Pemetaan Kondisi Lingkungan Tanam menggunakan K-Means Clustering

Ni'ma Kholila; M Mujiono; Dona Wahyudi

doi:10.53624/jsitik.v1i2.182

Authors

Ni'ma Kholila Akademi Komunitas Negeri Putra Sang Fajar Blitar http://orcid.org/0000-0002-9065-8783
M Mujiono Akademi Komunitas Negeri Putra Sang Fajar Blitar
Dona Wahyudi Akademi Komunitas Negeri Putra Sang Fajar Blitar

DOI:

https://doi.org/10.53624/jsitik.v1i2.182

Keywords:

Pemetaan, Kondisi Lingkungan Tanam, K-Means

Abstract

Melalui pendekatan clustering, data rekam yang terdiri dari waktu tanam, ph, suhu air, suhu udara, dan nilai TDS dapat dimanfaatkan guna memetakan kondisi lingkungan tanam. Melalui pemetaan kondisi lingkungan tanam, petani mendapatkan informasi tambahan terkait kondisi lingkungan tanam milik petani. Melalui informasi tersebut, diharapkan petani dapat memberikan tindakan pertanian yang sesuai dengan kondisi lingkungan tanam, lebih efektif dan efisien. Pemetaan kondisi lingkungan tanam menggunakan k-means clustering algorithm dalam 3 (tiga) cluster. Masing-masing merupakan cluster kondisi lingkungan tanam yang kurang nutrisi dan kurang air, cukup nutrisi tetapi kurang air, serta cukup nutrisi dan cukup air. Cluster testing menggunakan elbow method menunjukkan bahwa jumlah cluster optimal dalam pengelompokan K-Means adalah 3 cluster dengan nilai inersia 199.065.

Downloads

Download data is not yet available.

References

BPS, “Statistik Hortikultura 2021,” vol. 21, no. 1, pp. 1–9, 2020.

A. Nalendra, M. N. Fuad, D. Wahyudi, N. Kholila, and M. Mujiono, “Effectiveness of the Use of the Internet of Things (IoT) in the Agricultural Sector,” International Journal of Science and Society, vol. 4, no. 3, pp. 474–478, Sep. 2022, doi: 10.54783/ijsoc.v4i3.541.

W. W. Widiyanto, F. Nugroho, and K. Kusrini, “Implementation Of The K-Means Cluster Algorithm In Rice Production Mapping And As A Decision Support For Agricultural Function Transition,” Jurnal Informa : Jurnal Penelitian dan Pengabdian Masyarakat, vol. 5, no. 4, pp. 46–52, 2020, doi: 10.46808/INFORMA.V5I4.155.

I. H. Hayatu, A. Mohammed, B. A. Ismaâ€TMeel, and S. Y. Ali, “K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA,” FUDMA JOURNAL OF SCIENCES, vol. 4, no. 2, pp. 780–787, Nov. 2020, doi: 10.33003/fjs-2020-0402-363.

N. B. Nugraha, E. Alimudin, and B. V. Indriyono, “Implementasi K-Means Clustering Pada Sistem Pakar Penentuan Jenis Sayuran,” Journal of Innovation Information Technology and Application (JINITA), vol. 4, no. 2, pp. 133–141, 2022, doi: 10.35970/JINITA.V4I2.1627.

B. Chong, “K-means clustering algorithm: a brief review,” Academic Journal of Computing & Information Science, vol. 4, no. 5, 2021, doi: 10.25236/ajcis.2021.040506.

K. P. Sinaga and M. S. Yang, “Unsupervised K-means clustering algorithm,” IEEE Access, vol. 8, pp. 80716–80727, 2020, doi: 10.1109/ACCESS.2020.2988796.

A. K. Nalendra, D. Wahvudi, M. Mujiono, M. N. Fuad, and N. Kholila, “IoT-Agri: IoT-based Environment Control and Monitoring System for Agriculture,” pp. 1–6, 2023, doi: 10.1109/ICIC56845.2022.10006964.

I. Yuniarfi and S. Saifulloh, “Penerapan Algoritma K-means Untuk Pengelompokan Usia Pasien Penerima Vaksin di KAB. Ngawi,” Jurnal Informasi dan Komputer, vol. 9, no. 2, pp. 51–62, 2021, doi: 10.35959/JIK.V9I2.211.

S. A. B. C. Busro et al., “Rancangan Pembuatan API Website Data Tanaman Obat Dan Langka Kabupaten Kediri,” Bulletin of Information Technology (BIT), vol. 3, no. 4, pp. 255–260, Dec. 2022, doi: 10.47065/BIT.V3I4.373.

R. A. Purba and S. Sondang, “Design and Build Monitoring System for Pregnant Mothers and Newborns using the Waterfall Model,” INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, vol. 6, no. 1, pp. 29–42, Feb. 2022, doi: 10.29407/INTENSIF.V6I1.16085.

I. Benawan, D. Mutiara, K. Nugraheni, B. Noranita, and G. Aryotejo, “Digital Education Game for TK-A Level Students Using Multimedia Development Life Cycle Method,” INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, vol. 7, no. 1, pp. 68–83, Feb. 2023, doi: 10.29407/INTENSIF.V7I1.18671.

M. Iqbal, F. Barchia, and A. Romeida, “PERTUMBUHAN DAN HASIL TANAMAN MELON (Cucumis melo L.) PADA KOMPOSISI MEDIA TANAM DAN FREKUENSI PEMUPUKAN YANG BERBEDA,” Jurnal Ilmu-Ilmu Pertanian Indonesia, vol. 21, no. 2, pp. 108–114, 2019, doi: 10.31186/JIPI.21.2.108-114.

A. Susanto and ; Meiryani, “Functions, Processes, Stages And Application Of Data Mining,” INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH, vol. 8, p. 7, 2019.

A. F. Febrianti, A. H. Cabral, and G. Anuraga, “K-Means Clustering Dengan Metode Elbow Untuk Pengelompokan Kabupaten Dan Kota Di Jawa Timur,” Seminar Nasional Hasil Riset dan Pengabdian -SNHRP, pp. 863–870, 2018.

S. Sunardi, A. Fadlil, and N. M. P. Kusuma, “Comparing Data Mining Classification for Online Fraud Victim Profile in Indonesia,” INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, vol. 7, no. 1, pp. 1–17, Feb. 2023, doi: 10.29407/INTENSIF.V7I1.18283.

Sucipto, Kusrini, and E. L. Taufiq, “Classification method of multi-class on C4.5 algorithm for fish diseases,” in Proceeding - 2016 2nd International Conference on Science in Information Technology, ICSITech 2016: Information Science for Green Society and Environment, 2016, pp. 5–9. doi: 10.1109/ICSITech.2016.7852598.

M. A. Jassim and S. N. Abdulwahid, “Data Mining preparation: Process, Techniques and Major Issues in Data Analysis,” IOP Conference Series: Materials Science and Engineering, vol. 1090, no. 1, p. 12053, 2021, doi: 10.1088/1757-899X/1090/1/012053.

E. Umargono, J. E. Suseno, and V. G. S. K., “K-Means Clustering Optimization using the Elbow Method and Early Centroid Determination Based-on Mean and Median,” vol. 474, no. Isstec 2019, pp. 234–240, 2020, doi: 10.5220/0009908402340240.

D. Ayu, I. C. Dewi, and K. Pramita, “Analisis Perbandingan Metode Elbow dan Silhouette pada Algoritma Clustering K-Medoids dalam Pengelompokan Produksi Kerajinan Bali,” Matrix : Jurnal Manajemen Teknologi dan Informatika, vol. 9, no. 3, pp. 102–109, Nov. 2019, doi: 10.31940/MATRIX.V9I3.1662.