Klasterisasi Data Pertanian di Tingkat Provinsi Jambi Tahun 2021 Menggunakan Algoritma K-Means
DOI:
https://doi.org/10.47065/bulletincsr.v3i1.205Keywords:
Clustering; K-Means; Agriculture; IT; WekaAbstract
Data clustering provides an overview of the grouping of data through classification so that the groups have levels that have the same category. Cluster classification is carried out on agricultural data in Jambi Province with agricultural production groups including rice, rubber, palm oil, and coffee in the period 2021 for 11 (eleven) cities/districts including Jambi City, East Tanjung Jabung Regency, Sungai Full City, Kerinci Regency , Muaro Jambi Regency, West Tanjung Jabung Regency, Merangin Regency, Sarolangun Regency, Batanghari Regency, Tebo Regency, and Bungo Regency. The purpose of the cluster is used for allocations related to the budget, land, and support that can be used both to increase the amount of production and evaluation related to agriculture, especially at the Jambi Province level. So that the clustering carried out using the Weka application is 4 clusters, the result is that the cluster process stops at the 2nd iteration, the output information that occupies cluster 0 is 3 cities/districts, cluster 1 has 1 city/regency, cluster 2 has 2 cities/districts, and cluster 3 there are 5 cities/districts, with a total attribute of 11 (eleven) city/district data. Based on experiments on manual clustering, it can be concluded that the equations that can be seen from the output results using Weka and manual calculations are the same as doing two data iterations and with the same data group results.
Downloads
References
W. Xu, S. Wu, M. J. Er, C. Zheng, and Y. Qiu, “New non-negative sparse feature learning approach for content-based image retrieval,” IET Image Process., vol. 11, no. 9, 2017, doi: 10.1049/iet-ipr.2016.0726.
C. H. Lin, C. C. Chen, H. L. Lee, and J. R. Liao, “Fast K-means algorithm based on a level histogram for image retrieval,” Expert Syst. Appl., vol. 41, no. 7, pp. 3276–3283, 2014, doi: 10.1016/j.eswa.2013.11.017.
B. Demir and L. Bruzzone, “A Novel Active Learning Method in Relevance Feedback for Content-Based Remote Sensing Image Retrieval,” Geosci. Remote Sensing, IEEE Trans., vol. 53, no. 5, pp. 2323–2334, 2015, doi: 10.1109/TGRS.2014.2358804.
E. Rasywir, R. Sinaga, and Y. Pratama, “Analisis dan Implementasi Diagnosis Penyakit Sawit dengan Metode Convolutional Neural Network ( CNN ),” J. Paradig. UBSI, vol. 22, no. 2, pp. 117–123, 2020.
Fachruddin, M. R. Pahlevi, M. Ismail, and E. Rasywir, “Pengujian Implementasi Sistem Pengelolaan Keuangan Masjid Berbasis Web Dan Android,” J. Paradig. UBSI, vol. 22, no. 2, pp. 124–131, 2020.
Saparudin and E. Rasywir, “Pengenalan potensi anak melalui sidik jari menggunakan algoritma voting feature intervals 5 (vfi5) 1,” vol. I, no. I, pp. 25–30, 2012.
E. Rasywir and A. Purwarianti, “Eksperimen pada Sistem Klasifikasi Berita Hoax Berbahasa Indonesia Berbasis Pembelajaran Mesin,” J. Cybermatika, vol. 3, no. 2, pp. 1–8, 2015, [Online]. Available: http://cybermatika.stei.itb.ac.id/ojs/index.php/cybermatika/article/view/133.
M. R. Borroek, E. Rasywir, Y. Pratama, Fachruddin, and M. Istoningtyas, “Analysis on Knowledge Layer Application for Knowledge Based System,” in Proceedings of 2018 International Conference on Electrical Engineering and Computer Science, ICECOS 2018, 2019, pp. 177–182, doi: 10.1109/ICECOS.2018.8605262.
Dodo Zaenal Abidin, S. Nurmaini, R. F. Malik, Jasmir, E. Rasywir, and Y. Pratama, “A Model of Preprocessing For Social Media Data Extraction,” in 2019 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 2019, vol. 1, no. 1, pp. 1346–1358, doi: 10.1109/JPROC.2015.2447016.
E. Gho, D. Z. Abidin, and E. Rasywir, “Analisis Dan Penerapan Data Mining Pada Transaksi Penjualan Obat Menggunakan Algoritma Apriori Di Apotek Persijam,” Tek. Inform. STIKOM Din. Bangsa, pp. 56–64, 2013.
F. Fachruddin, E. Rasywir, Hendrawan, Y. Pratama, D. Kisbianty, and M. R. Borroek, “Real Time Detection on Face Side Image with Ear Biometric Imaging Using Integral Image and Haar- Like Feature,” 2018 Int. Conf. Electr. Eng. Comput. Sci., pp. 165–170, 2018.
K. Mustaqim, “Aplikasi Sistem Pakar Untuk Diagnosa Hama dan Penyakit Tanaman Kelapa Sawit Menggunakan Naive Bayes( STUDY KASUS?: PT . Perkebunan Nusantara V ),” 2013.
R. I. Fajri, “Identifikasi Penyakit Daun Tanaman Kelapa Sawit Menggunakan Support Vector Machine,” J. Teknol. Perkeb., 2014, [Online]. Available: http://repository.usu.ac.id/handle/123456789/42256.
A. Sidauruk and A. Pujianto, “Sistem Pakar Diagnosa Penyakit Tanaman Kelapa Sawit menggunakan Teorema Bayes,” J. Ilm. Data Manaj. dan Teknol. Inf., vol. 18, no. maret, 2017.
E. Rasywir, R. Sinaga, and Y. Pratama, “Evaluasi Pembangunan Sistem Pakar Penyakit Tanaman Sawit dengan Metode Deep Neural Network ( DNN ),” vol. 4, pp. 1206–1215, 2020, doi: 10.30865/mib.v4i4.2518.
Hendrawan, A. Haris, E. Rasywir, and Y. Pratama, “Sistem Pakar Diagnosis Penyakit Tanaman Karet dengan Metode Fuzzy Mamdani Berbasis Web,” J. Media Inform. Budidarma, vol. 4, no. 4, pp. 1225–1234, 2020, doi: 10.30865/mib.v4i4.2521.
Y. Hartiwi, E. Rasywir, Y. Pratama, and P. A. Jusia, “Eksperimen Pengenalan Wajah dengan fitur Indoor Positioning System menggunakan Algoritma CNN,” J. Paradig. UBSI, vol. 22, no. 2, 2020.
E. Rasywir, Y. Pratama, H. Hendrawan, and M. Istoningtyas, “Removal of Modulo as Hashing Modification Process in Essay Scoring System Using Rabin-Karp,” 2018 Int. Conf. Electr. Eng. Comput. Sci., pp. 159–164, 2018.
Y. Pratama and E. Rasywir, “Eksperimen Penerapan Sistem Traffic Counting dengan Algoritma YOLO (You Only Look Once) V.4.,” J. Media Inform. Budidarma, vol. 5, no. 4, p. 1438, 2021, doi: 10.30865/mib.v5i4.3309.
Y. Hartiwi, E. Rasywir, Y. Pratama, and P. A. Jusia, “Sistem Manajemen Absensi dengan Fitur Pengenalan Wajah dan GPS Menggunakan YOLO pada Platform Android,” J. Media Inform. Budidarma, vol. 4, pp. 1235–1242, 2020, doi: 10.30865/mib.v4i4.2522.
Fachruddin, M. R. Pahlevi, M. Ismail, E. Rasywir, and Y. Pratama, “Analisis Usability Pada Implementasi Sistem Pengelolaan Keuangan Masjid Menggunakan USE Questionnaire,” J. Media Inform. Budidarma, vol. 4, pp. 1216–1224, 2020, doi: 10.30865/mib.v4i4.2518.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Klasterisasi Data Pertanian di Tingkat Provinsi Jambi Tahun 2021 Menggunakan Algoritma K-Means
ARTICLE HISTORY
How to Cite
Issue
Section
Copyright (c) 2022 Yovi Pratama, Yuga Pramudya, Evan Albert, Mumtaz Ilham S, Rio Ferdinand, Verwin Juniansyah, Errissya Rasywir
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
