Predicting Figure Coalition for 2019 Indonesian Presindential Election Using Modified Markov Clustering Algorithm
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Abstract
This paper presents a new approach to ameliorate the Markov Cluster algorithm for predicting ?gure coalition for 2019 Indonesian Presidential Election. The proposed method is the modi?cation of the Markov Clustering algorithm. First, 20 ?gures are collected to form a 20 x 20 matrix. Second, the entries of the matrix are scored by 0, 1, 2, or 3 concerning the number of positive comments from netizen towards the observed ?gures photo on Instagram. Third, we implemented the Markov Clustering to ?nd the clusters that represent the number of coalitions. The effectiveness of the proposed method is con?rmed by comparing the prediction results with the actual coalition.
Article Details
Section
Applied Mathematics
References
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[3] R. Ginanjar, A. Bustamam, and H. Tasman, ˜Implementation of regularized Markov clustering algorithm on protein interaction networks of schizophrenia's risk factor candidate genes, IEEE Transactions on Reliability, pp. 297-302, 2016.
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[5] A. Bustamam, T. Siswantining, N. L. Febriyani, and I. D. Novitasari, ˜Protein sequences clustering of herpes virus by using Tribe Markov clustering (Tribe-MCL), AIP Conf. Proc., vol. 1862, pp. 030150-1-030150-8, 2017.
[6] A. Bustamam, M. S. Wisnubroto, and D. Lestari, ˜Analysis of protein-protein interaction network using Markov clustering with pigeon-inspired optimization algorithm in HIV (human immunodeficiency virus), AIP Conf. Proc., vol. 2023, pp. 020229-1-020229-6, 2018.
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