PREDICTING FIGURE COALITION FOR 2019 INDONESIAN PRESIDENTIAL ELECTION USING MODIFIED MARKOV CLUSTERING ALGORITHM
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Abstrak
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 MCL method is used in this research because the algorithm can be used to clustering large data with a high level of sparsity. The effectiveness of the proposed method is con?rmed by comparing the prediction results with the actual coalition. The result is Markov Clustering method can be used to solve problems in the fields of politics with detail ?rst coalition consist of seven members with the center is PRO and the other coalition, consist of six members with the center is JKW.
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Terbitan
Bagian
Applied Mathematics
Referensi
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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.
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