The agriculture extension program can be developed effectively and efficiently by professional personal in agriculture extension field. The existing main problem is low quality and quantity of agri-extension workers (include in Kampar district, Riau province). Therefore, the goals of this research are: (1) To analyze: farmer characteristics; social system characteistics; agri-extension worker competencies; agri-extension worker performance to empower farmer and level of fulfill need for farmer’s capacity development in agribusiness; (2) To analyze determinant factors which influenze agri-extension worker performance to empowering farmer and (3) To formulate strategy to increase agri-extension worker performance to empower farmer. Through multistage cluster sampling technique, this research have found farmers sample with 180 person amoun (each of them consist of: 60 food crops farmers, 60 oil palm farmers and 60 rubber farmers). This research have been done from June 2007 up to October 2007. The analysis of data done by descriptive analysis and Path analysis. The research conclusion are: performance level of agri-extension worker to empower farmer still not yet good (“enough” category) because of the influence factor to the performance of agri-extension worker: agri-extension worker competencies (communication competency; competency in farmers learning and competency in social interaction); farmer characteristics ( farmer’s access to the non formal education) and social sistem support (soscio-cultural values; agribusiness facilitation by government institution and fartmer’s access to the aggribusiness institution) are still not yet (“enough” category).
The research aimed to identify carcass characteristic that can be used for estimating composition of beef carcass. It was used 165 Brahman crossbred cattle in this research. Carcass characteristics were weight of a half cold carcass (WC) ranged from 96 to 151 kg, loin eye area (LEA) ranged from 22.09 to 304.8 mm
Regression with L 1 regularization (lasso) method was compared to principal component regression (PCR) in Statistical Downscaling (SDS) modeling to predict monthly rainfall. SDS modeling uses ill-conditioned (high correlation/multicolliniear) covariates, which can be solved with selection or shrinkage methods. In this study, we used two GCMs with different characteristics as covariates (CMIP5 and GPCP version 2.2). The results shows that the lasso method gave better results (smaller RMSE and RMSEP) than PCR for GPCP version 2.2, and as good as PCR for CMIP5 covariates.
ABSTRAKCatatan bobot badan 1221 sapi yang digunakan dalam penelitian ini dikumpulkan dari PT Taurus Dairy Farm Sukabumi dari tahun 2001 sampai 2011. Catatan yang dapat digunakan untuk analisis adalah 373 dari 1221 sapi, yang mempunyai data dari lahir sampai masa kawin pertama. Tiga model yang berbeda yaitu, Logistic, Gompertz, dan von Bertalanffy dilakukan untuk menganalisis laju pertumbuhan sapi. Hasil penelitian menunjukkan bahwa tiga model memiliki akurasi yang berbeda dan sangat tergantung pada umur, lingkungan dan lamanya pengamatan. Makin lama pengamatan ternyata bobot dewasa (A) makin besar, demikian juga dengan umur dan bobot pubertas. Model Gompertz merupakan model yang paling mudah dalam proses penghitungan, sedangkan model Logistic merupakan model yang lebih sulit. Semua model menunjukkan akurasi yang tinggi dengan koefisien determinasi (R 2 ) lebih dari 90%. Model Gompertz dan Logistic dapat direkomendasikan untuk memprediksi kecepatan atau laju pertumbuhan saat pubertas Kata kunci: kurva pertumbuhan, koefisien determinasi, dara, sapi perah, FH
ABSTRACTThe body weight records of 1221 heifers were used in this study collected from PT Taurus Dairy Farm Sukabumi from year 2001 until 2011. The records that could be used for analysis were 373 out of 1221 heifers, having completed data from birth to first mating period. Three different models i.e, Logistic, Gompertz, and von Bertalanffy were performed to analyze the growth rate of heifers. The results showed that the three models had different accuracy and heavily depend on age, environment and duration of recording. The body weights of sexual maturity and on certain ages were affected by the duration of recording. The Gompertz model was performed as the simpliest model in form of calculation. On the other hand, the Logistic was more difficult to calculate. All models indicated high accuracy with the determination coefficient (R 2 ) more than 90%. Based on the comparison, the Gompertz and Logistic model are recommended for predicting the growth rate of heifers from birth to sexual maturity.
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