HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.

• Main Author: Vantika, Sandy
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/69646
• Institution: Institut Teknologi Bandung

Hidden Markov Model (HMM) is applied to the case of mutation of human mitochondrial DNA. A total of 25 samples were taken at random from the 100 sequences of human mitochondrial DNA. From each sample, the emission matrices and the transition matrices were determined. Furthermore, the Viterbi algorit...