Judul: Penggerombolan Data Panel Emiten Sektor Pertambangan selama Pandemi Covid-19
Abstrak: The Covid-19 pandemic has made people start looking for new income, one of which is stock investment. Mining Stock recorded the highest sectoral index increase in 2020. The high increase in the mining sector index doesn’t indicate all of the stocks have a good performance. Clustering data of mining stock can help to see which stock has the best performance. Variables used in clustering are technical factors with details: return, trading volume, transaction frequency, bid volume, and foreign buy. Data in this research is longitudinal data from March 2020 until January 2022 and the clustering technique used is k-means. Clustering on outliers data and non-outliers data is done separately. Definition of outliers is exploratively with biplot analysis. Clustering on outliers data results obtained are five clusters and clustering on non-outliers data results obtained are two clusters. Best cluster is cluster who obtained ANTM because has highest value in return, transaction frequency, and foreign buy.
Keyword: clustering on longitudinal data, k-means, mining, stock, technical factor

Judul: Clustering Saham Pasca Pandemi COVID-19 Menggunakan Metode Probabilistic Distance Clustering Adjusted for Cluster Size
Abstrak: Pada tahun 2020, pandemi COVID-19 mengakibatkan penurunan drastis harga saham di pasar saham yang menyebabkan investor mengalami kerugian besar. Dalam menghadapi perubahan ini, investor membutuhkan strategi baru untuk mengurangi risiko dan meningkatkan return investasi. Clustering saham menggunakan metode Probabilistic Distance Clustering Adjusted for Cluster Size (PDQ) dapat menjadi suatu alat untuk menganalisis pasar saham yang merupakan langkah penting untuk mengurangi risiko dan meningkatkan return investasi. Dalam penelitian ini, digunakan data 300 saham yang diperdagangkan di bursa efek NASDAQ dan NYSE pada tahun 2023 dengan variabel nilai beta, return saham, dan Earning per Share (EPS). Berdasarkan hasil clustering, terdapat dua cluster yang terbentuk. Cluster pertama memiliki rata-rata return saham yang lebih tinggi dengan risiko yang lebih tinggi dibandingkan dengan saham pada cluster kedua. Kemudian, cluster kedua memiliki rata-rata nilai beta yang lebih rendah dengan EPS yang lebih tinggi dibandingkan dengan cluster pertama, yang menunjukkan bahwa saham pada cluster kedua lebih tidak sensitif terhadap perubahan pasar dan memiliki nilai valuasi perusahaan yang lebih tinggi.
Keyword: clustering

Judul: Penyelesaian Masalah Rotasi Aliran Fluida Kental Von Karman Menggunakan Metode Homotopi
Abstrak: Von Karman equation is an equation that describes fluid viscous flow induced by infinite disk rotation. By assuming steady flow and laminar, viscous incompressible fluid flow is represented in Von Karman equation by an angular velocity and the vertical direction velocity as the independent variables. Von Karman equation is a nonlinear problem that is solved using the homotopy method. The use of homotopy method is done by defining an homotopy function that requires auxiliary parameters to control the convergent region of the solution. The solution is a recursive formula with given initial conditions. Using software based-functional shows that velocity components converge to a value.
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