Similarity Analisis model naive bayes untuk identifikasi penggolongan Daya listrik di kota Lhoksumawe

Ermatita, Ermatita (2022) Similarity Analisis model naive bayes untuk identifikasi penggolongan Daya listrik di kota Lhoksumawe. Turnitin Universitas Sriwijaya. (Submitted)

Text Turnitin - untuk identifikasi penggolongan Daya listrik di kota Lhoksumawe.pdf Download (1MB)

Abstract

Electricity subsidy is provided for all 450 VA power household customers and 900 VA power household customers who are poor and disadvantaged. However, there are many facts that household customers with 450 VA power are capable and 900 VA power household customers consist of capable households, boarding houses or luxury rented. Households are able to use more electricity than poor households. This paper describe to the identification of household customers' electrical power in the Lhokseumawe city to facilitate PLN in classifying customer power by using the Naive Bayes method. Naive bayes value variables used in this study are: monthly income, highest diploma, last job, house area, subscription fee and government registered household. The classification of household customer power is grouped into three categories, namely low (450 VA down), medium (900 VA) and high (above 1300 VA).. Based on household customer data that is used as training data, the Naive Bayes method is able to classify the customer data tested. So the Naive Bayes method successfully predicts the magnitude of the probability of household electrical power with an accuracy percentage of 80%.

Item Type:	Other
Subjects:	#3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions:	09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User:	Dr Ermatita zuhairi
Date Deposited:	25 Jun 2024 06:07
Last Modified:	25 Jun 2024 06:07
URI:	http://repository.unsri.ac.id/id/eprint/147740

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