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All Journal Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Riset Rumpun Ilmu Teknik (JURRITEK)
Sirajuddin Hawari
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Industrial & Manufacturing Engineering

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MINIMAX ALGORITHM BASED ON "MAIN INI YUK" GAME Sirajuddin Hawari; Muhammad Zulfikri Maulanab; Teuku Binzar Nawaf Musyaffa; Desy Komalasari; Mutiara Persada Pulungan
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2022): Maret : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v2i1.318

Abstract

In the game there are rules for each game. The rules are made as a challenge to achieve victory. To achieve victory requires analysis of the right algorithm in making decisions. Minimax is one of the best decision-making algorithms to be applied in a game. The time complexity of the minimax algorithm is O(b^m) which b is the branching and m is the depth.
MEMBANDINGAN METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION DAN LEARNING VECTOR QUANTIZATION DENGAN OPENCV PADA PENGENALAN WAJAH Muhammad Varriel Avenazh Nizar; Sirajuddin Hawari; Ahmad Nur Ihsan Purwanto
JURAL RISET RUMPUN ILMU TEKNIK Vol. 1 No. 1 (2022): April : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (903.499 KB) | DOI: 10.55606/jurritek.v1i1.593

Abstract

Face recognition is an area that is still being researched and improved for various purposes such as attendance, population data collection, security systems and others. Two methods that are often used for face recognition applications are artificial intelligence methods, especially back-propagation neural networks (ANN) and learning vector quantization. Both of these techniques are directed learning techniques that are widely used to identify distinctive patterns, namely grouping patterns into groups of patterns, making them ideal for use in facial recognition applications. In this application, preprocessing of the input image includes the detection process of scaling, grayscale, edged with the sobel and threshold methods, carried out before the image is processed in ANN. Meanwhile, the ANN approach used to identify faces involves the Backpropagation method and the Learning Vector Quantization method. The findings of this analysis are a comparison of the backpropagation neural network method and quantization of the learning vectors of face recognition used to assess variations, limitations, strengths and optimal results of the two techniques for use in facial recognition systems.
Co-Authors Ahmad Nur Ihsan Purwanto Desy Komalasari Muhammad Varriel Avenazh Nizar Muhammad Zulfikri Maulanab Mutiara Persada Pulungan Teuku Binzar Nawaf Musyaffa