Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal Multitek Indonesia : Jurnal Ilmiah
Sri Lestari
UPTD Puskeswan Purwantoro Wonogiri
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analisa Berat Bersih Daging Serta Ciri-Ciri Sapi Normal dan Glongongan Menggunakan Sistem Pakar dengan Metode Case Based Reasoning (CBR) Berbasis Android Lukman Effendi; Deden Mauli Darajat; Sri Lestari
MULTITEK INDONESIA Vol 12, No 2 (2018): Desember
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (593.298 KB) | DOI: 10.24269/mtkind.v12i2.1219

Abstract

Meat needs, especially beef, are increasingly increasing, because human awareness of the importance of nutritional needs derived from animal meat. The high demand for beef needs has resulted in farmers and cattle traders trying to sell as many animals as possible. Farmers and cattle traders in Indonesia are still largely unprofessional. For the sake of getting a lot of profit, it was time to takeaction that harmed cattle and consumers. One such action is to sell “glonggongan” meat which is to increase the mass / weight of beef by giving excessive drinking water before the cow is cut. One way to overcome this action is to provide information to buyers through a net weight analysis system for normal beef and glonggings using an expert system with case-based reasoning. The research will be carried out starting from the collection of data from normal and glaucous cows by looking at the body  weight, gender, upper-lower cows circumference of the abdomen, side of the cow's overall body  circumference, height, leg height, head length, butt width, body length cow. In obtaining output with a 95% truth value, the base of the case stored in the database is at least 150 cases. All input variables will be analyzed and matched on a case basis using an expert system with CBR (case-based reasoning) method
Co-Authors Deden Mauli Darajat Lukman Effendi