Background: Human face is a biometric feature. Artificial Intelligence (AI) called Artificial Neural Network (ANN) can be used in recognising such a biometric feature. In ANN, the learning process is divided into two: supervised and unsupervised learning. In supervised learning, a common method used is Backpropagation, while in the unsupervised learning, a common one is Kohonen Self Organizing Map (KSOM). However, the application of Backpropagation and KSOM need to be adjusted to improve the performance.Objective: In this study, Backpropagation and KSOM algorithms are rewritten to suit face image recognition, applied and compared to determine the effectiveness of each algorithm in solving face image recognition.Methods: In this study, the methods used and compared in the case of face image recognition are Backpropagation dan Kohonen Self Organizing Map (KSOM) Artificial Neural Network (ANN).Results: The smallest False Acceptance Rate (FAR) value of Backpropagation is 28%, and KSOM is 36%, out of 50 unregistered face images tested. While the smallest False Rejection Rate (FRR) value of Backpropagation is 22%, and KSOM is 30%, out of 50 registered face images. The fastest time for the training process using the backpropagation method is 7.14 seconds, and the fastest time for recognition is 0.71 seconds. While the fastest time for the training process using the KSOM method is 5.35 seconds, and the fastest time for recognition is 0.50 seconds.Conclusion: Backpropagation method is better in recognising face images than KSOM method, but the training process and the recognition process by KSOM method are faster than Backpropagation method due to the hidden layers. Keywords: Artificial Neural Network (ANN), Backpropagation, Kohonen Self Organizing Map (KSOM), Supervised learning, Unsupervised learning

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Radar Altimeter digunakan untuk mengukur jarak dari pesawat ke permukaan tanah atau permukaan laut yang bekerja pada frekuensi 4,2-4,3 GHz. Antena microstrip sebagai antena alternatif terdiri dari tambalan dan pesawat darat dengan Tembaga dan substrat menggunakan FR-4. Antena microstrip melingkar array 2x2 terdiri dari empat elemen antena melingkar tunggal yang dikombinasikan dengan teknik Wilkinson Power Divider. Optimalisasi array antena melingkar microstrip 2x2 pada 4,3 GHz sesuai dengan frekuensi operasi radar altimeter dengan kehilangan kembali -12,41 dB dalam rentang frekuensi 4,22 GHz hingga 4,36 GHz, bandwidth 144,1 MHz, VSWR 1,6, menghasilkan keuntungan 6.9 dB, serta menghasilkan pola radiasi lobus utama 7,34 dBi ke arah 20,0 deg dan beamwidth 26,3 deg. Hasil optimasi dibandingkan dengan antena microstrip melingkar tunggal, yang memiliki kehilangan pengembalian -16,19 dB dalam rentang frekuensi 4,27 GHz - 4,31 GHz, bandwidth antena ini adalah 48,4 MHz, VSWR 1,3, menciptakan keuntungan 4,3 dB, serta menghasilkan pola radiasi lobus utama 2,76 dBi ke arah 47,0 deg dan beamwidth 49,1 deg