<![CDATA[ Pada makalah ini, kami meneliti mengenai optimisasi robust (robust optimization), metode ini berguna untuk menangani masalah optimisasi dimana data permasalahan tidak diketahui dengan pasti tetapi diasumsikan berada dalam suatu himpunan ketidakpastian (uncertainty set). Selanjutnya Second Order Cone Programming (SOCP) digunakan untuk menyelesaikan masalah optimisasi robust. SOCP adalah masalah pemrograman konveks dimana fungsi tujuannya berbentuk linear dengan kendala second order cone. Penerapan SOCP pada pembentukan masalah portofolio mean variance berhasil dilakukan. Berdasarkan studi kasus, portofolio robust melalui SOCP lebih unggul dibandingkan portofolio klasik ditinjau dari capital gain. Kata Kunci : Optimisasi robust, Second order cone programming, Portofolio mean-variance. Robust Optimization Through Second Order Cone Programming with Applications on the Establishment of Optimal Portfolio Abstract In this paper, we studied about robust optimization, this method is useful for dealing with optimization problems where data are not known certainly but assumed belong to uncertainty set. Furthermore, Second Order Cone Programming (SOCP) is used to solve the robust optimization problems. SOCP is a convex programming problem where the objective function in the form of linear with constraints in the form of second order cone. Application of SOCP in the formation of mean variance portfolio problem successfully conducted. Based on case studies, robust portfolios through SOCP are superior compared to classical portfolios in terms of capital gain. Keywords: Robust optimization, Second order cone programming, Mean variance portfolio. ]]>
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