Randy Anwar Romadhonny, Agustinus Bimo Gumelar, Tresna Maulana Fahrudin, Wahyu Putra Adi Setiawan, Febri Dwi Cahaya Putra, Rizky Davit Nugroho, Jauhara Rana Budiani
The development of the dairy cows cattle industry has management standards ranging from feed management, breeding, and milk production. Inbreeding of dairy cows, Artificial Insemination (AI) is carried out from selected stud semen so that dairy cows have more opportunity to calve female cows. Dairy cows have indication of lust regularly called as estrous cycle. Good handling of AI during the estrous period, will increase the percentage pregnancy of the cow. A balanced plan between stud semen stock with AI needs in the farm will help the management of dairy cows. This research uses a dataset of 1,790 dairy cows with the collection of training and testing data. The stored data will be processed using the Multiple Logistic Regression method to be calculated as a result of the prediction ahead of the estrous cycle. Data on dairy cows that meet the processing requirements will be categorized by themselves. Variables in the dataset used in prediction calculations are time-series data. The results showed that the two features of the independent variables χ1 and χ2 have constant-coefficient values (βO) = 0.7927, (β1) = 0.0156, (β2) = 0.0000926 with model accuracy> 80%. Independent variable multinomial calculations produce an accuracy of 83.2%. © 2019 IEEE.
Fakultas Ilmu Komputer, Universitas Narotama, Surabaya, Indonesia; Faculty of Medicine, Widya Mandala Catholic University, Surabaya, Indonesia; Fakultas Matematika Komputasi Dan Sains Data, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia