Calor (Calf Detector)


  • Kadek Ayu Darmini SMA Negeri Bali Mandara
  • Kadek Adi Hendrawan SMA Negeri Bali Mandara
  • Komang Indah Juliani SMA Negeri Bali Mandara
  • Kadek Yuli Artama S.T., M.Pd. SMA Negeri Bali Mandara

Kata Kunci:

Dystocia and Death in Cattle, NodeMCU, IMU Sensor, IoT System


As an agricultural country, the livestock sector plays an important role in fulfilling food commodities and is a source of the economy of the population in Indonesia. The presence of dystocia in cows and the feeding of calves by dogs and other animals are both detrimental to the farmer if the livestock dies during the birth process and is based on the lack of direct supervision from the breeder during the birth process. The birth of calves in cows is mostly unknown when the birth takes place and this is what causes the problem of death in cowbirths to occur either because of dystocia or being preyed upon by other animals after the birth of the cow. In order for the community to know this, preventive measures are needed as an early stage to prevent the failure of the calving processin cows. Therefore, researchers offer Calor (Calf Detector) as a tool to provide information about the right time to give birth for cows based on microcontroller technology, especially NodeMCU. The objectives of this research are (1) to describe the working mechanism of Calor in predicting the birth of calves and (2) to determine the technical feasibility of Calor's simple technology. owned by the nominal and ordinal scale with the addition of other characteristics in the form of a fixed interval. The results of this study are as follows: 1) The working mechanism of the tool uses an IMU sensor and a pH sensor as input. NodeMCU as procces and LCD and short message as output. 2) Calor has technical feasibility that is able to provide benefits to the community. Based on the exposure, it can be concluded that the products offered by researchers can be used as smart technology in knowing the right time in the process of giving birth to cows so as to minimize prediction errors and handling errors.