Klasifikasi Data Mining Pada Bibit Pertanian Dengan Menggunakan Algoritma Naïve Bayes
DOI:
https://doi.org/10.30865/resolusi.v5i1.2172Keywords:
Calcific; Data Mining; Naïve BayesAbstract
Choosing the right oil palm seedlings is one of the efforts to increase the productivity of oil palm plants. At the time of seedling selection, the problem that is often faced is that not all types of seeds can be as desired by farmers against the conditions of different types of oil palm fruit seeds. Therefore, a system is needed that helps in determining the type of superior seedlings according to the needs of farmers. In this research the author applies a machine learning prediction model in determining oil palm seedlings based on leaf type, stem type, seed origin and stem candidates. The purpose of this research is to produce a classification model for determining oil palm seedlings and can provide accurate training for farmers in choosing superior seeds and also can farmers know the characteristics of superior seeds. The method used in this research is naïve bayes. In the first test, both models managed to achieve an accuracy of 84% and an F1-score value of 66%. However, the best performing Naïve Bayes model is the one used in the second test scenario, which is applied as a prediction model in determining oil palm seedlings through the website developed in this study, in the form of a Data Mining Classification System on Agricultural Seedlings at the Agricultural Extension Center of Tuah Negeri District, Musi Rawas Regency Based on Website which can assist in the selection process of oil palm seedlings that will be planted and get superior seedling results.
Downloads
References
R. Azhar, A. Surahman, and C. Juliane, “Analisis Sentimen Terhadap Cryptocurrency Berbasis Python TextBlob Menggunakan Algoritma Naïve Bayes,” J. Sains Komput. Inform. (J-SAKTI, vol. 6, no. 1, pp. 267–281, 2022.
A. P. S. Iskandar and I. K. D. G. Supartha, “Sistem Informasi Geografis Pemetaan Sebaran Alumni,” J. Comput. Sci. Informatics Eng., vol. 3, no. 2, pp. 172–180, 2019, doi: 10.29303/jcosine.v3i2.307.
C. A. Febrina, F. Ariany, and D. A. Megawaty, “Aplikasi E-Marketplace Bagi Pengusaha Stainless Berbasis Mobile Di Wilayah Bandar Lampung,” J. Teknol. dan Sist. Inf., vol. 2, no. 1, pp. 15–22, 2021, [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI
M. Ridho Handoko, “Sistem Pakar Diagnosa Penyakit Selama Kehamilan Menggunakan Metode Naive Bayes Berbasis Web,” J. Teknol. dan Sist. Inf., vol. 2, no. 1, pp. 50–58, 2021, [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI
S. Widaningsih, “Penerapan Data Mining untuk Memprediksi Siswa Berprestasi dengan Menggunakan Algoritma K Nearest Neighbor,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 3, pp. 2598–2611, 2022, doi: 10.35957/jatisi.v9i3.859.
M. S. Wahyudin, N. Lestari, T. H. B. Aviani, and S. T. Faulina, “Sistem Informasi Point Of Sales Berbasis Web Pada Toko Sismaret Menggunakan Framework Codeigniter,” J. Teknol. Inf. Mura, vol. 16, no. 1, pp. 44–53, 2024, doi: 10.32767/jti.v16i1.2120.
C. H. Yanti and S. A. Arnomo, “Rancang Bangun Sistem Informasi Point of Sale Berbasis Web,” Comput. Sci. Ind. Eng., vol. 9, no. 3, pp. 18372–18381, 2023, doi: 10.33884/comasiejournal.v9i3.7669.
Y. Handrianto and B. Sanjaya, “Model Waterfall Dalam Rancang Bangun Sistem Informasi Pemesanan Produk Dan Outlet Berbasis Web,” J. Inov. Inform., vol. 5, no. 2, pp. 153–160, 2020, doi: 10.51170/jii.v5i2.66.
A. Nugraha, O. Nurdiawan, and G. Dwilestari, “Penerapan Data Mining Metode K-Means Clustering Untuk Analisa Penjualan Pada Toko Yana Sport,” JATI (Jurnal Mhs. Tek. Inform., vol. 6, no. 2, pp. 849–855, 2022, doi: 10.36040/jati.v6i2.5755.
P. G. S. C. Nugraha, “Rancang Bangun Sistem Informasi Software Point of Sale (Pos) Dengan Metode Waterfall Berbasis Web,” JST (Jurnal Sains dan Teknol., vol. 10, no. 1, pp. 92–103, 2021, doi: 10.23887/jstundiksha.v10i1.29748.
Suprianto, M. Fadlan, and D. Prayogi, “Perancangan Aplikasi Point of Sale Berbasis Web Pada,” J. Sebatik, vol. 25, no. 2, pp. 624–631, 2023.
S. Suprianto, M. Fadlan, and D. Prayogi, “Perancangan Aplikasi Point of Sale Berbasis Web Pada Toko Project Salfa Tarakan,” Sebatik, vol. 25, no. 2, pp. 624–631, 2021, doi: 10.46984/sebatik.v25i2.1519.
F. Yudianto, M. A. Firdaus, F. A. Susanto, and T. Herlambang, “Perancangan Sistem Informasi Penjualan Toko Online Galeri Nada Berbasis Website,” Remik Ris. dan E-Jurnal Manaj. Inform. Komput., vol. 6, no. 3, pp. 575–585, 2022.
F. K. Pratama, D. W. Widodo, and N. Shofia, “Implementasi Metode Naïve Bayes dalam Mengklasifikasi Penerima Program Keluarga Harapan ( PKH ) Desa Minggiran Kediri,” Semin. Nas. Inov. Teknol. UN PGRI Kediri, pp. 23–28, 2021, [Online]. Available: https://proceeding.unpkediri.ac.id/index.php/inotek/article/view/1072%0Ahttps://proceeding.unpkediri.ac.id/index.php/inotek/article/download/1072/685
Yensi, “3388-Article Text-11521-2-10-20220825 JD 1,” J. Pendidik. Teknol. Inf. dan Komun., vol. 2, pp. 52–64, 2022.
A. Damuri, U. Riyanto, H. Rusdianto, and M. Aminudin, “Implementasi Data Mining dengan Algoritma Naïve Bayes Untuk Klasifikasi Kelayakan Penerima Bantuan Sembako,” JURIKOM (Jurnal Ris. Komputer), vol. 8, no. 6, p. 219, 2021, doi: 10.30865/jurikom.v8i6.3655.
F. Prasetya and F. Ferdiansyah, “Analisis Data Mining Klasifikasi Berita Hoax COVID 19 Menggunakan Algoritma Naive Bayes,” J. Sist. Komput. dan Inform., vol. 4, no. 1, p. 132, 2022, doi: 10.30865/json.v4i1.4852.
A. L. R. Entini and K. Handoko, “Jurnal Comasie IMPLEMENTASI DATA MINING DENGAN ALGORITMA NAIVE BAYES,” J. Comaise, vol. 03, pp. 343–351, 2023.
B. Ginting and F. Riandari, “Implementasi Metode K-Means Clustering Dalam Pengelompokan Bibit Tanaman Kopi Arabika,” J. Nas. Komputasi dan Teknol. Inf., vol. 3, no. 2, pp. 151–157, 2020, doi: 10.32672/jnkti.v3i2.2381.
N. Agustina, A. Adrian, and M. Hermawati, “Implementasi Algoritma Naïve Bayes Classifier untuk Mendeteksi Berita Palsu pada Sosial Media,” Fakt. Exacta, vol. 14, no. 4, p. 206, 2022, doi: 10.30998/faktorexacta.v14i4.11259.
E. R. Alfiyyah, R. Andreswari, and E. Sutoyo, “Analisis dan deteksi fraud pada data panggilan menggunakan algoritma k-nearest neighbor (studi kasus: pt xyz),” e-Proceeding Eng., vol. 7, no. 2, pp. 6640–6646, 2020.
A. Saepudin, R. Aryanti, E. Fitriani, and D. Ardiansyah, “Perancangan Sistem E-Commerce Menggunakan Model Rapid Application Development Pada Pengurus Cabang Judo Karawang,” Paradig. - J. Komput. dan Inform., vol. 23, no. 1, pp. 25–32, 2021.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Klasifikasi Data Mining Pada Bibit Pertanian Dengan Menggunakan Algoritma Naïve Bayes
ARTICLE HISTORY
Issue
Section
Copyright (c) 2024 Pandu Rahmat Aprianto, Novi Lestari, Cindi Wulandari
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).
