Implementation of Factor Analysis and BiClustering in Classifying Multidimensional Under-Five Poverty in East Nusa Tenggara

https://doi.org/10.22146/ijccs.70433

Rahmadathul Wisdawati(1), Rani Nooraeni(2*), Bagaskoro Cahyo Laksono(3), Bintang Izzatul Fatah(4)

(1) BPS-Statistics of Karimun Regency
(2) Polytechnic of Statistics STIS, East Jakarta
(3) Polytechnic of Statistics STIS, East Jakarta
(4) Polytechnic of Statistics STIS, East Jakarta
(*) Corresponding Author

Abstract


Under-five poverty is a condition where the needs of toodlers are not met, resulting in undernourished children and unable to reach their full potential in the social sphere. East Nusa Tenggara is a province that still faces the biggest nutritional problems in Indonesia in 2019. This study aims to explain the variables that form toodlers multidimensional poverty in East Nusa Tenggara (ENT), form the Multidimensional Under-Five Poverty Index (MUPI), and compare the results of index formed with the results of bicluster. Data source used in this study is SUSENAS KOR 2019. The analytical method used is a factor and bicluster analysis. The results shows that 11 multidimensional poverty indicators form three dimensions, namely the Adequate Food and Beverage Facility Factor, Health Protection Factor, and Housing and Nutrition Factor, which is used to form the index. Based on regional grouping, there are five areas with low MUPI scores, fourteen areas with medium MUPI scores, and three areas with high MUPI scores. However, biclustering results show that there are two areas with low poverty category, thirteen regions with moderate poverty category, and seven regions with high poverty category. The result of the comparison of MUPI grouping with the biclustering method obtained different results based on the composition of the resulting area.


Keywords


Under-five poverty; Factor Analysis; BiClustering

Full Text:

PDF


References

[1] UNICEF. (2020). Situasi Anak di Indonesia - Tren, Peluang, dan Tantangan dalam Memenuhi Hak-hak Anak. Jakarta: UNICEF Indonesia.

[2] Badan Pusat Statistik. (2017). Analisis Kemiskinan Anak dan Deprivasi Hak-hak Dasar Anak di Indonesia. Jakarta: Badan Pusat Statistik.

[3] OECD. (2019). Social Protection System Review of Indonesia, OECD Development Pathways, OECD. Paris: OECD Publishing.

[4] Alamsyah, D., Mexitalia, M., Margawati, A., Hadisaputro, S., & Setyawan, H. (2017). Beberapa Faktor Risiko Gizi Kurang dan Gizi Buruk pada Balita 12-59 Bulan (Studi Kasus di Kota Pontianak). Jurnal Epidemiologi Kesehatan Komunitas, 2(1), 46. https://doi.org/10.14710/jekk.v2i1.3994

[5] Aulia, L. A., & Wulansari, I. Y. (2020). Pembentukan Indeks Kemiskinan Multidimensi Anak Dan Pemanfaatannya Untuk Pengentasan Kemiskinan Berkelanjutan Di Indonesia Tahun 2017. Seminar Nasional Official Statistics, 2019(1), 336–346. https://doi.org/10.34123/semnasoffstat.v2019i1.222

[6] Wisdawati, R., & Nooraeni, R. (2021). Pembangunan Indeks Kemiskinan Balita Multidimensi di Provinsi Nusa Tenggara Timur Tahun 2019. March 2019.

[7] Putri, C. A., Irfani, R., & Sartono, B. (2021). Recognizing poverty pattern in Central Java using Biclustering Analysis. Journal of Physics: Conference Series, 1863(1). https://doi.org/10.1088/1742-6596/1863/1/012068

[8] Nurmawiya., & Kurniawan, R. (2021). Pengelompokan Wilayah Indonesia Dalam Menghadapi Revolusi Industri 4.0 Dengan Metode Biclustering. Seminar Nasional Official Statistics, 2020(1), 790–797. https://doi.org/10.34123/semnasoffstat.v2020i1.511

[9] Andriani, Merrryana dan Wirjatmadi, Bambang. (2012). Peranan Gizi dalam Silkus Kehidupan. Jakarta: Kencana.

[10] Johnson, Richard A and Wichern, Dean W. (2007). Applied Multivariate Statistical Analysis. New Jersey : Pearson Education, Inc.

[11] Sundari, M., Sihombing, P. R., & Hakim, K. F. (2021). Perbandingan Metode Analisis Gerombol K-Rataan Dan Bicluster (Studi Kasus: Kerentanan Kelurahan Di Kota Depok TAHUN 2020). Lombok Journal of Science, 1-11.

[12] Habibi, M., & Cahyo, P. W. (2019). Clustering User Characteristics Based on the influence of Hashtags on the Instagram Platform. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 13(4), 399. https://doi.org/10.22146/ijccs.50574

[13] Mina, E., Feelders, A. J., Kemmeren, P., & Siebes, A. P. J. M. (2011). Applying biclustering to understand the molecular basis of phenotypic diversity. Phd. Utrecht University Faculty of Science Department of Information and Computing Sciences.

[14] Chakraborty, A., & Maka, H. (2005 Biclustering of gene expression data using genetic algorithm. In 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (pp. 1-8). IEEE.

[15] Pontes, B., Girldez, R., & Aguilar-Ruiz, J. S. (2015). Quality measures for gene expression biclusters. PloSone, 10(3)

[16] Yuniarto, B., & Kurniawan, R. (2017). Understanding Structure of Poverty Dimensions in East Java: Bicluster Approach. Signifikan: Jurnal Ilmu Ekonomi, 6(2), 289-300.

[17] Rifai, N. A. K., Afendi, F. M., & Sumertajaya, I. M. (2018). Simultaneous clustering analysis with molecular docking in network pharmacology for type 2 antidiabetic compounds. Indonesian Journal of Biotechnology, 22(1), 43. https://doi.org/10.22146/ijbiotech.27334

[18] Nurmawiya., & Kurniawan, R. (2021). Pengelompokan Wilayah Indonesia Dalam Menghadapi Revolusi Industri 4.0 Dengan Metode Biclustering. Seminar Nasional Official Statistics, 2020(1), 790–797. https://doi.org/10.34123/semnasoffstat.v2020i1.511

[19] Kaban, P. A., Kurniawan, R., Caraka, R. E., Pardamean, B., & Yuniarto, B. (2019). Biclustering Method to Capture the Spatial Pattern and to Identify the Causes of Social Vulnerability in Indonesia: A New Recommendation for Disaster Mitigation Policy. Procedia Computer Science, 157, 31-37.

[20] Siagian, T. H., Purhadi, P., Suhartono, S., & Ritonga, H. (2014). Social vulnerability to natural hazards in Indonesia: driving factors and policy implications. Natural hazards, 70(2), 1603-1617.

[21] Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis, 7thEdition. United State: Pearson Prentice Hall.



DOI: https://doi.org/10.22146/ijccs.70433

Article Metrics

Abstract views : 1150 | views : 950

Refbacks

  • There are currently no refbacks.




Copyright (c) 2022 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Copyright of :
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
ISSN 1978-1520 (print); ISSN 2460-7258 (online)
is a scientific journal the results of Computing
and Cybernetics Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijccs.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijccs



View My Stats1
View My Stats2