PERAN INSEMINASI BUATAN (IB) TERHADAP PENINGKATAN POPULASI TERNAK SAPI DI KECAMATAN IV NAGARI KABUPATEN SIJUNJUNG: THE ROLE OF ARTIFICIAL INSEMINATION (AI) IN THE INCREASE OF CATTLE POPULATION IN IV NAGARI DISTRICT SIJUNJUNG REGENCY

Abdi Alva Arezhi; Rini Alisia; Maiyontoni Maiyontoni; Refika Komala; Fadilla Meidita

doi:10.36596/tas.v7i1.1816

Authors

Abdi Alva Arezhi Program Studi Peternakan, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia
Rini Alisia Program Studi Peternakan, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia
Maiyontoni Maiyontoni Program Studi Peternakan, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia
Refika Komala Program Studi Peternakan, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia
Fadilla Meidita Program Studi Peternakan, Jurusan Teknologi Produksi Peternakan, Politeknik Pertanian Negeri Payakumbuh, Indonesia

DOI:

https://doi.org/10.36596/tas.v7i1.1816

Keywords:

Artificial Insemination, NonReturnRate, Service per Conception, Conception Rate

Abstract

The increasing demand for animal protein from beef has not been matched by a proportional rise in cattle populations in Indonesia, necessitating strategies such as artificial insemination (AI) to accelerate reproduction. This study aimed to evaluate the success of AI programs in increasing cattle populations in IV Nagari District, Sijunjung Regency, by analyzing Non-Return Rate (NRR), Service per Conception (S/C), and Conception Rate (CR). A survey method was employed using primary data (farmer interviews) and secondary data (Puskeswan medical records from 2019–2023). The results showed NRR ranged from 69.80% to 77.91%, indicating a high pregnancy rate after the first AI, S/C for Bali and Ongole cattle averaged 1.13–1.30, reflecting efficient AI implementation, and CR reached 77.7%, exceeding the national standard (60–70%). In conclusion, the AI program in IV Nagari District successfully increased cattle populations, as evidenced by optimal NRR, S/C, and CR values. This success was influenced by inseminator training, farmer awareness, and AI infrastructure support.