Comparative Evaluation of Cheng and Church and BCBimax Biclustering Algorithms on Sustainable Development  Goals Data

Destriana Aulia Rifaldi; Indahwati Indahwati; Muhammad Nur Aidi

doi:10.31764/jtam.v10i4.40389

Comparative Evaluation of Cheng and Church and BCBimax Biclustering Algorithms on Sustainable Development Goals Data

Destriana Aulia Rifaldi, Indahwati Indahwati, Muhammad Nur Aidi

Abstract

Sustainable Development Goals (SDGs) comprise multidimensional indicators that reflect various aspects of sustainable development and often exhibit heterogeneous patterns across countries. Although biclustering has been widely applied to analyze high-dimensional data, comparative studies evaluating the performance of the Cheng and Church (CC) and Binary Inclusion-Maximal Biclustering (BCBimax) algorithms on SDGs data remain limited. Therefore, this study compares the performance of the CC and BCBimax algorithms in identifying local patterns in the 2024 SDGs achievement data. The dataset consists of 167 countries and 17 SDG indicators obtained from the Sustainable Development Report. Data exploration was conducted using heatmaps and PCA biplots, followed by biclustering analysis. The CC algorithm was applied to standardized numerical data, while BCBimax was implemented on binarized data using several thresholding approaches. Algorithm performance was evaluated using the number of biclusters, Average Squared Residue (ASR), Jaccard Index, and row membership coverage. The results indicate that the optimal CC model was obtained at δ = 0.14, producing 7 biclusters with complete coverage of all 167 countries and an ASR value of 0.2465. In contrast, the optimal BCBimax model generated 38 biclusters with a lower ASR value of 0.0450, indicating greater homogeneity, but covered only 112 countries. The Jaccard Index of 30.61% suggests low similarity between the bicluster structures produced by the two algorithms. Overall, CC provides broader coverage and better represents numerical data patterns, whereas BCBimax produces more homogeneous and specific biclusters.

Keywords

ASR; BCBimax; Biclustering; Cheng and Church; SDGs.

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DOI: https://doi.org/10.31764/jtam.v10i4.40389