A. Saefuddin
Department of Statistics, Faculty of Sciences, Bogor Agricultural Universit, Darmaga Campus, Bogor 16680

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COMPARISON ON ACCURACY OF LOGISTIC, GOMPERTZ AND VON BERTALANFFY MODELS IN PREDICTING GROWTH OF NEW BORN CALF UNTIL FIRST MATING OF HOLSTEIN FRIESIAN HEIFERS Budimulyati S., L.; Noor, R.R.; Saefuddin, A.; Talib, C.
Journal of the Indonesian Tropical Animal Agriculture Vol 37, No 3 (2012): (September)
Publisher : Diponegoro University

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Abstract

The body weight records of 1221 heifers were used in this study collected from PT Taurus DairyFarm Sukabumi from year 2001 until 2011. The records that could be used for analysis were 373 out of1221 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. Theresults showed that the three models had different accuracy and heavily depend on age, environment andduration of recording. The body weights of sexual maturity and on certain ages were affected by theduration of recording. The Gompertz model was performed as the simpliest model in form ofcalculation. On the other hand, the Logistic was more difficult to calculate. All models indicated highaccuracy with the determination coefficient (R2) more than 90%. Based on the comparison, theGompertz and Logistic model are recommended for predicting the growth rate of heifers from birth tosexual maturity.
IDENTIFICATIONS OF CARCASS CHARACTERISTIC FOR ESTIMATING THE COMPOSITION OF BEEF CARCASS Hafid, H.; Gurnadi, R.E.; Priyanto, R.; Saefuddin, A.
Journal of the Indonesian Tropical Animal Agriculture Vol 35, No 1 (2010): (March)
Publisher : Diponegoro University

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Abstract

The research aimed to identify carcass characteristic that can be used for estimating composition ofbeef carcass. It was used 165 Brahman crossbred cattle in this research. Carcass characteristics wereweight of a half cold carcass (WC) ranged from 96 to 151 kg, loin eye area (LEA) ranged from 22.09 to304.8 mm2, 12th rib fat thickness (FT12) ranged from 0.80 to 2.90 mm, meat ranged from 53.55 to 90.10kg and carcass fat ranged from 5.54 to 39.72 kg. Result showed that a half weight cold carcass as asingle indicator major may be used to predict meat weight and carcass fat with regression linearequation: Meat (kg) = 10.64 + 0.49 WC (R2=0.728 and SE=3.58), and Fat (kg) = -21.70 + 0.36 WC**(R2=0.582 and SE=3.65). Multiple regression to predict meat weight based on fat percentage of kidney,pelvic and heart (KPH) was Meat (kg) = 7.99 + 0.58 WC** - 4.41 KPH** (R2=0.751 and SE=3.43).
Potential Ecology Suitability Distribution of Forage Availability for Dairy Cattle. Case study: Lembang District Area, West Java Al Zahra, W.; Saefuddin, A.; Abdullah, L.
Jurnal Ilmu Produksi dan Teknologi Hasil Peternakan Vol 3, No 1 (2015): Jurnal Ilmu Produksi dan Teknologi Hasil Peternakan
Publisher : Bogor Agricultural University

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Abstract

Dairy cattle have a highly depend on forage for its daily diet that will influence milk production. Therefore forage supply is the core issue in dairy farming productivity in Indonesia. Hence, it is very important in securing forage supply in order for sustainability of dairy farming. However, the forage availability is becoming rare due to the limitation of farming land owned by the farmers. The aim of this research was to determine geospatial distribution of forage availability for dairy cattle in Lembang Area, West Java. GIS software (ArcView 3.2) was used in this research. Secondary data, including maps (Land use, rainfall, slope, ect) were required in this research. As we know that the ecological suitability was the primary requirements for forage management. Moreover, the ecological suitability was assessed by criteria classification in order to achive optimum forage production. The result of map overlapping has resulted the potential ecology suitability for forage management. Furthermore, land suitability was physically divided into 4 classes; highly suitable (S1), moderate suitable (S2), marginally suitable (S3), not suitable (N) and constrain (C) that became the restriction point for forage management.Keywords : Dairy Cattle, Forage, Geographic Information System