AI Smart Contract: Point Conversion Platform For The Merdeka Belajar – Kampus Merdeka Program Based On Artificial Intelligence

The Merdeka Belajar – Kampus Merdeka (MBKM) policy issued by the Ministry of Education and Culture opens up great opportunities for universities to create graduates who are competent and competitive. The MBKM program gives students the right to take part in learning outside the department or university with the equivalent or conversion of credits. However, the Director General of the Ministry of Education and Culture, Research, Technology and Higher Education, highlighted that there are still many universities that have not provided proper grade conversion rights to students (Kemendikbud, 2022). The Kastrat BEM FMIPA UNEJ team found that 93.7% of students who had taken MBKM were worried because they had to retake credits that had not been converted (Kastrat BEM FMIPA UNEJ, 2022). Through SWOT analysis, this research provides an idea solution in the form of an Artificial Intelligence-based Smart Contract as a value conversion platform for the MBKM program to make it easier for departments to convert student grades according to their needs and core competencies

Penggunaan Fungsi Heuristik Sederhana pada Permainan Tic-Tac-Toe

Tic-Tac-Toe merupakan salah satu permainan papan sederhana. Permainan ini dimainkan oleh dua pemain dengan cara mengisi kolom pada papan dengan bidak X atau bidak O sedemikian hingga terbentuk garis sejajar secara vertikal, horizontal dan diagonal. Dengan perkembangan bidang Artifial Intellingence (AI), berbagai algoritma telah diaplikasikan pada permainan ini. Persoalan utama pada penggunaan metode (algoritma) dalam permainan ini adalah pohon solusi yang dibangun secara exhaustive akan meningkatkan beban komputasi. Karena itu metode yang memanfaatkan fungsi heuristik banyak digunakan untuk menemukan solusi optimum lokal. Kendati demikian, penerapan metode-metode tersebut (seperti algoritma minimax dan algoritma genetika) juga relatif kompleks, karena perlu mengevaluasi keadaan berikutnya (next state), dan proses evaluasinya yang iteratif. Penelitian ini mencoba untuk memberikan cara pandang lain dalam menemukan solusi permainan tic-tac-toe berukuran 3 x 3. Dalam penelitian ini fungsi heuristik yang sederhana akan digunakan untuk mengevaluasi current state. Hasil penelitian menunjukkan bahwa metode ini dapat menemukan solusi optimum lokal seperti halnya metode-metode terdahulu. Pada tahap penelitian selanjutnya perlu dilakukan evaluasi keefektifan dan keefisienan metode ini dibandingkan dengan metode lainnya. Kata kunci: tic-tac-toe, fungsi heuristik

AI model for computer games based on case based reasoning and AI planning

Making efficient AI models for games with imperfect information can be a particular challenge. Considering the large number of possible moves and the incorporated uncertainties building game trees for these games becomes very difficult due to the exponential growth of the number of nodes at each level. This effort is focused on presenting a method of combined Case Based Reasoning (CBR) with AI Planning which drastically reduces the size of game trees. Instead of looking at all possible combinations we can focus only on the moves that lead us to specific strategies in effect discarding meaningless moves. These strategies are selected by finding similarities to cases in the CBR database. The strategies are formed by a set of desired goals. The AI planning is responsible for creating a plan to reach these goals. The plan is basically a set of moves that brings the player to this goal. By following these steps and not regarding the vast number of other possible moves the model develops Game Trees which grows slower so they can be built with more feature moves restricted by the same amount of memory