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Soybean Collect Recommender Based on Distance and Productivity Cluster Using K-means Clustering and Simple Addictive Weighting Method
Feddy Setio Pribadi, Universitas Negeri Semarang, Indonesia
Abstract
Soybeans are an essential agricultural product that is one of the primary food sources in Indonesia, such as tempeh, tofu, soy milk, soy sauce, and other preparations. However, production yields, harvested land area, and soybean productivity in each district or city in Central Java Province vary widely. Differences in soybean productivity in each area are due to production factors such as area, use of fertilizers, seeds, and labor. This study tries to provide recommendations for soybean harvesting based on the distance and productivity of an area using K-means clustering and the simple addictive weighting method. In the Central Java Province, 35 regions will be divided into four clusters: the first with high productivity, the second with medium productivity; the third with low productivity; and the fourth with very low productivity. Additionally, based on the fourth cluster clustering results, it will be advised to take soybeans from other clusters by taking the closest distance and cluster members into account. According to the research, four clusters have formed: the first has five members, the second has fourteen, the third has nine, and the fourth has seven. The fourth cluster, which consists of seven members who do not grow soybeans, is advised to buy soybeans from the following regions: Kendal Regency, Klaten Regency, Magelang Regency, Batang Regency, and Brebes Regency.
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G. Setyawan and S. Huda, “Analisis Pengaruh Produksi Kedelai, Konsumsi Kedelai, Pendapatan per Kapita . dan Kurs Terhadap Impor Kedelai di Indonesia,” J. Ekon. dan Manaj., vol. 19, no. 2, pp. 215–225, 2022, doi: 10.29264/jkin.v19i2.10949.
M. Nahrul, F. Ristanto, and S. N. Sarifah, “Analisis Determinan Volume Impor Kedelai Indonesia menggunakan Metode ECM (Error Correction Model) Tahun 1991- 2020,” J. Ekon. Bisnis, Manaj. dan Akunt., vol. Im, pp. 18–30, 2022.
S. Madrim, “Menteri Pertanian: 90 Persen Kebutuhan Kedelai Dipenuhi Lewat Impor,” VOA Indonesia, 2022. https://www.voaindonesia.com/a/menteri-pertanian-90-persen-kebutuhan-kedelai-dipenuhi-lewat-impor/6410366.html (accessed Jun. 05, 2022).
B. Kharisma, “Determinan Produksi Kedelai di Indonesia dan Implikasi Kebijakannya,” E-Jurnal Ekon. dan Bisnis Univ. Udayana, vol. 3, p. 679, 2018, doi: 10.24843/eeb.2018.v07.i03.p03.
I. Hardianti and N. D. Setiawina, “Faktor - Faktor Mempengaruhi Impor Kedelai di Indonesia,” E-Jurnal Ekon. Pembang. Univ. Udayana, vol. 10, no. 6, pp. 2313–2340, 2021.
C. M. Annur, “Nilai Impor Kedelai Indonesia Naik Jadi US$ 1,48 Juta pada 2021,” databoks, 2022.https://databoks.katadata.co.id/datapublish/2022/03/07/nilai-impor-kedelai-indonesia-naik-jadi-us-148-juta-pada-2021.
D. W. Laily, “Faktor-Faktor Yang Berpengaruh Terhadap Produksi Kedelai Nasional,” J. Agrinka, vol. 2, no. 02, 2018.
S. Rokhimah, T. Widjojoko, and A. N. Mandamdari, “Analisis Peramalan Produksi, Luas Panen, dan Harga Kedelai di Provinsi Jawa Tengah,” in Prosiding Seminar Nasional Hasil Penelitian Agribisnis, 2022, vol. 6, pp. 124–130.
M. Ivanni, N. Kusnadi, and Suprehatin, “Efisiensi Teknis Produksi Kedelai Berdasarkan Varietas dan Wilayah Produksi di Indonesia,” J. Agribisnis Indones., vol. 7, no. 1, pp. 27–36, 2019.
R. Anggreati, “Indonesia Dinilai Sanggup Kurangi Ketergantungan Impor Kacang Kedelai,” medcom.id, 2022. https://www.medcom.id/ekonomi/bisnis/GNlWgwmK-indonesia-dinilai-sanggup-kurangi-ketergantungan-impor-kacang-kedelai (accessed Jul. 26, 2022).
A. D. Fadhlullah, T. Ekowati, and Mukson, “Analisis Rantai Pasok (Supply Chain) Kedelai di UD Adem Ayem Kecamatan Pulokulon Kabupaten Grobogan,” J. Pendidik. Bisnis dan Ekon., vol. 4, no. 2, pp. 1–10, 2018, [Online]. Available: https://jurnal.uns.ac.id/bise/article/download/22826/18374.
Masitha, Solikhun, D. Suhendro, I. S. Damanik, and M. Fauzan, “Implementasi K-Means Clustering Untuk Mengelompokkan Hasil Pertanian Kacang Kedelai ( Ha ) Berdasarkan Provinsi,” Senaris, vol. 2, no. 5, pp. 192–199, 2020.
Sudirman, A. P. Windarto, and A. Wanto, “Data mining tools | rapidminer : K-means method on clustering of rice crops by province as efforts to stabilize food crops in Indonesia,” 2018, doi: 10.1088/1757-899X/420/1/012089.
H. Rhomadhona et al., “Sistem Pendukung Keputusan Distribusi Bantuan Pertanian Menggunakan Simple Additice Weighting,” J. Syst. Comput. Eng. ISSN, vol. 2, no. 1, p. 1, 2021.
Y. Yanuari, M. G. Husada, and D. B. Utami, “Aplikasi Rekomendasi Jenis Tanaman Pangan Menggunakan Metode Simple Additive Weighting (SAW,” JOINTECS (Journal Inf. Technol. Comput. Sci., vol. 3, no. 1, 2018, doi: 10.31328/jointecs.v3i1.495.
P. Dauni, M. D. Firdaus, R. Asfariani, M. I. N. Saputra, A. A. Hidayat, and W. B. Zulfikar, “Implementation of Haversine formula for school location tracking,” J. Phys. Conf. Ser., vol. 1402, no. 7, 2019, doi: 10.1088/1742-6596/1402/7/077028.
C. Husada, K. D. Hartomo, and H. P. Chernovita, “Implementasi Haversine Formula untuk Pembuatan SIG Jarak Terdekat ke RS Rujukan COVID-19,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 4, no. 5, pp. 874–883, 2020, doi: 10.29207/resti.v4i5.2255.
Badan Pusat Statistik, “Luas Panen, Produksi, dan Produktivitas Jagung dan Kedelai Menurut Kabupaten/Kota di Provinsi Jawa,” Badan Pusat Statistik, 2021. https://jateng.bps.go.id/statictable/2021/04/15/2450/luas-panen-produksi-dan-produktivitas-jagung-dan-kedelai-menurut-kabupaten-kota-di-provinsi-jawa-2019.html (accessed Feb. 10, 2022).
K. P. Sinaga and M. S. Yang, “Unsupervised K-means clustering algorithm,” IEEE Access, voyl. 8, pp. 80716–80727, 2020, doi: 10.1109/ACCESS.2020.2988796.
S. Abadi et al., “Application model of k-means clustering: Insights into promotion strategy of vocational high school,” Int. J. Eng. Technol., vol. 7, no. 2.27 Special Issue 27, pp. 182–187, 2018, doi: 10.14419/ijet.v7i2.11491.
M. Z. Hossain, M. N. Akhtar, R. B. Ahmad, and M. Rahman, “A dynamic K-means clustering for data mining,” Indones. J. Electr. Eng. Comput. Sci., vol. 13, no. 2, pp. 521–526, 2019, doi: 10.11591/ijeecs.v13.i2.pp521-526.
J. Han and M. Kamber, Data Mining: Concepts and Techniques, 2nd ed. Morgan Kaufmann Publishers, 2006.
H. Harliana, R. M. Herdian Bhakti, O. Saeful Bachri, and F. Sofian Efendi, “Optimasi K-Means dengan Particle Swarm Optimization pada Pengelompokkan Daerah Stunting,” J. Ilm. Intech Inf. Technol. J. UMUS, vol. 3, no. 02, pp. 95–101, 2021, doi: 10.46772/intech.v3i02.457.
A. E. Wibowo and T. Habanabakize, “K-Means Clustering Untuk Klasifikasi Standar Kualifikasi Pendidikan Dan Pengalaman Kerja Guru,” J. Din. Vokasional Tek. Mesin, vol. 7, pp. 152–163, 2022.
A. H. Nasyuha, Zulham, and I. Rusydi, “Implementation of K-means algorithm in data analysis,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 20, no. 2, pp. 307–313, 2022, doi: 10.12928/TELKOMNIKA.v20i2.21986.
R. A. Azdy and F. Darnis, “Use of Haversine Formula in Finding Distance between Temporary Shelter and Waste End Processing Sites,” J. Phys. Conf. Ser., vol. 1500, no. 1, 2020, doi: 10.1088/1742-6596/1500/1/012104.
N. Aminudin et al., “Higher Education Selection using Simple Additive Weighting,” Int. J. Eng. Technol., vol. 7, no. 2.27, p. 211, Aug. 2018, doi: 10.14419/ijet.v7i2.27.11731.
N. Setiawan et al., “Simple Additive Weighting As Decision Support System For Determining Employees Salary,” Int. J. Eng. Technol., vol. 7, no. 2.14 Special Issue 14, pp. 309–313, 2018.
A. Fitrul Hadi, R. Permana, and H. Syafwan, “Decision Support System in Determining Structural Position Mutations Using Simple Additive Weighting (SAW) Method,” J. Phys. Conf. Ser., vol. 1339, no. 1, p. 012015, Dec. 2019, doi: 10.1088/1742-6596/1339/1/012015.
Fauzi, Nungsiyati, T. Noviarti, M. Muslihudin, R. Irviani, and A. Maseleno, “Optimal Dengue Endemic Region Prediction using Fuzzy Simple Additive Weighting based Algorithm,” Int. J. Pure Appl. Math., vol. 118, no. 7 Special Issue, 2018.
A. Cahyapratama and R. Sarno, “Application of Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Methods In Singer Selection Process,” in 2018 International Conference on Information and Communications Technology (ICOIACT), Mar. 2018, pp. 234–239, doi: 10.1109/ICOIACT.2018.8350707.
Y. Fiona., Soetoro., and Z. Normansyah, “Analisis Pemasaran Kedelai (Suatu Kasus di Desa Langkapsari Kecamatan Banjarsari Kabupaten Ciamis),” J. Ilm. Mhs. Agroinfo Galuh, vol. 1, no. 2, pp. 137–142, 2015.
N. E. Kristanti and I. S. Almuntaha, “Penentuan Saluran Pemasaran terhadap Tingkat Harga pada Rantai Pasok Kedelai (Glycine maxL.) Merr.) di Kabupaten Grobogan Provinsi Jawa Tengah,” Agritech, vol. 37, no. 4, p. 443, 2018, doi: 10.22146/agritech.24808.
Badan Pusat Statistik, “Rata-Rata Konsumsi per Kapita Seminggu Beberapa Macam Bahan Makanan Penting, 2007-2021,” Badan Pusat Statistik, 2021. https://www.bps.go.id/statictable/2014/09/08/950/rata-rata-konsumsi-per-kapita-seminggu-beberapa-macam-bahan-makanan-penting-2007-2021.html. (accessed Feb. 10, 2022).
DOI: https://doi.org/10.21831/elinvo.v8i1.53208
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