skip to main content

Aplikasi Penentuan Tarif Listrik Menggunakan Metode Fuzzy Sugeno

*Hari Santosa  -  Politeknik Negeri Semarang, Indonesia

Citation Format:
Abstract

This reasearch applied Sugeno fuzzy method for determining electricity tariff  based on the data of electric customers 450 VA and 900 VA from PLN APJ South Semarang. Tariff of  PLN clasifications calculation is done in a progressive way with three block/ classification tariff . This method is considered less representative because many users who consume less or more electrical energy (kWh) in one block/class charged or valued equally. Electric customer data during the 5 months from May to September 2012, which contains a large kWh consumption is then calculated by means of progressive tariff . The data is then performed clustering with FCM method (Mean C Fuzz) into 5 groups, thus obtained cluster centers or power usage and price rates. The power usage and price of the cluster centers are used ​​as a reference manufacture and fed into the membership function of fuzzy inference system  built by Sugeno method. This research used the triangular shape of the curve membership function.The system  built in the form of application Sugeno fuzzy method which is tested by inserting a number of sample test data . The results are  the tariff  to be paid by electricity customers . The tariff is resulting from the calculation of the system compared to the tariff calculated in a progressive way of PLN. The difference in total tariff to customers for power of 450 VA Rp 93.3107   or 0.004%, while for the 900 VA at Rp  3503.2  or 0.12 %. The tariff were calculated using Sugeno fuzzy method from this research is more fair to the consumer  there is increase  in revenue for PLN.

 

Keywords : Fuzzy Sugeno; Tariff classification; Calculation

Fulltext View|Download

Article Metrics:

Last update:

No citation recorded.

Last update: 2024-04-17 09:52:53

  1. Comparison of ANFIS and NFS on inflation rate forecasting

    Sari N.. Proceeding - 2017 5th International Conference on Electrical, Electronics and Information Engineering: Smart Innovations for Bri, 127 , 2018. doi: 10.1109/ICEEIE.2017.8328775