Cluster Analysis of Indonesian Provinces Based On Harvest Area And Rice Productivity Using Single Linkage Method
DOI:
https://doi.org/10.24014/sitekin.v20i2.21737Abstract
In this article, a cluster analysis will be conducted for provinces in Indonesia based on the harvest area (ha) and rice productivity (ku/ha) of 34 provinces in Indonesia. Clustering is done using a hierarchical method, namely single linkage. The distance used as the basis for clustering is the euclidian distance. Based on the results of clustering using single linkage, 3 large clusters were obtained. In this article, a cluster analysis will be conducted for provinces in Indonesia based on the harvest area (ha) and rice productivity (ku/ha) of 34 provinces in Indonesia. clustering is done using a hierarchical method, namely single linkage. The distance used as the basis for clustering is the euclidian distance. Based on the results of clustering using single linkage, 3 large clusters were obtained. Cluster consists of 3 provinces, cluster 2 consists of 1 province and cluster 3 consists of 30 provinces. Cluster 1 is a province with high rice production with an average total rice production of 9,628,788 tons. Cluster 2 with an average total rice production of 5,341,021 tons. While cluster 3 with an average rice production of 863,995.34 tons. Furthermore, based on cluster validation using the anova test, the significance value is 0.00>0.05, which means that there is a significant difference between clusters. Thus it can be stated that the division of 34 Indonesian provinces in terms of land area and rice productivity into 3 large clusters using the single linkage method is valid.
References
S. Konyep, “Upaya Pencapaian Swasembada Pangan Melalui Membumikan Padi Amfibi Balitbangtan di Provinsi Papua Barat,” Triton, vol. 11, no. 2, pp. 32–41, 2020.
S. Paipan and M. Abrar, “Determinan Ketergantungan Impor Beras Di Indonesia ( Determinants of Rice Import Dependency in Indonesia ),” J. Ekon. dan Kebijak. Publik, vol. 11, no. 01, pp. 53–64, 2020.
Nazaruddin, “Luas Tanam Dan Luas Panen Padi Di Jawa Barat,” J. Trit., vol. 10, no. 1, pp. 59–68, 2019.
E. P. Cynthia et al., “Convolutional Neural Network and Deep Learning Approach for Image Detection and Identification,” in Journal of Physics: Conference Series, 2022, vol. 2394, no. 1, p. 12019.
M. L. Hamzah, M. Rizki, and M. I. H. Umam, “Integration of Fuzzy Logic Algorithms with Failure Mode and Effect Analysis for Decision Support Systems in Product Quality Improvement of Piano Cabinets,” in 2022 International Conference on Electrical and Information Technology (IEIT), 2022, pp. 13–19.
M. Yanti, F. S. Lubis, N. Nazaruddin, M. Rizki, S. Silvia, and S. Sarbaini, “Production Line Improvement Analysis With Lean Manufacturing Approach To Reduce Waste At CV. TMJ uses Value Stream Mapping (VSM) and Root Cause Analysis (RCA) methods,” 2022.
M. L. Hamzah, A. A. Purwati, S. Sutoyo, A. Marsal, S. Sarbani, and N. Nazaruddin, “Implementation of the internet of things on smart posters using near field communication technology in the tourism sector,” Comput. Sci. Inf. Technol., vol. 3, no. 3, pp. 194–202, 2022.
S. Sarbaini, “Modeling of Traffic Flow Schemes at Road Intersections in Pekanbaru City Using Compatible Graphs,” Eduma Math. Educ. Learn. Teach., vol. 11, no. 2, pp. 213–222, 2022.
R. H. B. Bangun, “Analisis Klaster Non-Hierarki Dalam Pengelompokan Kabupaten/Kota Di Sumatera Utara Berdasarkan Faktor Produksi Padi,” Agrica (Jurnal Agribisnis Sumatera Utara), vol. 4, no. 1, pp. 54–61, 2016.
T. E. Nita and L. Zahrotun, “Penerapan Metode Single Linkage dengan Manhattan Distance Similarity dalam Mengelompokkan Trens Topik Kerja Praktik Application of the Single Linkage Method with Manhattan Distance Similarity in Grouping Trens of Practical Work Topics,” J. Ris. Sains dan Teknol., vol. 5, no. 1, pp. 39–44, 2021.
D. Rachmatin, “Aplikasi metode-metode agglomerative dalam analisis klaster pada data tingkat polusi udara,” J. Ilm. Progr. Stud. Mat. STKIP Siliwangi Bandung, vol. 3, no. 2, pp. 133–149, 2014.
I. N. Hasanah and A. Sofro, “Analisis Cluster Berdasarkan Dampak Ekonomi Di Indonesia Akibat Pandemi Covid-19,” J. Ilm. Mat., vol. 10, no. 02, 2022.
N. Ulinnuh and R. Veriani, “Analisis Cluster dalam Pengelompokan Provinsi di Indonesia Berdasarkan Variabel Penyakit Menular Menggunakan Metode Complete Linkage , Average Linkage dan Ward,” J. Nas. Inform. dan Teknol. Jar., vol. 5, no. 1, 2020.
G. Haumahu and Y. W. Nanlohy, “Penerapan Analisis Klaster Hierarki Untuk Pengelompokkan Kabupaten / Kota Di Provinsi Maluku Berdasarkan Konsumsi Kalori ( The Application of Hierarchical Cluster Analysis for Grouping District / City in Maluku Province Based on Population Calories Consum,” Var. J. Stat. its Appl., vol. 2, no. 2, pp. 75–79, 2020.
V. Devani, M. I. H. Umam, Y. Aiza, and S. Sarbaini, “Optimization of Tire Production Planning Using The Goal Programming Method and Sensitivity Analysis,” Int. J. Comput. Sci. Appl. Math., vol. 8, no. 2, pp. 36–40, 2022.
S. Sarbaini, Z. Zukrianto, and N. Nazaruddin, “Pengaruh Tingkat Kemiskinan Terhadap Pembangunan Rumah Layak Huni Di Provinsi Riau Menggunakan Metode Analisis Regresi Sederhana,” J. Teknol. dan Manaj. Ind. Terap., vol. 1, no. III, pp. 131–136, 2022.
N. Nazaruddin and S. Sarbaini, “Evaluasi Perubahan Minat Pemilihan Mobil dan Market Share Konsumen di Showroom Pabrikan Honda,” J. Teknol. dan Manaj. Ind. Terap., vol. 1, no. II, pp. 97–103, 2022.
S. Sarbaini, M. Imran, and A. Karma, “Metode Bertipe Steffensen dengan Orde Konvergensi Optimal untuk Menyelesaikan Persamaan Nonlinear.” Riau University, 2014.
S. Sarbaini, W. Saputri, and F. Muttakin, “Cluster Analysis Menggunakan Algoritma Fuzzy K-Means Untuk Tingkat Pengangguran Di Provinsi Riau,” J. Teknol. dan Manaj. Ind. Terap., vol. 1, no. II, pp. 78–84, 2022.
R. Handoyo, “perbandingan metode clustering menggunakan metode single linkage dan k-means pada pengelompokan dokumen,” JSM SRMIK Mikroskil, vol. 15, no. 2, pp. 73–82, 2014.
Suyanto, Syarippudin, and Wasono, “Di Kabuapten Kutai KartannegaraTahun 2019 Single Linkage Cluster Analysis Based on Village Potential,” EKSPONENSIAL, vol. 12, no. 1, pp. 59–64, 2021.
N. Asiska, N. Satyahadewi, and H. Perdana, “Pencarian Cluster Optimum Pada Single Linkage , Complete Linkage Dan Average Linkage,” Bul. Ilm. Math, Stat, dan Ter., vol. 08, no. 3, pp. 393–398, 2019.
S. Sarbaini, E. P. Cynthia, and M. I. Arifandy, “Pengelompokan Diabetic Macular Edema Berbasis Citra Retina Mata Menggunakan Fuzzy Learning Vector Quantization (FLVQ),” SITEKIN J. Sains, Teknol. dan Ind., vol. 19, no. 1, pp. 75–80, 2021.
M. I. Arifandy, E. P. Cynthia, and F. Muttakin, “Potensi Limbah Padat Kelapa Sawit Sebagai Sumber Energi Terbarukan Dalam Implementasi Indonesian Sustainability Palm Oil,” SITEKIN J. Sains, Teknol. dan Ind., vol. 19, no. 1, pp. 116–122, 2021.
F. Muttakin, K. N. Fatwa, and S. Sarbaini, “Implementasi Additive Ratio Assessment Model untuk Rekomendasi Penerima Manfaat Program Keluarga Harapan,” SITEKIN J. Sains, Teknol. dan Ind., vol. 19, no. 1, pp. 40–48.
S. Sarbaini and E. Safitri, “Penerapan Metode Single Exponential Smoothing dalam Memprediksi Jumlah Peserta Pelatihan Masyarakat,” Lattice J. J. Math. Educ. Appl., vol. 2, no. 2, pp. 103–117, 2022.
R. D. Fitriani, H. Yasin, and Tarno, “PENANGANAN KLASIFIKASI KELAS DATA TIDAK SEIMBANG DENGAN RANDOM OVERSAMPLING PADA NAIVE BAYES (Studi Kasus: Status Peserta KB IUD di Kabupaten Kendal),” J. GAUSSIAN, vol. 10, no. 1, pp. 11–20, 2021.
R. G. Whendasmoro and Joseph, “Analisis Penerapan Normalisasi Data Dengan Menggunakan Z-Score,” JURIKOM (Jurnal Ris. Komputer), vol. 9, no. 4, pp. 872–876, 2022, doi: 10.30865/jurikom.v9i4.4526.
C. V. Bertan, A. K. T. Dundu, and R. J. M. Mandagi, “Pengaruh Pendayagunaan Sumber Daya Manusia ( Tenaga Kerja ) Terhadap Hasil Pekerjaan ( Studi Kasus Perumahan Taman Mapanget Raya ( TAMARA )),” J. Sipil Statik Vol.4, vol. 4, no. 1, pp. 13–20, 2016.
J. Supranto, Analisis Multivariat: Arti dan interpretasi. Jakarta.: PT. Rineka Cipta., 2004.
M. Roux, “A Comparative Study of Divisive and Agglomerative Hierarchical Clustering Algorithms,” J. Classif., vol. 35, 2018, doi: 10.1007/s00357-018-9259-9.
M. Paramadina, S. Sudarmin, and M. K. Aidid, “Perbandingan Analisis Cluster Metode Average Linkage dan Metode Ward (Kasus: IPM Provinsi Sulawesi Selatan),” VARIANSI J. Stat. Its Appl. Teach. Res., vol. 1, no. 2, p. 22, 2019, doi: 10.35580/variansiunm9357.
D. Noor, P. Sari, and Y. L. Sukestiyarno, “Analisis Cluster dengan Metode K-Means pada Persebaran Kasus COVID-19 Berdasarkan Provinsi di Indonesia,” PRISMA, vol. 4, pp. 602–610, 2021.
A. Septiadi and W. K. Ramdhani, “Penerapan Metode Anova untuk Analisis Rata-rata produksi donat, burger, dan Croissant pada Toko Roti Animo Bakery,” Bull. Appl. Ind. Eng. Theory, vol. 1, no. 2, pp. 60–64, 2020.
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