| Autor: |
Tresna Maulana Fahrudin, Agustinus Bimo Gumelar, Febri Dwi Cahaya Putra, Jauhara Rana Budiani, Rizky Davit Nugroho, Wahyu Putra Adi Setiawan, Randy Anwar Romadhonny |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
2019 International Seminar on Application for Technology of Information and Communication (iSemantic). |
| Popis: |
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%. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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