Sistem Pendukung Keputusan Diagnosis Penyakit Sapi Potong Menggunakan K-Nearest Neighbour (K-NN)

Penulis

Diva Kurnianingtyas, Brillian Aristyo Rahardian, Dyan Putri Mahardika, Amalia Kartika A., Dwi Angraeni K.

Abstrak

Abstrak

Industri peternakan merupakan salah satu industri yang penting dalam bidang penyediaan nutrisi makanan sehingga pertumbuhan produk ternak bisa menciptakan suatu ancaman kesehatan masyarakat dimana menyebabkan permasalahan kesehatan. Kurangnya pengetahuan peternak sapi potong mengenai berbagai penyakit yang menyerang serta solusi penanganan salah satu alasan  memanajemen kesehatan ternak dirasa cukup menyulitkan beberapa peternak. Pengembangan sistem pendukung keputusan yang menggunakan metode K-Nearest Neighbour (K-NN) sebagai metode inferensi untuk mendiagnosis penyakit ini. Data 11 jenis penyakit dapat dikenali oleh sistem pendukung keputusan dan 20 jenis gejala yang dapat dikenali oleh sistem. Hasil pengujian keakuratan 325 data latih dan 11 data uji telah menghasilkan tingkat akurasi 100% dengan nilai k = 3.

Kata kunci: penyakit sapi potong, sistem pendukung keputusan, K-Nearest Neighbour

 

Abstract

The livestock industry is one industry that is important in the provision of food nutrients so that the growth of livestock products could create a public health threat which causes health problems. Lack of beef cattle farmers knowledge about the various diseases that attack as well as the handling solutions is one reason s managing animal health are considered difficult for some farmers. The development of decision support systems using K-Nearest Neighbour (K-NN) as an inference method to diagnose this disease. Data 11 types of diseases can be recognized by decision support systems and 20 types of symptoms that can be recognized by the system. Results of testing the accuracy of 325 training data and test data 11 has yielded an accuracy rate of 100% with a value of k = 3.

Keywords: cattle cow disease, desicion support system, K-Nearest Neighbour

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Referensi


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DOI: http://dx.doi.org/10.25126/jtiik.201742308