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Perbandingan Berbagai Model Peramalan Indeks Harga Saham Gabungan (IHSG) di Masa Pandemi Covid-19 Bakti Siregar; F. Anthon Pangruruk; Prya Artha Widjaja
Jurnal Multidisiplin Madani Vol. 2 No. 2 (2022): February 2022
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (752.723 KB)

Abstract

The COVID-19 pandemic has a negative impact on various sectors, including the stock market where many people are hesitant to invest in stocks, especially in Indonesia. This condition is due to anxiety and the inability to control random influences in the field of buying and selling shares. However, investors can still get benefits in investing in stocks if every decision is made by using the best model to predict the future trend and determine their optimized portfolio. Therefore, this study aims to compare several models that can forecast the Composite Stock Price Index (IHSG). The results confirmed that the Prophet model is the best. These results are confirmed by observing the MAE, MAPE, MASE, SMAPE, RMSE, and R- squared.
Portfolio Optimization Based on Clustering of Indonesia Stock Exchange: A Case Study of Index LQ45 Bakti Siregar; F. Anthon Pangruruk
Indonesian Journal of Business Analytics Vol. 1 No. 1 (2021): April, 2021
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (700.196 KB) | DOI: 10.55927/ijba.v1i1.5

Abstract

In general portfolio optimization is a technique for selecting the proportion of assets to make a better portfolio by maximizing the expectation return while also minimizing the risk. In this research, k-means clustering method is used to classify stocks are listed on the LQ45 Index and select stocks whose has the price tend to be increase. Then the Markowitz approach is used to analyze the performance of optimization portfolio models that have a minimum variance in expected return and risk. After understanding the performance this portfolio optimization, future works will be able to apply this model in cloud computing or artificial intelligence. In addition, investors will develop a better view of the latest performance of the stocks are listed in LQ45 index and support them decide which stocks that should be include to their portfolios, thus prevent wrong decisions.
Pengenalan Data Science dan Profesi Data Scientist di SMA Pramita Tangerang Bakti Siregar; F. Anthon Pangruruk; Sherly Taurin Siridion; Kefas Ronaldo Immanuel; Jeffry Wijaya; Vanessa Supit; Jocelyn Irene Gani
Jurnal Pengabdian Masyarakat Bestari Vol. 1 No. 2 (2022): May 2022
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (942.491 KB) | DOI: 10.55927/jpmb.v1i3.620

Abstract

Peran sains data diera digital seperti sekarang ini sangatlah penting karena begitu banyak data yang kita produksi setiap hari. Banyak ahli terutama para praktisi memperkirakan bahwa profesi data scientist merupakan profesi yang sangat dibutuhkan khususnya dalam proses penambangan data yang sangat besar (big data). Namun, tingginya permintaan terhadap profesi data scientist ini justru berbanding terbalik dengan ketersedian sumber daya manusia yang ada Indonesia. Sehingga, untuk menjawa  permasalahan tersebutdiatas maka program studi statistika universitas matana merasa penting untung melakukan pengenalan sejak dini perihal sains data dan mengenal dengan baik profesi tersebut. Adapun yang menjadi mitra dalam pengabdian ini adalah SMA Pramita Tangerang, dilaksanakan pada tanggal 2 Juni 2022. Diharapkan, para peserta seminar menyadari pentingnya sains data dan terapannya.