Main Article Content
Abstract
Poverty is an essential issue for every country, including Indonesia. Poverty can be caused by the scarcity of basic necessities or the difficulty of accessing education and employment. In 2019 Papua Province became the province with the highest poverty percentage at 27.53%. Seeing this, the district groupings formed in describing poverty conditions in Papua Province are based on similar characteristics using the variables Percentage of Poor Population, Gross Regional Domestic Product, Open Unemployment Rate, Life Expectancy, Literacy Rate, and Population Working in the Agricultural Sector using K-medoids clustering algorithm. The results of this study indicate that the optimal number of clusters to describe poverty conditions in Papua Province is 4 clusters with a variance of 0.012, where the first cluster consists of 10 districts, the second cluster consists of 5 districts, the third cluster consists of 12 districts, and the fourth cluster consists of 2 districts.
Keywords
Article Details
Authors who publish with this journal 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 that allows others to share the work with an acknowledgment 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 acknowledgment 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 (See The Effect of Open Access).
References
- BAPPENAS, "Rencana Pembangunan Jangka Menengah Nasional 2004-2009", 2009.
- BAPPENAS, Badan Pembangunan Nasional, [Online]. Available: https://www.bappenas.go.id/id/berita-dan-siaran-pers/gelar-konferensi-pers-akhir-tahun-bappenas-paparkan-rkp-2021-capaian-sdgs-indonesia-dan-transformasi-ekonomi/.
- BPS, "Penduduk Fakir Miskin Indonesia Tahun 2002," 2002.
- E. Saputera, "Faktor-Faktor yang Mempengaruhi Kemiskinan di Provinsi Papua Periode 2006-2016," Jurnal Ilmiah Mahasiswa Universitas Surabaya, vol. 8, no. 1, 2019.
- Fauziah, "Hierarchical Cluster Analysis Industri Manufaktur Besar dan Sedang Berdasarkan Status Penanaman Modal. Studi Kasus: Industri Manufaktur Besar dan Sedang di Jawa Tengah Tahun 2015," in Skripsi Jurusan Statistika Fakultas Matematika dan Ilmu Pengetahuan Alam, Yogyakarta, Universitas Islam Indonesia, 2019.
- Febriyana, "Analisis K-Means dan K-Median pada Data Indikator Kemiskinan.," in Universitas Islam Negeri Syarif Hidayatullah, Jakarta, 2011.
- G. I. Nyoman, S. and N. N. Yuliarmi, "Analisis Faktor-Faktor yang Mempengaruhi Tingkat Kemiskinan di Nusa Tenggara dan Papua," Jurnal Ekonomi Pembangunan Universitas Udayana, vol. 9, no. 12, pp. 2762-2791, 2019.
- M. Abid, "Pengaruh Angka Melek Huruf Terhadap Kemiskinan di Provinsi Jawa Timur Periode 2008-2015," Jurnal Penelitian Ilmu Manajemen, vol. 1, no. 03, 2016.
- M. Bunkers, "Definition of Climate Regions in the Northern Plains Using an Objecting Cluster Modification Technique," j.Climate, pp. 130-146.
- N. Kaur, "K-Medoids Clustering Algorithm," International Journal of Computer Application and Technology, pp. 42-45, 2014.
- N. L. Anggraeni, "Teknik Clustering Dengan Algoritma K-Medoids untuk Menangani Strategi Promosi di Politeknik TEDC Bandung," Jurnal TEDC, vol. 12, no. 2, 2019.
- R. E. Walpole and R. H. Myers, Ilmu Peluang dan Statistika untuk Insinyur dan Ilmuwan, Bandung: ITB, 1995.
- R. P. Silhouttes, "A Graphical Aid To The Interpretation And Validation Of ClusterAnalysis," Journal of computational and Applied Mathematics, pp. 20:53-65, 1987.
- S. N. Ika., "Analisis Kemiskinan di Provinsi Jawa Tengah Menggunakan Metode Regresi Spasial," in Skripsi Prodi Statistika, Yogyakarta, Universitas Islam Indonesia, 2015.
- S. Santoso, Menguasai Statistik Parametrik Konsep dan Aplikasi dengan SPSS, Jakarta: PT Elex Media Komputindo, 2015.
- S. Wahyuni and Y. A. Jatmiko, "Pengelompokan Kabupaten/Kota di Pulau Jawa Berdasarkan Faktor-Faktor Kemiskinan dengan Pendekatan Average Linkage Hierarchical Clustering," Jurnal Aplikasi Statistika dan Komputasi Statistika STIS, vol. 10, no. 1, 2018.
- T. Supriatna, "Birokrasi. Pemberdayaan. dan Pengentasan Kemiskinan," in Humaniora Utama Press, Bandung, 1997.
- Tiswati, "Analisis Faktor-Faktor yang Mempengaruhi Tingkat Kemiskinan di Indonesia," Jurnal Ekonomi Pembangunan, vol. 10, no. 1, Juni, 2012.
- Y. H. Christanto and G. Abdillah, "Penerapan Algoritma Partitioning Around Medoids (Pam) Clustering Untuk Melihat Gambaran Umum Kemampuan," Semin. Nas. Teknol. Inf. dan Komun, vol. 2015, no. sentika, pp. 444-448, 2015.
References
BAPPENAS, "Rencana Pembangunan Jangka Menengah Nasional 2004-2009", 2009.
BAPPENAS, Badan Pembangunan Nasional, [Online]. Available: https://www.bappenas.go.id/id/berita-dan-siaran-pers/gelar-konferensi-pers-akhir-tahun-bappenas-paparkan-rkp-2021-capaian-sdgs-indonesia-dan-transformasi-ekonomi/.
BPS, "Penduduk Fakir Miskin Indonesia Tahun 2002," 2002.
E. Saputera, "Faktor-Faktor yang Mempengaruhi Kemiskinan di Provinsi Papua Periode 2006-2016," Jurnal Ilmiah Mahasiswa Universitas Surabaya, vol. 8, no. 1, 2019.
Fauziah, "Hierarchical Cluster Analysis Industri Manufaktur Besar dan Sedang Berdasarkan Status Penanaman Modal. Studi Kasus: Industri Manufaktur Besar dan Sedang di Jawa Tengah Tahun 2015," in Skripsi Jurusan Statistika Fakultas Matematika dan Ilmu Pengetahuan Alam, Yogyakarta, Universitas Islam Indonesia, 2019.
Febriyana, "Analisis K-Means dan K-Median pada Data Indikator Kemiskinan.," in Universitas Islam Negeri Syarif Hidayatullah, Jakarta, 2011.
G. I. Nyoman, S. and N. N. Yuliarmi, "Analisis Faktor-Faktor yang Mempengaruhi Tingkat Kemiskinan di Nusa Tenggara dan Papua," Jurnal Ekonomi Pembangunan Universitas Udayana, vol. 9, no. 12, pp. 2762-2791, 2019.
M. Abid, "Pengaruh Angka Melek Huruf Terhadap Kemiskinan di Provinsi Jawa Timur Periode 2008-2015," Jurnal Penelitian Ilmu Manajemen, vol. 1, no. 03, 2016.
M. Bunkers, "Definition of Climate Regions in the Northern Plains Using an Objecting Cluster Modification Technique," j.Climate, pp. 130-146.
N. Kaur, "K-Medoids Clustering Algorithm," International Journal of Computer Application and Technology, pp. 42-45, 2014.
N. L. Anggraeni, "Teknik Clustering Dengan Algoritma K-Medoids untuk Menangani Strategi Promosi di Politeknik TEDC Bandung," Jurnal TEDC, vol. 12, no. 2, 2019.
R. E. Walpole and R. H. Myers, Ilmu Peluang dan Statistika untuk Insinyur dan Ilmuwan, Bandung: ITB, 1995.
R. P. Silhouttes, "A Graphical Aid To The Interpretation And Validation Of ClusterAnalysis," Journal of computational and Applied Mathematics, pp. 20:53-65, 1987.
S. N. Ika., "Analisis Kemiskinan di Provinsi Jawa Tengah Menggunakan Metode Regresi Spasial," in Skripsi Prodi Statistika, Yogyakarta, Universitas Islam Indonesia, 2015.
S. Santoso, Menguasai Statistik Parametrik Konsep dan Aplikasi dengan SPSS, Jakarta: PT Elex Media Komputindo, 2015.
S. Wahyuni and Y. A. Jatmiko, "Pengelompokan Kabupaten/Kota di Pulau Jawa Berdasarkan Faktor-Faktor Kemiskinan dengan Pendekatan Average Linkage Hierarchical Clustering," Jurnal Aplikasi Statistika dan Komputasi Statistika STIS, vol. 10, no. 1, 2018.
T. Supriatna, "Birokrasi. Pemberdayaan. dan Pengentasan Kemiskinan," in Humaniora Utama Press, Bandung, 1997.
Tiswati, "Analisis Faktor-Faktor yang Mempengaruhi Tingkat Kemiskinan di Indonesia," Jurnal Ekonomi Pembangunan, vol. 10, no. 1, Juni, 2012.
Y. H. Christanto and G. Abdillah, "Penerapan Algoritma Partitioning Around Medoids (Pam) Clustering Untuk Melihat Gambaran Umum Kemampuan," Semin. Nas. Teknol. Inf. dan Komun, vol. 2015, no. sentika, pp. 444-448, 2015.