OPTIMASI RANDOM FOREST TERHADAP DATA TELCO CUSTOMER CHURN MENGGUNAKAN FIREFLY ALGORITHM

Abril Muhammad Fikar Wijaya, . (2024) OPTIMASI RANDOM FOREST TERHADAP DATA TELCO CUSTOMER CHURN MENGGUNAKAN FIREFLY ALGORITHM. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Customer churn is the percentage of customers who have stopped or switched using a product/service periodically. The telecommunications industry experiences an average annual churn rate of 30-35%, and acquiring new customers is 5-10 times more expensive than retaining existing ones. Predicting churn can be used to help companies identify churners earlier before customer defection occurs. The objective of this research is to perform classification using the Random Forest method combined with the Firefly Algorithm to enhance accuracy. The classification evaluation results using the confusion matrix show an accuracy of 80,48%, precision of 77%, recall of 82,7%, and an F1-score of 79,71% before optimization. After optimization using the Firefly Algorithm, the accuracy increased to 82,08%, precision to 77,7%, recall to 86,2%, and F1-score to 81,6%.

Item Type:	Thesis (Skripsi)
Additional Information:	[No.Panggil: 1910511061] [Pembimbing 1: Iin Ernawati] [Pembimbing 2: Muhammad Adrezo] [Penguji 1: Bayu Hananto] [Penguji 2: Catur Nugrahaeni Puspita Dewi]
Uncontrolled Keywords:	Customer Churn, Classification, Random Forest, Firefly Algorithm
Subjects:	Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Abril Muhammad Fikar Wijaya
Date Deposited:	20 Feb 2024 03:11
Last Modified:	20 Feb 2024 03:11
URI:	http://repository.upnvj.ac.id/id/eprint/29153

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