Pemanfaatan Algoritma K-Means Dalam Menentukan Potensi Hasil Produksi Kelapa Sawit

 (*)Ayu Sri Wahyuni Mail (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Elin Haerani (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Elvia Budianita (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Liza Afrianti (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)

(*) Corresponding Author

Submitted: December 22, 2023; Published: December 31, 2023

Abstract

Considering the importance of oil palm cultivation now and in the future, as well as the increasing demand for palm oil by the world population, it is necessary to think about efforts to increase the quality and quantity of palm oil production appropriately in order to achieve the desired and achievable goals. Based on data on palm fruit production results from PT Salim Ivomas Pratama Tbk, it can be seen that fruit production varies in several places. The potential yield of oil palm fruit is based on the harvested area, actual production and year of planting. K-Means welding can help identify the potential of oil palm, with results that vary from day to day. This process allows locations with similar production patterns, which facilitates management decisions and production strategies. In this research, potential fruit planting areas were grouped using the K-Means algorithm. K-Means aims to facilitate the grouping of blocks with high and low fruit production. The data used is 180 data for the last 5 years, namely from 2018 to 2022, with the attributes Harvest Block, Area, Sheet Weight, and Product Realization or quantity. This research uses the help of Rapidminer and Google Colab software. The results of this research show that C1 (the highest) is 125 Harvest Block data in the sense that the first group is included in the good or high harvest yield category in 2018-2022, and C0 (the lowest) is 55 Harvest Block data in the sense that the second group is included low yield category 2018-2022.

Keywords


Palm Oil; Harvest Results; Data Mining; Clustering; Algorithms K-Means

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References

E. F. Himmah, M. Widyaningsih, and M. Maysaroh, “Identifikasi Kematangan Buah Kelapa Sawit Berdasarkan Warna RGB Dan HSV Menggunakan Metode K-Means Clustering,” J. Sains dan Inform., vol. 6, no. 2, pp. 193–202, 2020, doi: 10.34128/jsi.v6i2.242.

F. Nasari and U. P. Utama, “Optimalisasi Pengelompokkan Data Produksi Kelapa Sawit Menggunakan Algoritma K-Medoids,” vol. 5, no. 1, 2022.

I. Ramadhani and M. Megawati, “Implementasi Algoritma K-Means Untuk Klustering Data Produktivitas Kelapa Sawit: Implementation Of K-Means Algorithm For Palm Oil Productivity Data Clustering,” Indones. J. Inform. …, vol. 3, no. 1, pp. 56–64, 2023, [Online]. Available: https://journal.irpi.or.id/index.php/ijirse/article/view/488%0Ahttps://journal.irpi.or.id/index.php/ijirse/article/download/488/261

A. A. Simangunsong, I. Gunawan, and Z. M. Nasution, “Pengelompokkan hasil produksi tanaman perkebunan berdasarkan provinsi menggunakan metode K-Means,” J. Mach. Learn. Artif. Intelegence, vol. 1, no. 4, pp. 273–284, 2022, doi: 10.55123/jomlai.v1i4.1661.

D. Marlina, N. Lina, A. Fernando, and A. Ramadhan, “Implementasi Algoritma K-Medoids dan K-Means untuk Pengelompokkan Wilayah Sebaran Cacat pada Anak,” J. CoreIT J. Has. Penelit. Ilmu Komput. dan Teknol. Inf., vol. 4, no. 2, p. 64, 2018, doi: 10.24014/coreit.v4i2.4498.

Z. Nabila, A. Rahman Isnain, and Z. Abidin, “Analisis Data Mining Untuk Clustering Kasus Covid-19 Di Provinsi Lampung Dengan Algoritma K-Means,” J. Teknol. dan Sist. Inf., vol. 2, no. 2, p. 100, 2021, [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI

A. Dan Pemetaan Jumlah Penumpang Kereta Api Di, B. Wijaya, T. Maulana Fahrudin, and A. Nugroho, “Indonesia Menggunakan Metode Statistik Deskriptif Dan K-Means Clustering ARTICLEINFO ABSTRACT,” JurnalMantik, vol. 3, no. 2, pp. 1–9, 2019, [Online]. Available: https://iocscience.org/ejournal/index.php/mantik/index

W. J. Mawaddah, I. Gunawan, and I. P. Sari, “Implementation of Data Mining Algorithm for Clustering of Palm Oil Harvested Data,” JOMLAI J. Mach. Learn. Artif. Intell., vol. 1, no. 1, pp. 43–54, 2022, doi: 10.55123/jomlai.v1i1.163.

W. E. Sari, M. Muslimin, A. Franz, and P. Sugiartawan, “Deteksi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit dengan Algoritme K-Means,” SINTECH (Science Inf. Technol. J., vol. 5, no. 2, pp. 154–164, 2022, doi: 10.31598/sintechjournal.v5i2.1146.

mohamad jajuli nurul rohmawati, sofi defiyanti, “Implementasi Algoritma K-Means Dalam Pengklasteran Mahasiswa Pelamar Beasiswa,” Jitter 2015, vol. I, no. 2, pp. 62–68, 2015.

D. Anitasari and W. J. Pranot, “Clustering Penggunaan Fuel Pada PT Trasindo Murni Perkasa Menggunakan Algoritma K-Means,” J. Tek. Mesin, Ind. Elektro Dan Inform., vol. 3, no. 1, 2024.

S. Wijayanto and Y. Fathoni, M, “Pengelompokkan Produktivitas Tanaman Padi di Jawa Tengah Menggunakan Metode Clustering K-Means,” J. JUPITER, vol. 13, no. 2, pp. 212–219, 2021.

L. Gayatri and H. Hendry, “Pemetaan Penyebaran Covid-19 Pada Tingkat Kabupaten/Kota Di Pulau Jawa Menggunakan Algoritma K-Means Clustering,” Sebatik, vol. 25, no. 2, pp. 493–499, 2021, doi: 10.46984/sebatik.v25i2.1307.

P. Lay and A. B. Warsito, “Penerapan Algoritma K-Means Untuk Clustering Big Five Personality,” J. Tek. Mesin, Ind. Elektro Dan Inform., vol. 3, no. 1, 2024.

D. F. Pasaribu, I. S. Damanik, E. Irawan, Suhada, and H. S. Tambunan, “Memanfaatkan Algoritma K-Means Dalam Memetakan Potensi Hasil Produksi Kelapa Sawit PTPN IV Marihat,” BIOS J. Teknol. Inf. dan Rekayasa Komput., vol. 2, no. 1, pp. 11–20, 2021, doi: 10.37148/bios.v2i1.17.

H. Effendi, A. Syahrial, S. Prayoga, and W. D. Hidayat, “Penerapan Metode K-Means Clustering untuk Pengelompokan Lahan Sawit Produktif pada PT Kasih Agro Mandiri,” Teknomatika, vol. 11, no. 02, pp. 117–126, 2021.

A. Qurrata, A. Nazir, L. Handayani, and I. Afrianty, “Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia ( BI ),” vol. 4, no. 3, pp. 530–539, 2023, doi: 10.47065/josyc.v4i3.3343.

A. Sulistiyawati and E. Supriyanto, “Implementasi Algoritma K-means Clustring dalam Penetuan Siswa Kelas Unggulan,” J. Tekno Kompak, vol. 15, no. 2, p. 25, 2021, doi: 10.33365/jtk.v15i2.1162.

E. Muningsih, I. Maryani, and V. R. Handayani, “Penerapan Metode K-Means dan Optimasi Jumlah Cluster dengan Index Davies Bouldin untuk Clustering Propinsi Berdasarkan Potensi Desa,” vol. 9, no. 1, pp. 95–100, 2021.

E. Purwaningsih and E. Nurelasari, “Implementasi Metode K-Means Clustering Dengan Davies Bouldin Index Pada Analisis Faktor Penyebab Perceraian,” J. Inf. Manag., vol. 7, no. 2, 2023.

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