Aplikasi Sistem Pakar Diagnosa Penyakit Anjing Berbasis Facebook Messenger
Abstract
Abstract—An Expert System of Disease Diagnosis in Dogs Based on Facebook Messenger was a useful application to provide an initial diagnosis of the diseases based on the symptoms given by the users. The application uses the Facebook Messenger-based on Natural Language Processing (NLP) method to allow users to easily and comfortably interacting with the app. Diagnosis was obtained by identifying the pattern, and classifying the pattern. The method used in the pattern identification process is N-gram, this method was a matching pattern method where the number of words or character pattern that would be match could be adjusted. The method used to classify a disease is a Matching Template, this method worked by matching the template pattern with the test pattern to find the similarities between the patterns. The study concluded that the application of an expert systems using the N-gram method and the Matching Template had an accurate diagnosis rate of 80%.
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References
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[3] C. Amiot, B. Bastian and P. Martens, “People and Companion Animals: It Takes Two to Tango,” BioScience, vol. 66, no. 7, 2016.
[4] Y. L. X. G. S. G. Tailai Wu, “A Study of Active Usage of Mobile Instant Messaging Application: An attachment theory perspective,” Information Development, vol. 33, no. 2, 2016.
[5] A. P. J. I. Indonesia, “Penetrasi & Profil Pengguna Internet Indonesia 2018,” Asosiasi Penyelenggara Jasa Internet Indonesia, Indonesia, 2018.
[6] M. A. Ali, “Artificial intelligence and natural language processing: the Arabic corpora in online translation software,” International Journal of Advanced and Applied Sciences, vol. 3, no. 9, 2016.
[7] B. Zaman, E. Hariyanti and E. Purwanti, “Sistem Deteksi Bahasa pada Dokumen menggunakan N-Gram,” Jurnal Multinetics, vol. 1, no. 2, 2015.
[8] I. F. Katili and F. D. Esabella, “Pattern Recognition Of Javanese Letter Using Template Matching Correlation Method,” Journal of Applied Intelligent System, vol. 3, no. 2, 2018.
[9] A. Wrzalik and B. Jereb, “ Use Of Expert Systems In Crisis Management,” Czoto, vol. 1, no. 1, 2019.
[10] A. M. Karim, F. V. Çelebi and A. S. Mohammed, “Software Development for Blood Disease Expert System,” Lecture Notes on Software Engineering, vol. 4, no. 3, 2016.
[11] D. Agustina, H. Mustafidah and M. R. Purbowati, “Sistem Pakar Diagnosa Penyakit Kulit Akibat Infeksi Jamur,” JUITA, vol. 4, no. 2, 2016.
[12] S. R. Joseph, H. Hlomani and K. Letsholo, “Natural Language Processing: A Review,” International Journal of Research in Engineering and Applied Sciences, vol. 6, no. 3, 2016.
[13] B. Zaman, E. Hariyanti and E. Purwanti, “Sistem Deteksi Bahasa pada Dokumen menggunakan N-Gram,” JURNAL MULTINETICS, vol. 1, no. 2, 2015.
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[18] N. G. Yudiarta, M. Sudarma and W. G. Ariastina, “Penerapan Metode Clustering Text Mining Untuk Pengelompokan Berita Pada Unstructured Textual Data,” Majalah Ilmiah Teknologi Elektro, vol. 17, no. 3, 2018.
[19] M. S. N. P. Dewa Ayu Putri Wulandari, “Pemanfaatan Big Data Media Sosial Dalam Menganalisa Kemenangan Pilkada,” Majalah Ilmiah Teknologi Elektro, vol. 18, no. 1, 2019.
[20] I. Pujadayanti, M. A. Fauzi and Y. A. Sari, “Prediksi Rating Otomatis pada Ulasan Produk Kecantikan dengan Metode Naïve Bayes dan N-gram,” Jurnal Telematika, vol. 2, no. 11, 2018.
[21] Badrinaathan.J and L.N.B.Srinivas, “Angle and Scale Invariant Template Matching for Handling Image Distortions,” International Journal of Engineering & Technology, vol. 7, no. 2, 2018.
[22] I. M. O. Widyantara, A. T. A. P. Kusuma and N. M. A. E. D. Wirastuti, “Preprocessing pada Segmentasi Citra Paru-Paru dan Jantung Menggunakan Anisotropic Diffusion Filter,” Majalah Ilmiah Teknologi Elektro, vol. 14, no. 2, 2015.
[23] K. O. Oseni, K. Dingley and P. Hart, “Instant Messaging and Social Networks — The Advantages in Online Research Methodology,” International Journal of Information and Education Technology, vol. 8, no. 1, 2018.
[24] A. Yudhana, b. Riadi and c. Anshori, “Identification of Digital Evidence Facebook Messenger on Mobile Phone With National Institute of Standards Technology (NIST) Method,” Jurnal Ilmiah KURSOR, vol. 9, no. 3, 2018.
[25] P. S. M. Suryani, L. Linawati and K. O. Saputra, “Penggunaan Metode Naïve Bayes Classifier pada Analisis Sentimen Facebook Berbahasa Indonesia,” Majalah Ilmiah Teknologi Elektro, vol. 18, no. 1, 2019.
[26] A. V. M. Association, “Disease Risks for Dogs in Social Settings,” 29 Oktober 2019. [Online]. Available: https://www.avma.org/public/PetCare/Pages/Disease-Risks-for-Dogs.aspx.
Published
2020-10-18
How to Cite
FLORES, Veronica Ambassador; LINAWATI, Linawati.
Aplikasi Sistem Pakar Diagnosa Penyakit Anjing Berbasis Facebook Messenger.
Majalah Ilmiah Teknologi Elektro, [S.l.], v. 19, n. 1, p. 113-120, oct. 2020.
ISSN 2503-2372.
Available at: <https://ojs.unud.ac.id/index.php/mite/article/view/55818>. Date accessed: 19 nov. 2024.
doi: https://doi.org/10.24843/MITE.2020.v19i01.P17.
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License
