Please use this identifier to cite or link to this item: https://repositori.uma.ac.id/handle/123456789/24847
Title: Rancang Bangun Sistem untuk Mengidentifikasi Jenis Burung Accipiter Menggunakan Algoritma Naive Bayes
Other Titles: System Design for Identifying Accipiter Bird Types Using the Naive Bayes Algorithm
Authors: Wellsa, Sigit Winaya
metadata.dc.contributor.advisor: Susilawati
Keywords: accipiter;identifikasi;algoritma;naïve bayes;falconry;identification;algorithm
Issue Date: 1-Apr-2024
Publisher: Universitas Medan Area
Series/Report no.: NPM;178160059
Abstract: Burung Accipiter atau biasa dikenal dengan sebutan Elang alap merupakan burung pemangsa. Burung jenis accipiter sering dipelihara oleh orang-orang yang memiliki hobi memelihara burung pemangsa, pegiat Falconry,balai konservasi serta kebun binatang. Namun banyak pemilik burung tidak mengetahui secara pasti jenis burung yang dipelihara karena jenis accipiter memiliki beberapa ciri-ciri yang cenderung mirip, sehingga sulit membedakannya secara kasat mata. Kesulitan untuk mengetahui perbedaan jenis burung accipiter ini karena banyaknya jenis burung accipiter yaitu kurang lebih 47 jenis burung accipiter yang tersebar diseluruh dunia ditambah masih sangat sedikitnya para ahli dan pakar yang mengetahui secara pasti jenis jenis dari accipiter secara akurat. Oleh karena itu dibutuhkan sebuah sistem yang bertujuan untuk mengidentifikasi jenis burung accipiter berdasarkan ciri-cirinya dalam melakukan proses identifikasi terhadap accipiter yang belum diketahui jenisnya secara akurat. Proses klasifikasi dalam penelitian ini dilakukan dengan menerapkan metode Naïve Bayes. Hasil penerapan algoritma Naïve Bayes dalam proses klasifikasi accipiter memiliki rata-rata tingkat akurasi yang sangat tinggi jika dibandingkan dengan data aktual yaitu mencapai 97,06%. Tingkat akurasi tersebut diuji dengan 500 data dan menghasilkan klasifikasi Jenis Badius (Shikra hawk) 94,49%, Jenis Gularis (Japanese sparrowhawk) 97,14%, Jenis Virgatus (Besra) 97,71% dan Jenis Fasciatus (Brown goshawk) 98,91%. The Accipiter bird or commonly known as the peregrine falcon is a bird of prey. Accipiter birds are often kept by people who have a hobby of keeping birds of prey, falconry activists, conservation centers and zoos. However, many bird owners do not know exactly what type of bird they are keeping because the accipiter type has several characteristics that tend to be similar, making it difficult to differentiate them with the naked eye. The difficulty in knowing the different types of accipiter birds is because there are many types of accipiter birds, namely approximately 47 types of accipiter birds spread throughout the world plus there are still very few experts and experts who know for sure the types of accipiter accurately. Therefore, a system is needed that aims to identify the type of accipiter bird based on its characteristics in carrying out the identification process for accipiter whose type is not yet known accurately. The classification process in this research was carried out by applying the Naïve Bayes method. The results of applying the Naïve Bayes algorithm in the accipiter classification process have a very high average level of accuracy when compared with actual data, reaching 97.06%. This level of accuracy was tested with 500 data and resulted in a classification of Badius Type (Shikra hawk) 94.49%, Gularis Type (Japanese sparrowhawk) 97.14%, Virgatus Type (Besra) 97.71% and Fasciatus (Brown goshawk) 98%. 91%.
Description: 132 Halaman
URI: https://repositori.uma.ac.id/handle/123456789/24847
Appears in Collections:SP - Informatic Engineering

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