Penerapan Algoritma Naïve Bayes Untuk Diagnosa Hama Pada Tanaman Aglaonema SP dan Monstera Adansonii
- M Riandi Widiantoro Universitas Yapis Papua, Jayapura, Indonesia
-
Salahudin Robo
*
Universitas Yapis Papua, Jayapura,
Indonesia
- Almukarrama Almukarrama Universitas Yapis Papua, Jayapura, Indonesia (*) Corresponding Author
Abstract
Aglaonema sp and Monstera Adansonii are the most popular ornamental plants during the COVID-19 pandemic. Aglaonema sp and Monstera Adansonii become the target of the keepers because the colors and patterns on the leaves are unique. Despite the high popularity of Aglaonema sp and Monstera adansonii, not many keepers know the problems faced by their plants. The least number of triggers is knowledge of the keepers in caring for their plants. Therefore, to help the community in maintaining Aglaonema sp and Monstera Adansonii plants, an expert or expert in the field of ornamental plants is takes. Due to the difficulty of finding an expert, a system that is able to keep knowledge from an expert is required. An expert system is part of an intelligence that uses a person's knowledge that is summarized and processed carefully to solve problems. One of the statistical data calculation methods is Naïve Bayes. The Naïve Bayes method is a computational technique for predicting probabilities by calculating how many possible sets by adding up the frequency and combined values of the dataset. The software created is able to share understanding with the community about Aglaonema sp and monstera adansonii plants and what treatment should be given to their ornamental plants
Downloads
References
F. Arela, “9 Jenis Tanaman Hias Yang Populer Selama Pandemi,” wolipop, 2020. https://wolipop.detik.com/home/d-5229010/9-jenis-tanaman-hias-yang-viral-selama-pandemi.
A. Akbar, “Penggunaan dan Nilai Ekonomi dari Tanaman Aglaonema sp. di Kalangan Pedagang Tanaman Hias Sekitar Cengkareng dan Pulo Gadun,” J. Bios Logos, vol. 11, no. 2, pp. 122–128, 2021.
F. Damayanti, “Potensi Pemuliaan Mutasi Radiasi sebagai upaya Peningkatan Variasi Genetik pada Tanaman Hias,” EduBiologia Biol. Sci. Educ. J., vol. 1, no. 2, p. 78, 2021, doi: 10.30998/edubiologia.v1i2.9300.
M. M. Amalia, Ernawati, and A. Wijanarko, “Implementasi Metode Naive Bayes dalam Sistem Pakar Diagnosis Hama dan Penyakit Pada Tanaman Hias Aglaonema Sp,” vol. 10, no. 1, 2022.
F. Agus, O. I. Gifari, and Z. A. Kamil, “Komputasi Numerik pada Kasus Penentuan Penyakit Tanaman Hias,” Inform. Mulawarman J. Ilm. Ilmu Komput., vol. 16, no. 1, p. 42, 2021, doi: 10.30872/jim.v16i1.5262.
P. S. Dewi, C. K. Sastradipraja, and D. Gustian, “Sistem Pendukung Keputusan Kenaikan Jabatan Menggunakan Metode Algoritma Naïve Bayes Classifier,” J. Teknol. dan Inf., vol. 11, no. 1, pp. 66–80, 2021, doi: 10.34010/jati.v11i1.3593.
S. Robo, A. Sah, A. T. Sidarmawan, and M. T. Jufri, “Penerapan Metode Waterfall Dalam Pengembangan Sistem Informasi E-Learning (Studi Kasus: SMP Negeri 5 Jayapura),” JSAI (Journal Sci. Appl. Informatics), vol. 4, no. 2, pp. 154–164, 2021, doi: 10.36085/jsai.v4i2.1618.
L. Liliana, “A New Model of Ishikawa Diagram For Quality Assessment,” IOP Conf. Ser. Mater. Sci. Eng., vol. 161, no. 1, 2016, doi: 10.1088/1757-899X/161/1/012099.
S. Nurhayati, M. Tonggiroh, and N. Aini, “Sistem Pakar Diagnosa Penyakit Telinga Hidung Tenggorokan Menggunakan Dempster Shafer,” pp. 43–48, 2022.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Penerapan Algoritma Naïve Bayes Untuk Diagnosa Hama Pada Tanaman Aglaonema SP dan Monstera Adansonii
Pages: 116-122
Copyright (c) 2022 M Riandi Widiantoro, Salahudin Robo, Almukarrama Almukarrama
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).
