Herdiyanto, Asep Ardi (2019) Sistem Diagnosa Penyakit Tanaman Mangga Menggunakan Metode Bayesian Network. Sarjana thesis, Universitas Brawijaya.
Abstract
Sistem Diagnosis Penyakit Tanaman Mangga menggunakan Metode Bayesian Network merupakan aplikasi yang bertujuan membantu masyarakat khususnya para petani tanaman mangga dalam mendiagnosis hama dan penyakit tanaman mangga agar segera dilakukan penanganan gejala secara din'. Sistem ini dibangun berdasarkan masalah yang terjadi dimasyarakat yaitu sulitnya dalam mengenali hama dan penyakit tanaman mangga. Dikarenakan hama dan penyakit tanaman mangga memiliki gejala-gejala yang berjumlah cukup banyak serta terdapat kesamaan gejala yang dimiliki beberapa penyakit. Hal ini termasuk salah satu penyebab berkurangnya tingkat produktifitas tanaman mangga di Indonesia, tercatat dari riset Badan Pusat Statistik tahun 2015 mengalami penurunan panen nasional sebesar 252 ribu ton dengan keseluruhan jumlah 2.178 ribu ton tahun 2015. Namun pada tahun 2014 berjumlah 2,431 juta ton. Metode Bayeion Network dipilih pada penelitian in karena Bayesian Network mencakup seluruh fitur pada data lath, sehingga membuat metode ini optimal dalam melakukan proses perhitungan. Sistem ini menggunakan sistem operasi Android, karena android cukup merata dan populer di pasar smartphone Indonesia hingga sekarang. Data yang digunakan pada penelitian ini diperoleh dari dosen Fakultas Pertanian Universitas Brawijaya, kota Malang. Hash penelitian ini menunjukkan bahwa, pada pengujian akurasi dari 30 data uji mendapatkan tingkat akurasi sebesar 87,5%.
English Abstract
The Diagnosis of Mango Disease System using the Bayesian Network Method is an application that aims to help the community, especially the farmers of mango plants, in diagnosing mango pests and plant diseases so that the symptoms can be handled immediately. This system is built based on the problems that occur in the community, namely the difficulty in recognizing pests and diseases of mango plants. Because mango pests and diseases have quite a number of symptoms and there are similarities in symptoms that some diseases have.This is one of the causes of reduced productivity levels of mango plants in Indonesia, recorded from the 2015 Central Bureau of Statistics research experiencing a decline in national harvests of 252 thousand tons with a total number of 2,178 thousand tons in 2015. However in 2014 amounted to 2.431 million tons. The Bayeion Network method was chosen in this study because Bayesian Network includes all the features in the data lath, thus making this method optimal in carrying out the calculation process. This system uses the Android operating system, because Android is quite even and popular in the Indonesian smartphone market until now. The data used in this study were obtained from lecturers at the Faculty of Agriculture, Brawijaya University, Malang. The hash of this study shows that, in testing the accuracy of 30 test data, the accuracy rate was 87.5%.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FILKOM/2019/17/051902187 |
| Uncontrolled Keywords: | Gejala,diagnosa,penyakit tanaman mangga,Bayesian network-Symptoms,diagnosis,mango plant disease,Bayesian network |
| Subjects: | 600 Technology (Applied sciences) > 632 Plant injuries, diseases, pests > 632.9 General topics of pest and disease control |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Sugeng Moelyono |
| Date Deposited: | 09 Jun 2020 05:46 |
| Last Modified: | 19 Oct 2021 09:31 |
| URI: | http://repository.ub.ac.id/id/eprint/168844 |
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