Pengembangan produk baru merupakan hal yang sangat penting dalam menjagapertumbuhan perusahaan. Herbisida glyphosate dengan kemampuannya yangspesifik dan efektif dalam menghambat enzim 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) menjadi herbisida yang luas dipakai di seluruh duniatermasuk di Indonesia yaitu sebesar 51% pasar pada Maret 2013. Prosespembuatan produk baru ammonium glyphosate 400 g/L SL dilakukan melalui duametode optimasi yaitu Response Surface Method (RSM) dan Artificial NeuralNetwork-Genetic Algorithm (ANN-GA). Kemampuan prediksi respon RSM danANN dibandingkan melalui nilai root mean squared error (RMSE). Dari hasilprediksi RSM, RMSE untuk pembuatan ammonium glyphosate berbasa NH4OHdan berbasa NH4HCO3 secara berturut-turut adalah 44.37 dan 73.2. Sedangkandengan prediksi ANN RMSE untuk pembuatan ammonium glyphosate berbasaNH4OH dan berbasa NH4HCO3 secara berturut-turut adalah 122.04 dan 143.80.Pada penelitian ini juga ditunjukkan bahwa RSM memiliki kemampuan lebihbaik dalam menentukan kondisi optimal jika dibandingkan dengan ANN-GA.Berdasarkan hasil optimasi, formulasi ammonium glyphosate berbasa NH4OHdapat menurunkan biaya sebesar 3.71% dan dengan berbasa NH4HCO3 dapatmenurunkan biaya 11.08% dari komposisi yang sudah ada.

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New product development is very important for the companies to maintain the

growth. Since its specificity and affectivity in inhibits 5-enolpyruvylshikimate-3-

phosphate synthase (EPSPS), glyphosate becomes a worldwide herbicide

including in Indonesia with 51% market size in March 2013. The making of the

proposed new product, ammonium glyphosate 400 SL, is optimized by the two

methodologies Response Surface Method (RSM) and hybrid of Artificial Neural

Network-Genetic Algorithm (ANN-GA). Prediction capability of the RSM and

ANN model were determined by comparing the root mean squared error (RMSE).

From the RSM prediction, the RMSE for the NH4OH and NH4HCO3 experiment

were 44.37 and 73.2, respectively. And from the ANN prediction, the RMSE for

the NH4OH and NH4HCO3 experiment were 122.04 and 143.80, respectively. In

this study, RSM also showed its superiority in determine the optimum condition

for making ammonium glyphosate compared to the ANN-GA. Based on the

optimization result, NH4OH base formulation gave the 3.71% cost saving and

NH4HCO3 base formulation gave 11.08% cost saving compared to the existing

product.