ANALYSIS OF PIG PROFILES ON SMALL-SCALE PIG FARMERS IN MANOKWARI-WEST PAPUA

*D.A. Iyai -  Faculty of Animal Sciences Fisheries and Marine Sciences,The State University of Papua, Jl. Gunung Salju, Amban. Manokwari. Papua Barat 98314, Indonesia
B.W.I. Rahayu -  Faculty of Animal Sciences Fisheries and Marine Sciences,The State University of Papua, Jl. Gunung Salju, Amban. Manokwari. Papua Barat 98314, Indonesia
I. Sumpe -  Faculty of Animal Sciences Fisheries and Marine Sciences,The State University of Papua, Jl. Gunung Salju, Amban. Manokwari. Papua Barat 98314, Indonesia
D. Saragih -  Faculty of Animal Sciences Fisheries and Marine Sciences,The State University of Papua, Jl. Gunung Salju, Amban. Manokwari. Papua Barat 98314, Indonesia
Published: 15 Sep 2011.
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Language: EN
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Abstract
This study was aimed to determine the profiles of pig farming systems. Participatory situationanalysis was employed to gain data relating to pig profiles in the urban and rural areas of Manokwari.Due to the interests of combining many correlated data, multivariate analysis using Principal ComponentAnalysis (PCA) was performed. Cluster Analysis using Agglomerative Hierarchical Clustering wasapplied for analysis of merge samples based on similarity in components’ composition across sites.There were various twelve classes of pig profiles in Manokwari. In principal component of the first axiscorrelation of several components shows strong positive relation e.g. in piglets, sows, and total herd size.Status of region in the first axis of PCA (P1) through which pigs were raised had negative correlation,including grower, household member and pig production. In the second axis (P2), negative correlationswere shown in piglets, grower, boars, total herd size and the Pig Production Potential (PPP). Status ofregion has underpinned profiles of pigs. Several farmers were able to manage their farm continuity in asteady composition. Selling pigs was the main aim and few farmers play a role as pure breeder.
Keywords
agglomerative hierarchical clustering. pig profiles. principal component analysis. cluster analysis

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