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Optimasi MWMOTE pada data tidak seimbang menggunakan complete linkage

MWMOTE optimization for imbalanced data using complete linkage

Department of Informatics, Institut Teknologi Sumatera. Jl. Ryacudu, Lampung Selatan, Indonesia 35365, Indonesia

Received: 11 May 2020; Revised: 7 Dec 2020; Accepted: 18 Jan 2021; Published: 30 Apr 2021; Available online: 20 Apr 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Imbalanced data can result in classification errors, such as in WMMOTE, and can decrease its performance and accuracy. Clustering in MWMOTE can be optimized to improve synthetic data generation and improve MWMOTE performance. This study aims to optimize the MWMOTE algorithm's performance in the clustering process in making synthetic data with complete linkage (CL). The dataset used a variety of data ratios to handle imbalanced data. The decision tree was used to determine the performance of MWMOTE and CL-MWMOTE oversampling. CL-MWMOTE evaluation results provide better and optimal performance than MWMOTE and increase the precision, recall, f-measure, and accuracy of 0.53 %, 0.67 %, 0.66 %, and 0.67 %, respectively.

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Data Analysis: MWMOTE optimization for imbalanced data using complete linkage
Subject imbalaced; clustering; complete linkage; optimization; oversampling
Type Data Analysis
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Keywords: imbalanced data; clustering; complete linkage; optimization; oversampling
Funding: Institut Teknologi Sumatera, Indonesia

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