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Perilaku permasalahan aktual tidak selamanya menunjukkan pola solusi yang linier sehingga model-model non linier menjadi alternatif solusi yang layak dipertimbangkan. Penelitian ini mengkaji keandalan enam metode multidimensional search yaitu Rosenbrock with discrete steps, Levenberg Marquardt, Steepest Descent, Davidon-Fletcher-Powell, Gradien Konjugasi Fletcher dan Reeves, serta Zangwill. Perbandingan ini didasari pada kualitas hasil yang ditunjukkan oleh masing-masing metode dalam hal waktu komputasi dan nilai solusi optimalnya. Hasil penelitian menyajikan bahwa nilai solusi optimal yang dihasilkan setiap metode adalah signifikan tidak berbeda satu sama lain. Perbedaan lebih ditunjukkan oleh keragaman waktu komputasi akibat jumlah iterasi yang berbeda dari setiap metode. Kata Kunci: keandalan solusi, metode multidimensional search, waktu komputasi, solusi optimal Non linear models become a feasible solution alternative that being considered since the actual problem behavior is not always be showed as a linear solution pattern. This research is arranged to investigate reliability of the six methods of multidimensional search such as Rosenbrock with discrete steps, Levenberg Marquardt, Steepest Descent, Davidon-Fletcher-Powell, Gradien Konjugasi Fletcher and Reeves, and Zangwill based on their computation times and optimal solution values. The research’s results provide the common solutions significantly between methods. In contrast, the difference emerge in computation times caused by diversity of method’s iteration. Keywords: solution reliability, multidimensional search, computation time, optimal solution

ANALISIS KEANDALAN SOLUSI METODE MULTIDIMENSIONAL SEARCH UNTUK MODEL-MODEL OPTIMASI NON LINIER