IMPLEMENTASI METODE CERTANITY FACTOR UNTUK MENDETEKSI HAMA PENYAKIT TANAMAN PADI BERBASIS MOBILE
DOI:
https://doi.org/10.31000/jika.v10i1.15012Abstract
Penelitian ini megambil topik yang sesuai dan sejalan serta mendukung dengan program pemerintah yaitu tentang ketahanan pangan. Penelitian ini membahas tentang sebuah metode dalam mendeteksi dan mendiagnosa hama dan penyakit tanman padi. Tujuan dari penelitian ini adalah ikut membantu bagi petani dalam mengantisipasi hama dan dan penyakit sehingga diharapkan hasil panen bisa optimal. Jalan penelitian menggunakan metode yaitu Certainty Factor dan metode waterfall untuk tahapan pengembangan sistem yang terdiri dari analisis, desain, implementasi, dan pengujian sedangkan Certainty Factor untuk perhitungan tingkat akurasi. Hasil dari penelitian ini adalah sebuah aplikasi yang berbasis mobile diperuntukan bagi petani khususnya dan pemerintah dalam mendukung program ketahanan pangan dengan jalan menaikan hasil panen khusunya petani padiReferences
Adellia, D., Cendekia Siregar, A., Putri Alkadri, S., Jendral Ahmad Yani No, J., Belitung Laut, B., Tenggara, P., Pontianak, K., & Barat, K. (n.d.). JEPIN (Jurnal Edukasi dan Penelitian Informatika) Penerapan Metode Certainty Factor pada Sistem Pakar Diagnosa Hama dan Penyakit pada Tanaman Tomat.
Aini N Dwi, & Rudianto. (2024). Aplikasi Ruang Padi Untuk Diagnosa Hama Tanaman Padi. Jurnal INSAN (Journal of Information Systems Management Innovation, 4(2).
Badan Pusat Statistik. (2023). Luas Panen dan Produksi Padi di Indonesia 2023. Berita Resmi Statisik.
Beding, A., & Tiro, B. (2020). Uji Adaptasi Varietas Unggul Padi Tadah Hujan Kabupaten Jayapura, Papua. Pengkajian Dan Pengembangan Teknologi Pertanian, 151–161.
Gusti, I., Putu, A., Savitri, G., & Sutrisni, E. (n.d.). Strategi Memberantas Hama Terhadap Tanaman Padi dengan Pestisida Nabati di Desa Sesandan Wanasari Tabanan.
Hutabarat F, P., & Nasution, Y. R. (n.d.). Sistem Pakar Diagnosis Hama dan Penyakit pada Tanaman Padi Fatur.
Irfan Yahya, N., Lestanti, S., & Nur Budiman, S. (2022). Sistem Pakar Diagnosis Hama dan Penyakit Tanaman Aglonema Menggunakan Metode Certainty Factor. In Jurnal Mahasiswa Teknik Informatika) (Vol. 6, Issue 2).
Kasno, A., Setyorini, D., Wayan Suastika Balai Penelitian Tanah, I., Tentara Pelajar No, J., & Bogor, C. (n.d.). Makalah REVIEW.
Kusuma, B., Hermanto, T. I., & Lestari, C. D. (2025). Klasifikasi Jenis Penyakit Pada Tanaman Padi Menggunakan Algoritma Convolutional Nueral Network. JIKO (Jurnal Informatika Dan Komputer), 9(1), 40. https://doi.org/10.26798/jiko.v9i1.1395
Maria, E., Fadlin, F., & Taruk, M. (n.d.). Diagnosis Penyakit Tanaman Padi Menggunakan Metode Promethee. 15(1). https://doi.org/10.30872/jim.v15i1.2844
Matias Tobing, D. L., Pawan, E., Neno, F. E., & Kusrini, kusrini. (2019). Sistem Pakar Mendeteksi Penyakit Pada Tanaman Padi Menggunakan Metode Forward Chaining. In Tlp (Vol. 884, Issue 0274).
Mawardi, N. K., Ratri, W. S., & Widiatmi, S. (2020). Analysis of Feasibility of Rice Farming in the Rained Land in Girikarto Village, Panggang Sub-District, GunungKidul Disctict . Jurnal Pertanian Agros, 22(2).
Meniati, L., Yanti, N., Gaol, L., & Santoso, I. (2022). Sistem Pakar Mendiagnosa Penyakit Tanaman Kakao Menggunakan Metode Certainty Factor. Jurnal Teknologi Sistem Informasi Dan Sistem Komputer TGD), 5(1), 83–94. https://ojs.trigunadharma.ac.id/
Nafisa, L., Nur Ikhsanto, M., & Teknik Informatika STMIK Dharma Wacana, P. (n.d.). Penerapan Metode Forward Chaining untuk Mengidentifikasi Hama dan Penyakit Tanaman Padi (Studi Kasus : Desa Purworejo Kec. Kotagajah Kab. Lampung Tengah). Jurnal IRobot (International Research on Big-Data and Computer Technology), 5, 48.
Novia, R. A., Satriani, R., Agribisnis, J., Pertanian, F., Jenderal, U., & Purwokerto, S. (n.d.). Analisis Efisiensi Teknis Usahatani Padi Sawah Tadah Hujan di Kabupaten Banyumas Technical Analysis of Rained Lowland Rice Farming in Banyumas Regency.
Rahmah, M., & Fitriana, N. H. I. (2023). Gerakan Pengendalian Hama Wereng pada Tanaman Padi di Kecamatan Cerme Kabupaten Gresik. COMSERVA : Jurnal Penelitian Dan Pengabdian Masyarakat, 3(4), 1339–1345.
Setyaputri, K. E., Fadlil, A., & Sunardi, D. (n.d.). Analisis Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit THT.
Sularno, S., & Anggraini, P. (2017a). Penerapan Algoritma C4.5 untuk Klasifikasi Tingkat Keganasan Hama pada Tanaman Padi (Studi Kasus : Dinas Pertanian Kabupaten Kerinci). Jurnal Sains Dan Informatika, 3(2), 161.
Sularno, S., & Anggraini, P. (2017b). Penerapan Algoritma C4.5 untuk Klasifikasi Tingkat Keganasa Hama pada Padi (Studi Kasus : Dinas Pertanian Kabupaten Kerinci). Jurnal Sains Dan Informatika, 3(2), 161.
Downloads
Published
Issue
Section
License
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with International Journal of Advances in Intelligent Informatics agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- 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.
Licensing for Data Publication
International Journal of Advances in Intelligent Informatics use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Open Data Commons Attribution License, http://www.opendatacommons.org/licenses/by/1.0/ (default)
Creative Commons CC-Zero Waiver, http://creativecommons.org/publicdomain/zero/1.0/
Open Data Commons Public Domain Dedication and Licence, http://www.opendatacommons.org/licenses/pddl/1-0/
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.