DATA MINING FOR PREDICTING THE AMOUNT OF COFFEE PRODUCTION USING CRISP-DM METHOD
Data Mining Untuk Memprediksi Jumlah Produksi Tanaman Kopi Menggunakan Metode CRISP-DM
Abstract
The production of coffee plantations has become the leading plantation commodity with the export value of the fourth rank after oil palm, rubber and coconut. The number of coffee needs for export every year always increases, therefore it is necessary to predict the yield of coffee plants to estimate planting and anticipation that will be done so as to achieve the target. Coffee plant productivity is influenced by internal and external factors, namely the quality of the plant itself, soil, altitude and climate. The method used in this study is the CRISP-DM method and multiple linear regression algorithm to predict the amount of coffee production and determine the relationship between the variables. The steps taken are business understanding, data understanding, data preparation, modeling and evaluation. The data set that is used as many as 170 data after going through the data preparation stage produced 150 data with 5 attributes in the table. With calculations using tools, the coefficient of determination is 91.96%. That the variation in the value of the production of coffee plants is influenced by independent variables, namely the area of plantations, rainfall, air pressure and solar radiation by 91.96% and 8.04% influenced by other variables not measured in this study. The results of the evaluation and validation of predictions produce good accuracy with an RMSE value of 0.3477.
References
Ashari, S. (2004). Biologi reproduksi tanaman buah-buahan komersial. Malang : Bayu Media Pub.
Badan Pusat Statistik. (2018). Data Online Badan Statistik: Tabel Dinamis Subjek Perkebunan. Retrieved from https://www.bps.go.id/subject/54/perkebunan.html#subjekViewTab6
Bengnga, A., & Ishak, R. (2018). Prediksi Jumlah Mahasiswa Registrasi Per Semester Menggunakan Linier Regresi Pada Universitas Ichsan Gorontalo. ILKOM Jurnal Ilmiah, 10(2), 136–143. Retrieved from http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/274
Colin Shearer. (2000). The CRISP-DM Model: The New Blueprint for Data Mining. Journal of Data Warehousing, 5(4), 13–22.
Direktorat Jenderal Perkebunan. (2014). Statistik Perkebunan Indonesia Komoditas Kopi 2013 - 2015. Jakarta. Retrieved from https://bulelengkab.go.id/assets/instansikab/126/bankdata/data-statistik-perkebunan-indonesia-2013-2015-kopi-93.pdf
Iscaro, J. (2014). The Impact of Climate Change on Coffee Production in Colombia and Ethiopia. Global Majority E-Journal, 5(1), 33–43. Retrieved from http://www.bangladeshstudies.org/files/Global_Majority_e_Journal_5_1.pdf#page=33
Kamal, I. M., Hendro, T., & Ilyas, R. (2017). Prediksi Penjualan Buku Menggunakan Data Mining Di Pt. Niaga SwadayaPrediksi Penjualan Buku Menggunakan Data Mining Di Pt. Niaga Swadaya. In STMIK AMIKOM (Ed.), Seminar Nasional Teknologi Informasi dan Multimedia (pp. 49–54). Yogyakarta: STMIK AMIKOM.
Khumaidi, A. (2019). Final Research Report. Jakarta.
Lenisastri, L. (2000). Penggunaan Metode Akumulasi Satuan Panas (Heat Unit) sebagai Dasar Penentuan Umur Panen Benih Sembilan Varietas Kacang Tanah (Arachis hypogaea L.). Institut Pertanian Bogor. Retrieved from https://repository.ipb.ac.id/handle/123456789/20324
Maulida, L. (2018). Kunjungan Wisatawan Ke Objek Wisata Unggulan Di Prov . Dki Jakarta Dengan K-Means. JISKa, 2(3), 167–174. Retrieved from http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/1200
Ngumar, Y. H. (2008). Aplikasi Metode Numerik Dan Matrik Dalam Perhitungan Koefisien-Koefisien Regresi Linier Multiple Untuk Peramalan. In Konferensi Nasional Sistem dan Informatika (pp. 157–162). Bali: STIKOM Bali. Retrieved from https://yudiagusta.files.wordpress.com/2009/11/157-162-knsi08-029-aplikasi-metode-numerik-dan-matrik-dalam-perhitungan-koefisien-koefisien-regresi-linier-multiple-untuk-peramalan.pdf
Prasetyo, S. B., Aini, N., Dawam, M., Jurusan, M., Pertanian, B., & Pertanian, F. (2017). Dampak Perubahan Iklim Terhadap Produktivitas Kopi Robusta (Coffea Robusta) Di Kabupaten Malang. Jurnal Produksi Tanaman, 5(5), 805–811.
Setiawan, E. (2009). Kajian Hubungan Unsur Iklim Terhadap Produktivitas Cabe Jamu (Piper Retrofractum Vahl) Di Kabupaten Sumenep. AGROVIGOR, 2(1), 1–7.
Soni, N., & Ganatra, A. (2012). Categorization of Several Clustering Algorithms from Different Perspective: A Review. International Journal of Advanced Research in Computer Science and Software Engineering, 2(8), 63–68. Retrieved from https://www.researchgate.net/profile/Neha_Soni8/publication/267368768_Categorization_of_Several_Clustering_Algorithms_from_Different_Perspective_A_Review/links/575a6f7208ae414b8e460fa6/Categorization-of-Several-Clustering-Algorithms-from-Different-Perspective-A-Review.pdf
Warih, E. I. A., & Rahayu, Y. (2015). Penerapan Data Mining Untuk Menentukan Estimasi Produktivitas Tanaman Tebu Dengan Menggunakan Algoritma Linier Regresi Berganda Di Kabupaten Rembang. Semarang. Retrieved from http://eprints.dinus.ac.id/16925/1/jurnal_16115.pdf
Widayat, H. P., Anhar, A., & Baihaqi, A. (2015). Dampak Perubahan Iklim Terhadap Produksi, Kualitas Hasil Dan Pendapatan Petani Kopi Arabika Di Aceh Tengah. Agrisep, 16(2), 8–16. Retrieved from http://www.jurnal.unsyiah.ac.id/agrisep/article/view/3041
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