Penerapan X Means Clustering Pada UMKM Kab Banyumas Yang Mendukung Mega Shifting Consumer Behavior Akibat Covid-19

Article Sidebar

View PDF
Published Feb 14, 2022
DOI https://doi.org/10.20895/inista.v4i1.429

Main Article Content

Rifki Adhitama
IT Telkom Purwokerto
Auliya Burhanuddin
Atik Febriani

Abstract

The Covid-19 has become a epidemic that is troubling the public because of the extent and speed of the virus spreading. The Covid-19 has resulted in people being unable to move outside their homes freely so that household consumption has decreased. This condition is similar to the crisis in 1997-1998, where MSMEs and small traders could survive. In Banyumas district, the percentage of MSMEs are in the large, medium, and small groups that can support the habit of Mega Shifting, or  businesses that can be done at home so that they can be an economic savior in the covid-19. Clustering is a method of grouping similar objects which are taken from several criteria. X-Means is a grouping method that can be used to effectively calculate the value of K. As for testing the quality of a cluster using the Purity test method, it is said to be "Good" if the results of this Purity are close to 1. The total of MSMEs in the Banyumas district which be grouped is 27,574 MSMEs. The purity  based on the results of the cluster is 0.9892 (3 groups), 0.9894 (4 groups), 0.9928 (5 groups), and 0.9677 (6 groups). In 3 groups, the results of grouping are 58 MSMEs belong to large groups, 381 MSMEs belong to medium groups, and 26,602 MSMEs belong to small groups. The recommended MSMEs sectors to face mega shifting are food stalls, culinary, agriculture, snacks, traders, craftsmen, workshops, furniture, constructions, and grocery stores.

Article Details

How to Cite
Adhitama, R., Burhanuddin, A., & Febriani, A. (2022). Penerapan X Means Clustering Pada UMKM Kab Banyumas Yang Mendukung Mega Shifting Consumer Behavior Akibat Covid-19. Journal of Informatics Information System Software Engineering and Applications (INISTA), 4(1), 71-80. https://doi.org/10.20895/inista.v4i1.429
Issue
Vol 4 No 1 (2021): November 2021
Section
Articles

Copyright Notice

 

Authors who publish with Journal of Informatics, Information System, Software Engineering and Applications (INISTA) agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

References

[1] N. R. Yunus, A. Rezki, Kebijakan Pemberlakuan Lockdown sebagai Antisipasi Penyebaran Corona Virus Covid-19, 2020.
[2] L. Heng, Dampak Orientasi Kewirausahaan dan Keunggulan Penciptaan Nilai terhadap Kinerja Pemasaran UMKM (Studi Empiris Pada UMKM Sub Sektor Kreatif di Kota Pontianak), 2018.
[3] B. D. Komara, H.C.B.Setiawan, Jalan Terjal UMKM dan Pedagang Kecil Bertahan di Tengah Pandemi Covid-19 dan Ancaman Krisis Ekonomi Global, Jurnal Manajemen Bisnis Vol 17. No. 3 Juli 2020. ISSN. 1829-8486, 2020.
[4] R. Adhitama, A.Burhanuddin, R.Ananda, Penentuan Jumlah Cluster Ideal SMK di Jawa Tengah dengan Metode X Means Clustering dan K Means Clustering. Jurnal Informatika dan Ilmu Komputer (JIKO) Vol. 3. No. 1. April 2020, 2020.
[5] R.O. Duda and P. E. Hart. Pattern classification and scene analysis, 1st edition. New York: Wiley, 1973.
[6] A. Al-wakeel and J. Wu, “K-Means Based Cluster Analysis of Residential Smart Meter Measurements,” Energy Procedia, Vol. 88, pp. 754-60, 2016.
[7] C. C. Aggarwal, C. K. Reddy, Data Clustering Algorithms and Applications. CRC Press, 2014.
[8] S. Nawrin, M. Rahatur, and S. Akhter, “Exploring K-Means With Internal Validity Indexes For Data Clustering in Traffic Management System’, Int. J Adv. Comput. Sci. Appl. Vol. 8, no.3, 2017.
[9] A. Bates and J. Kalita, “Counting Cluster in Twitter Posts” in ACM International Conference Proceeding Series, vol. 04-05- Marc, 2016.
[10] R. Handoyo, M. R. Rumaini, S.M. Nasution, Perbandingan Metode Clustering menggunakan metode Single Linkage dan K means pada Pengelompokkan Dokumen. In JSM STIMIK Mikroskil ISSN. 1412-0100 Vol. 15, No 2, 2014, pp 73-82, 2014.
[11] E. Herwiyanti, M Pinasti, N Puspasari, Riset UMKM Pendekatan Multiperspektif. Penerbit Deepublish Publisher, 2020.
[12] Yuswohadi, Hadapi Empat Mega Shifts Consumer Behavior, Sun Live Hadirkan Sun Connect.Website:
https://mix.co.id/marcomm/brand-insight/marketing-strategy/hadapi-empat-mega-shifts-consumer-behavior-sun-life-hadirkan-sun-connect/, 2020