A Design of Optimization of Goat Sales Based on The Website

Authors

  • Taufik Indra P. Taufik POLITEKNIK NEGERI MALANG
  • Lis Diana Mustafa State Polytechnic of Malang
  • Waluyo Waluyo State Polytechnic of Malang

DOI:

https://doi.org/10.33795/jartel.v13i2.542

Keywords:

Goat care, Feed optimization, Goats, RFID, E-COMMERCE.

Abstract

Currently, goat farming is one of the fastest growing businesses. Developments that occur include buying and selling that can be done through e-commerce available on digital media. E-commerce can increase sales from goat breeders through complete descriptions and goat productivity. Based on the description above, it is necessary tools and systems that can help increase the productivity of goat farmers. The method used is to carry out the process of weighing goats using loadcell, measuring goat body temperatures using MLX614 temperature sensors, and RFID sensors used to detect goat ID, goat type, and weighing time. In addition, it also uses Arduino as a microcontroller and raspberry pi as a server. There are sensor nodes and server nodes where data will be sent from the arduino uno sensor server node raspberry pi 3RF24L01. Communication technique is client server designed for communication between the client node and the server so that error the data transmission smaller. The results of testing tools and systems include testing the accuracy of sensors having several sensor values ??such as RFID, Loadcell and temperature sensors MLX90614 with several points, namely for RFID itself it is concluded that the success rate is read 100%, for the accuracy level of the loadcell sensor with a comparison of some of the scales carried out 10, the average error was 0.77% and the testing accuracy of the MLX90614 temperature sensor with a thermogun comparison, the average error value before calibration was 7.565%, while after calibration, the average error value was 0.507%.

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Published

2023-06-30

How to Cite

[1]
T. I. P. Taufik, L. D. Mustafa, and W. Waluyo, “A Design of Optimization of Goat Sales Based on The Website”, Jartel, vol. 13, no. 2, pp. 185-189, Jun. 2023.