<![CDATA[This study aimed to make estimation model of metabolizable energy (ME) of broiler chicken ration and feedstuffs based on proximate analysis and gross energy (GE). The estimation model used multiple and simple linear regression analysis with in vivo data approach. A total of 34 starter commercial ration data, 33 finisher commercial ration data, 17 experimental ration data, 14 corn data, 8 palm kernel cake (PKC) data from Center for Quality Testing and Feed Certification Laboratory and other research while the moisture content (MC), ash, crude protein (CP), ether extract (EE), crude fiber (CF), GE and ME were used as database and analyzed using SPSS version 20. The results showed that ME estimation using multiple regression equation for starter commercial ration ME = 2,444.89 + 201.34x(MC) - 415.85x(ash) - 0.87x(CP) + 282.58x(EE) 284.96x(CF), finisher commercial ration ME = 6,451.05 - 244.99x(MC) - 226.72x(ash) - 101.40x(EE) + 363.12x(CF), experimental ration ME = 3,001.07 + 41.39x(MC) - 19.49x(ash) - 12.82 x(CP) + 87.31x(EE) - 160.99x(CF), corn ME= 8,504.07- 301.32x(MC) + 196.41x(ash) -252.58x(CP) + 114.52x(EE) + 47.99x(CF) and PKC ME = 6,197.28 - 111.45x(CF) while linear equation for starter commercial ration ME= 3,821.79 - 0.15GE, finisher commercial ration ME = 12,266.23 - 2.19 (GE), research ration ME= 1,416.83 + 0.398x(GE), corn ME= -2,958.80 + 1.68x(GE), PKC ME = -5,769.41 + 2.09x(GE). These two models could be used to estimate ME content in commercial finisher ration, experimental ration, corn, and PKC whereas both models could not be used for commercial feed starter. Key words: chicken feed, corn, metabolizable energy, palm kernel cake, regression analysis]]>
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