Judul: Optimisasi Rute Traveling Salesman Problem Menggunakan Algoritme Bee Colony Optimization
Abstrak: Traveling Salesman Problem (TSP) merupakan masalah penentuan rute guna mengunjungi sekumpulan kota/tempat yang sepenuhnya terhubung dimana setiap koneksi antar dua kota dikaitkan dengan jarak atau biaya. Ada beberapa metode yang digunakan untuk penyelesaian masalah ini. Pada karya ilmiah ini, digunakan metode eksak Integer Linear Programming (ILP) dan metode meta-heuristic Bee Colony Optimization (BCO) untuk menyelesaikan TSP. Metode eksak ILP diselesaikan dengan bantuan perangkat lunak optimisasi LINGO 18.0, sedangkan metode BCO diselesaikan dengan bantuan bahasa pemrograman Python 3.6.9. Hasil yang diperoleh menunjukan bahwa waktu eksekusi metode BCO lebih cepat dibandingkan metode eksak namun, metode BCO menghasilkan selisih jarak yang relatif besar dibandingkan metode eksak., Traveling salesman problem (TSP) is a problem of determining a route to visit a group of fully connected cities/places where each connection between two cities is related to distance or cost. There are several methods to solve this problem. In this manuscript, integer linear programming (ILP) as an exact method and bee colony optimization (BCO) as a meta-heuristic method will be used to solve TSP. The exact ILP method is solved by LINGO 18.0 optimization software, while the BCO method is solved by Python 3.6.9 programming language. The results obtained show that the BCO execution time is faster than the exact method, but the BCO method produces a relatively large distance difference compared to the exact method.
Keyword: bee colony optimization, integer linear programming, meta-heuristic method, traveling salesman problem

Judul: Penentuan Rute Traveling Salesman Problem Menggunakan Algoritme Ant Colony Optimization
Abstrak: Traveling Salesman Problem (TSP) merupakan salah satu permasalahan yang sering muncul dalam sistem distribusi. Seiring berjalannya waktu, pemecahan masalah TSP berkembang dengan begitu cepat. Para ilmuwan berusaha mencari cara agar dapat menemukan hasil yang semakin baik dengan waktu eksekusi yang semakin cepat. Ada beberapa metode yang dikembangkan untuk permasalahan ini. Pada karya ilmiah ini, digunakan metode eksak Integer Linear Programming (ILP) dan metode meta-heuristic Ant Colony Optimization (ACO) untuk menyelesaikan TSP. Hasil yang diperoleh menunjukkan bahwa waktu eksekusi metode ACO jauh lebih cepat dibandingkan dengan metode eksak. Akan tetapi, ACO masih menghasilkan selisih jarak yang relatif besar dibandingkan ILP.
Keyword: ant colony optimization, integer linear programming, metode meta-heuristic, traveling salesman problem

Judul: Profil Antibodi IgM dan IgG pada Beruk (Macaca nemestrina) setelah Diinfeksi Virus Dengue Serotipe-3 (DEN-3) melalui Rute Intravena
Abstrak: The aim of this study was to detect IgM and IgG in pig-tailed macaques (Macaca nemestrina) primarily innoculated by Dengue virus serotype-3 (DEN-3) by intravenous route. A total of 84 plasma samples were examined in the study. Plasma samples were taken on day 0 before infection, followed by plasma collections on day 1 through day 13 post infection. The obtained plasma samples were analyzed using indirect ELISA test. The results showed the increasing titer of IgM started on day-3 post infection with its peak occurred on day 11 post infection and started to decline afterward; while the IgG titer started to increase on day 6 or day 7 post infection and continue to increase until the day 13 post infection. These results showed that in a primary infection of DEN-3 byintravenous route, the tendency of IgM titer increase was higher than the IgG titer increase; also shown that the IgM titer increase was occured earlier than IgG. The profile of IgM and IgG antibodies is outlined in this study.
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