Expert System for Diagnosing Disease Symptoms of Rice Pests Using the Dempster Shafer Algorithm and Fuzzy Tsukamoto Algorithm
(1) Universitas Langlangbuana
(2) Universitas Langlangbuana
(3) Universitas Langlangbuana
(4) Universitas Langlangbuana
(5) Universitas Langlangbuana
(6) Universitas Langlangbuana
(*) Corresponding Author
Abstract
Agriculture is the largest sector in almost every developing country economy. This sector produces food for most of the population in the country. Some Indonesian people work as farmers who have an important role to ensure the availability of basic ingredients, namely rice from rice. However, the limited number of experts, namely Field Agricultural Extension Officers (PPL) results in limited counseling that will be obtained by farmers, because to overcome all the problems faced by farmers, it is constrained by time and the number of farmers who have problems with their crops. In this case, farmers find it difficult to deal with problems of pests and diseases that attack rice, therefore a tool or an expert application is needed that can help farmers to diagnose pests and diseases of rice in order to provide solutions to overcome them. In connection with that, this study aims to develop an application design of an expert system for diagnosing rice pests using the Fuzzy Tsukamoto algorithm which is a method for classifying objects based on the most similar data, and adding the Dempster Shafer algorithm as a comparison of the methods used to obtain data. maximum result validation. By using the Fuzzy Tsukamoto Algorithm, the author classifies similar objects, in this case the symptoms that often occur during the rice harvest season, then compares them with the Dempster Shafter Algorithm to obtain validation of diseases that occur in rice plants based on the classification of symptoms that have been mapped. . Furthermore, the system will provide the best decision to provide advice related to diseases experienced by rice plants so that farmers can immediately resolve them.
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D. Darmastuti, “Implementasi Metode Fuzzy Tsukamoto Dalam Sistem Pendeteksi Penyakit Jantung,” J. Sist. dan Teknol. Inf., vol. 16, no. 2, pp. 1–6, 2019.
D. A. Rivai and B. E. Purnama, “Pembangunan Sistem Informasi Pengolahan Data Nilai Siswa Berbasis Web Pada Sekolah Menengah Kejuruan (SMK) Miftahul Huda Ngadirojo,” vol. 3, no. 2, pp. 19–25, 2014.
D. Priyanti, “Sistem Informasi Data Penduduk Pada Desa Bogoharjo Kecamatan Ngadirojo Kabupaten Pacitan,” IJNS - Indones. J. Netw. Secur., vol. 2, no. 4, p. 56, 2013.
F. Wafiyah, N. Hidayat, and R. S. Perdana, “Implementasi Algoritma Dempster Shafer untuk Klasifikasi Penyakit Demam,” J. Pengemb. Teknol. Inf. dan Ilmu Komputer. Univ. Brawijaya, vol. 1, no. 10, pp. 1210–1219, 2017.
F. Nugraha, B. Surarso, and B. Noranita, “Sistem Pendukung Keputusan Evaluasi Pemilihan Pemenang Pengadaan Aset dengan Metode Dempster Shafer ,” J. Sist. Inf. Bisnis, vol. 2, no. 2, pp. 67–72, 2019.
H. M. S. A. Haviluddin; “Sistem Pendukung Keputusan Untuk Menentukan Siswa Masuk ke Suatu Jurusan,” J. Inform. Mulawarman, vol. 6, no. 3, pp. 98–104, 2018.
H. T. Sihotang and M. Siboro, “Aplikasi Sistem Pendukung Keputusan Penentuan Siswa Bermasalah Menggunakan Metode Dempster Shafer Pada Sekolah SMP Swasta Mulia Pratama Medan,” J. Informatics Pelita Nusant., vol. 1, no. 1, pp. 1–6, 2008.
K. Juerg., M. Paul Andre. " A Mathematical Theory of Hints: An Approach to the Dempster-Shafer Theory of Evidence (Lecture Notes in Economics and Mathematical Systems ", Springer 2015
L. Jay, " The Handbook of Applied Expert Systems 1st Edition ", CRC Press, 2017
I. A. Nasution, “Sistem pendukung keputusan penentuan pemilihan laptop dengan menerapkan fuzzy tahani,” Pelita Inform. Budi Darma, Vol. VI, Nomor 1, Maret 2014, vol. VI, no. 0911378, pp. 93–96, 2017.
M Komarudin, “Pengujian perangkat Lunak metode Black box berbasis partitions pada aplikasi sistem informasi di sekolah,” J. Mikrotik, vol. o6, no. 1, pp. 02–16, 2016.
M. S. Mustaqbal, R. F. Firdaus, and H. Rahmadi, “Pengujian Aplikasi Menggunakan Black Box Testing Boundary Value Analysis (Studi kasus: Aplikasi Prediksi Kelulusan SNMPTN),” Penguji. Apl. Menggunakan Black Box Test. Bound. Value Anal. (Studi Kasus Apl. Prediksi Kelulusan SNMPTN), vol. I, no. 3, p. 34, 2018.
N. L. G. P. Suwir Mayanti, “Penerapan Metode Fuzzy Tsukamoto Untuk Sistem Rekomendasi Pemilihan Mobil,” Techno.Com, vol. 16, no. 2, pp. 120–131, 2017.
N. Hidayati, “Penggunaan Rapid Application Development dalam Rancang Bangun Program Simpan Pinjam pada Koperasi,” Intensif, vol. 2, no. 2, p. 87, 2018.
N. Hermanto, “Sistem Pendukung Keputusan Menggunakan Metode Fuzzy Tsukamoto Untuk Menentukan Jurusan Pada Smk Bakti Purwokerto,” Semin. Nas. Teknol. Inf. Komun. Terap. 2018 (Semantik 2012), vol. 2012, no. Semantik, pp. 52–62, 2018.
R. Fauzan, Y. Indrasari, and N. Muthia, “Sistem Pendukung Keputusan Penerimaan Beasiswa Bidik Misi di POLIBAN dengan Metode Fuzzy Tsukamoto Berbasis Web,” J. Online Inform., vol. 2, no. 2, p. 79, 2018.
R. System, “JURNAL RESTI Implementasi E - Modul pada Program Studi Manajemen Informatika,” vol. 2, no. 2, pp. 492–497, 2018.
Y. Radhitya, F. Nur Hakim, and A. Solechan, “Rancang Bangun Sistem Pendukung Keputusan Penentuan Penyakit Dalam Dengan Metode Dempster Shafer,” J. Speed - Sentra Penelit. Eng. dan Edukasi, vol. 8, no. 3, pp. 7–12, 2017.
Y. Ronald R., "Classic Works of the Dempster-Shafer Theory of Belief Functions (Studies in Fuzziness and Soft Computing", Springer, 2008.
Y. Utama, “Sistem Pendukung Keputusan Untuk Menentukan Prioritas Penanganan Perbaikan Jalan Menggunakan Metode Fuzzy Tsukamoto, 2013.
DOI: https://doi.org/10.32736/sisfokom.v11i3.1425
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