different methods. Furthermore, those three methods will be compared to determine the best method that produces a small measurement error. The three methods are linear regression, polynomial regression, and neuro fuzzy. The results show that the measurement error which generated by linear regression was 25.45%, the measurement error that generated by polynomial regression was 13.61%, and the measurement error that generated by neuro fuzzy was 3.76%. According to these error values, the study finds that neuro fuzzy is the best method for water level measurement.

Copyrights © 2021






Journal Info

Abbrev

JIK

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

Jurnal Informatika Kaputama adalah jurnal resmi STMIK kaputama dalam bentuk bunga rampai untuk menyajikan tulisan ilmiah berbagai disiplin ilmu pengetahuan yang ada hubungan atau keterikatan dengan ilmu komputer berupa hasil penelitian lapangan atau laboratorium maupun studi pustaka. Adapun fokus ...