Determining Strategies on Playing Badminton using the Knuth-Morris-Pratt Algorithm

Riza, Lala Septem; Firmansyah, Muhammad Irfan; Siregar, Herbert; Budiana, Dian; Rosales-Pérez, Alejandro

doi:10.12928/telkomnika.v16i6.11554

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…Different tasks in the related research to bioinformatics can be applied to test the proposed model as well, such as prediction on cáncer [22], kidney disease [23], and sleep disorder [24]. Additionally, another method that can be implemented for dealing with this research is Knuth Morris Pratt [25,26].…”

Section: Discussionmentioning

confidence: 99%

Parallel random projection using R high performance computing for planted motif search

Riza¹,

Dhiba²,

Setiawan³

et al. 2019

TELKOMNIKA

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Motif discovery in DNA sequences is one of the most important issues in bioinformatics. Thus, algorithms for dealing with the problem accurately and quickly have always been the goal of research in bioinformatics. Therefore, this study is intended to modify the random projection algorithm to be implemented on R high performance computing (i.e., the R package pbdMPI). Some steps are needed to achieve this objective, ie preprocessing data, splitting data according to number of batches, modifying and implementing random projection in the pbdMPI package, and then aggregating the results. To validate the proposed approach, some experiments have been conducted. Several benchmarking data were used in this study by sensitivity analysis on number of cores and batches. Experimental results show that computational cost can be reduced, which is that the computation cost of 6 cores is faster around 34 times compared with the standalone mode. Thus, the proposed approach can be used for motif discovery effectively and efficiently.

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Section: Discussionmentioning

confidence: 99%

Parallel random projection using R high performance computing for planted motif search

Riza¹,

Dhiba²,

Setiawan³

et al. 2019

TELKOMNIKA

Self Cite

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“…4) Testing the Knuth Morris Pratt Algorithm on Search Engine Systems At the testing stage, it will be tested regarding the implementation of the Knuth Morris Pratt algorithm in the search system (search engine) [14][15][16][17]. At this stage, the performance of the Knuth Morris Pratt algorithm will be known in obtaining optimal and accurate search results.…”

Section: ) Writing Kmp Functions On Search Enginesmentioning

confidence: 99%

Knuth Morris Pratt String Matching Algorithm in Searching for Zakat Information and Social Activities

Riawan

2022

J. Appl. Data Sci.

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Algorithms are one of the components that need to be considered in the development of information systems. Determination of the algorithm is adjusted to the purpose of the system to be built. One algorithm that can be used is string matching. The string matching algorithm will play a role in searching for a string consisting of several characters (usually called a pattern). The method used in this research is string matching knuth morris pratt (KMP) which is used to search zakat information and social activities in the search engine system. KMP is a string matching algorithm with good performance. The results showed the performance of string matching using the KMP algorithm with 5 trials of input pattern on zakat information with execution times of 0.03 ms, 0.03 ms, 0.02 ms, 0.02 ms and 0.03 ms. And 5 times the input pattern experiment on social activities with execution time of 0.02 ms, 0.02 ms, 0.03 ms, 0.03 ms and 0.02 ms. Thus the average execution time of the KMP algorithm in string matching is 0.026 ms and 0.024 ms.

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“…The KMP algorithm has a different shift than the Boyer-Moore algorithm. Broadly speaking the stages in the KMP algorithm, when performing string matching are [16,20,22,30]: a. Algorithms KMP starts matching pattern at the beginning of the text b. The KMP algorithm performs a shift or matching pattern character with text characters from left to right by matching characters per character until one of the conditions is met.…”

Section: Knuth Morris Pratt Algorithm (Kmp)mentioning

confidence: 99%

“…The boundary value is calculated based on a character pattern only. If anyone appreciates the character in the pattern, then the edge value 1 and so on will increase in value with the value j, and I shift to the next pattern character [16,20,22,30]. Table 4.…”

Section: Knuth Morris Pratt Algorithm (Kmp)mentioning

confidence: 99%

Comparison of search algorithms in Javanese-Indonesian dictionary application

et al. 2020

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This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. Performance Testing is used to test the performance of algorithm implementations in applications. The test results show that the Boyer Moore and Knuth Morris Pratt algorithms have an accuracy rate of 100%, and the Horspool algorithm 85.3%. While the processing time, Knuth Morris Pratt algorithm has the highest average speed level of 25ms, Horspool 39.9 ms, while the average speed of the Boyer Moore algorithm is 44.2 ms. While the complexity test results, the Boyer Moore algorithm has an overall number of n 26n 2 , Knuth Morris Pratt and Horspool 20n 2 each.

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Determining Strategies on Playing Badminton using the Knuth-Morris-Pratt Algorithm

Cited by 5 publications

References 22 publications

Parallel random projection using R high performance computing for planted motif search

Parallel random projection using R high performance computing for planted motif search

Knuth Morris Pratt String Matching Algorithm in Searching for Zakat Information and Social Activities

Comparison of search algorithms in Javanese-Indonesian dictionary application

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