PENERAPAN MODEL-BASED CLUSTERING PADA PENGELOMPOKAN SAHAM BERDASARKAN RASIO KEUANGAN
DOI:
https://doi.org/10.34123/jurnalasks.v15i1.510Abstract
Untuk meminimalkan kerugian dengan tingkat keuntungan tertentu, investor perlu memilih saham potensial agar keuntungan yang diperoleh optimal. Penelitian ini bertujuan untuk mengetahui penerapan Model-Based Clustering (MBC) dalam mengelompokkan perusahaan berdasarkan kinerja keuangan saham. Indikator keuangan yang digunakan yaitu data rasio likuiditas, profitabilitas, dan solvabilitas tahun 2020 untuk perusahaan yang terdaftar pada indeks LQ45. Dari proses clustering, terbentuk 6 cluster dengan nilai BIC -709,3757 dan model optimal terpilih VEV. Berdasarkan nilai rata-rata setiap rasio, cluster 6 merupakan cluster terbaik karena memiliki mayoritas rasio likuiditas dan profabilitas terbaik serta rasio solvabilitas terrendah. Cluster 6 memiliki kemampuan yang tinggi dibandingkan perusahaan cluster lain untuk membiayai kegiatan operasional perusahaan dan memenuhi kewajiban keuangannya jangka pendek.
Downloads
References
Andy, and Melly Megawati. 2019. “Analysis of Liquidity , Profitability and Solvency Ratios to Assess the Financial Performance of Companies in Cigarette Industries Listed on the Indonesia Stock Exchange.” ECo-Fin 1 (1): 22–34. https://doi.org/https://doi.org/10.32877/ef.v1i1.54.
Banfield, Jeffrey D., and Adrian E. Raftery. 1993. “Model-Based Clustering and Non-Gaussian Clustering.” Biometrics 49 (3): 803–21.
Bennett, Mark J., and Dirk L. Hugen. 2016. Financial Analytics with R: Building a Laptop Laboratory for Data Science. United Kingdom: Cambridge University Press.
Bishop, Christoper M. 2006. Pattern Recognition and Machine Learning. New York: Springer
Bouveyron, Charles, Gilless Celeux, T. Brenden Murphy, and Adrian E. Raftery. 2019. Model-Based Clustering and Classification for Data Science: With Application in R. United Kingdom: Cambridge University Press.
Deisenroth, Marc Peter, A Aldo Faisal, and Cheng Soon Ong. 2020. Mathematics For Machine Learning. Cambridge: Cambridge University Press. https://doi.org/10.1017/9781108679930
Fraley, Chris, and Adrian E Raftery. 2002. “Model-Based Clustering , Discriminant Analysis , and Density Estimation.” Journal of the American Statistical Association 97 (458): 611–31.
Gan, Guojun, Chaoqun Ma, and Jianhong Wu. 2007. Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability). Philadelphia, Pennsylvania: Society for Industrial and Applied Mathematics American.
Husnan, Suad., Enny Pudjiastuti, 2004. Dasar-Dasar Manajemen Keuangan. Edisi. Keempat, Yogyakarta, UPP AMP YKPN.
Mcnicholas, Paul D. 2016. “Model-Based Clustering.” Journal of Classificatio 373 (November): 331–73. https://doi.org/10.1007/s0035.
Munawir, S, 2002. Akuntansi Keuangan dan Manajemen, Edisi Pertama, Penerbit BPFE, Yogyakarta.
Qona’ah, Niswatul, Alvita Rachma Devi, and I Made Gde Meranggi Dana. 2020. “Laboratory Clustering Using K- Means, K -Medoids , and Model- Based Clustering.” Indonesian Journal of Applied Statistics 3 (1): 64–77.
Rist, Michael, and Albert J. Pizzica. 2015. Financial Ratios For Executives. New
York: Apress Berkeley, CA.
Scrucca L., Fop M., Murphy T. B. and Raftery A. E. (2016) mclust 5: clustering, classification and density estimation using Gaussian finite mixture models The R Journal 8/1, pp. 289-317
Shalev-shwartz, Shai, and Shai Ben-david. 2014. Understanding Machine Learning Machine: From Theory to Algorithms. New York: Cambridge University Press.
S.R. Nanda, B. Mahanty, M.K. Tiwari (2010) Clustering Indian Stock Market Data for Portfolio Management. Expert Systems with Applications 37 (2010) 8793-8798
Subekti, R, E R Sari, and R Kusumawati. 2018. “Ant Colony Algorithm for Clustering in Portfolio Optimization.” In IOP Conf. Series: Journal of Physics: Conf. Series 983.
Subekti, Retno, Rosita Kusumawati, and Eminugroho Ratna Sari. 2017. “K-Means Clustering dan Average Linkage dalam Pembentukan Portfolio Saham.” In Seminar Matematika Dan Pendidikan Matematika UNY T-31, 219–24.
