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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) International Journal of Advances in Intelligent Informatics
Sarni Suhaila Rahim
Universiti Teknikal Malaysia Melaka
Computer Science & IT

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Rayleigh quotient with bolzano booster for faster convergence of dominant eigenvalues M Zainal Arifin; Ahmad Naim Che Pee; Sarni Suhaila Rahim; Aji Prasetya Wibawa
International Journal of Advances in Intelligent Informatics Vol 8, No 1 (2022): March 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v8i1.718

Abstract

Computation ranking algorithms are widely used in several informatics fields. One of them is the PageRank algorithm, recognized as the most popular search engine globally. Many researchers have improvised the ranking algorithm in order to get better results. Recent research using Rayleigh Quotient to speed up PageRank can guarantee the convergence of the dominant eigenvalues as a key value for stopping computation. Bolzano's method has a convergence character on a linear function by dividing an interval into two intervals for better convergence. This research aims to implant the Bolzano algorithm into Rayleigh for faster computation. This research produces an algorithm that has been tested and validated by mathematicians, which shows an optimization speed of a maximum 7.08% compared to the sole Rayleigh approach. Analysis of computation results using statistics software shows that the degree of the curve of the new algorithm, which is Rayleigh with Bolzano booster (RB), is positive and more significant than the original method. In other words, the linear function will always be faster in the subsequent computation than the previous method.
Knowing group motivation using Bolzano method on PageRank computation M. Zainal Arifin; Ahmad Naim Che Pee; Sarni Suhaila Rahim
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 5: October 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i5.19650

Abstract

On the e-learning system, student assignments are collected, but problems arise that based on observations from two classes of database courses, 73% of students make plagiarism so lecturers need to give motivation to students. Self motivate is needed by with a group of students. For this reason, using a bolzano method or bisection method will provide an overview of the development of the plagiarism trend between groups of students based on scores on similarity score that compute by PageRank algorithm used by Google. Research method is carried out by conducting preliminary observations of plagiarism scores and creating markov matrix. PageRank compute this ranking and Bolzano method find the intersection of two eigenvalues. Bolzano results the maximum and minimum values on range of intervals where each group consists of 5 students. Experiments were conducted in 3 classes of database courses. Trend analysis found that the plagiarism score averaged 54% with a gradient of 3°, this is relatively small but when spread in different groups it becomes larger and student group have a higher plagiarism score. Results implies a way of looking student motivation based on the plagiarism score by a small groupto motivate each other.
Co-Authors Ahmad Naim Che Pee Aji Prasetya Wibawa M. Zainal Arifin M. Zainal Arifin