Article Per Year (5 Year)
p-Index From 2021 - 2026
3.712
P-Index
This Author published in this journals
All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Saintia Matematika Computatio : Journal of Computer Science and Information Systems Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Syntax Literate: Jurnal Ilmiah Indonesia KOMPUTIKA - Jurnal Sistem Komputer Syntax Idea Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Syntax Transformation Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika International Journal of Business, Economics, and Social Development FARABI: Jurnal Matematika dan Pendidikan Matematika Jurnal Sisfotek Global Jurnal Multidisiplin Madani (MUDIMA) Indonesian Journal of Business Analytics (IJBA) Jurnal Pengabdian Masyarakat Bestari (JPMB) Formosa Journal of Applied Sciences (FJAS) Mutiara: Multidiciplinary Scientifict Journal Jurnal Inovasi Global Journal of Mathematics, Computation and Statistics (JMATHCOS)
Bakti Siregar
Jurusan Statistika Universitas Matana
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Journal of Mathematics, Computation and Statistics (JMATHCOS)

 1 
The Comparative Analysis of Integrated Moving Average and Autoregressive Integrated Moving Average Methods for Predicting Bitcoin Returns Brigita Tiara Elgityana Melantika; Kalfin; Siregar, Bakti; Wiwik Wiyanti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.3788

Abstract

The rise in popularity of cryptocurrencies such as Bitcoin across various platforms has attracted the attention of young investors, making it easier for them to invest. However, due to the volatile nature of Bitcoin, this type of investment carries a high risk. Therefore, this research conducts an analysis of stock return prices to minimize losses and help investors make effective investment decisions through stock price prediction. The focus of this study is on predicting Bitcoin stock returns by analyzing closing price data over the past five years (2019-2024).  The methods used are a comparison between Integrated Moving Average (IMA) and Autoregressive Integrated Moving Average (ARIMA) with a quantitative approach using R Studio software. One of the main focuses of this research is the comparison of error estimation values between the two methods, namely Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The data analyzed comprises the daily closing prices of Bitcoin over the last five years, which is publicly accessible data. The best model for predicting the daily return of Bitcoin stock is the ARIMA (1,0,1) model. The predicted values for the next five days, from May 27, 2024, to May 31, 2024, are 0.0016632438, 0.0007991618, 0.0013415932, 0.0010010794, and 0.0012148386. The ARIMA (1,0,1) model has error measurement values with an MAE of 2.3% and an RMSE of 3.5%. It is hoped that this research will provide a better understanding of the effectiveness and relative advantages of the IMA and ARIMA methods in forecasting cryptocurrency returns, thereby offering more accurate guidance for investors in making investment decisions.
Comparative Analysis of K-Means and K-Medoids Algorithms for Product Sales Clustering and Customer Yosia; Siregar, Bakti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4053

Abstract

In today's rapidly evolving business landscape, effective product management is crucial for maintaining a company's competitive advantage. Comprehensive analysis is essential for providing insights that inform strategic business development decisions. This study examines the sales data of PT XYZ from July 2020 to May 2024 using the K-Medoids algorithm, with dimensionality reduction applied through Principal Component Analysis (PCA). The clustering results identified three customer segments: Cluster 1 with 46 customers, Cluster 2 with 76 customers, and Cluster 3 with 62 customers. For product segmentation, four clusters were identified: Cluster 1 with 52 products, Cluster 2 with 12 products, Cluster 3 with 20 products, and Cluster 4 with 53 products. The K-Medoids algorithm demonstrated superior performance compared to K-Means in terms of cluster separation and interpretability, with visualizations that enhance the understanding of customer and product distributions. This research aids the company in enhancing customer satisfaction, optimizing inventory, and increasing profitability.
Comparison of Holt Winter's and SARIMA Methods on the data of the Number of Foreign Tourist Visits in Bali Province Evania, Clara Della; Siregar, Bakti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4211

Abstract

The tourism sector is a critical component of a country’s economy, including in Indonesia, where its impact is felt both nationally and regionally, such as in provinces and cities. This research focuses on Bali Province and aims to conduct a comparative analysis of the Holt-Winter’s and Seasonal Auto-regressive Integrated Moving Average (SARIMA) methods for forecasting foreign tourist arrivals. The analysis centers on two primary entry points: Ngurah-Rai Airport and the seaport. The primary objective is to forecast the number of foreign tourist arrivals from February 2024 to January 2025. The results indicate that the Holt-Winter’s model has a Mean Absolute Percentage Error (MAPE) of 5.2631%, which is lower than the MAPE of 5.8920% for the SARIMA model. Additionally, the Mean Absolute Error (MAE) for the Holt-Winter’s model is 19,149.18, compared to 20,883.20 for the SARIMA model. Consequently, this study concludes that the Holt-Winter’s model provides more accurate predictions and is closer to the actual values than the SARIMA model. Bali, Holt-Winter’s, forecasting, SARIMA, tourism.
Co-Authors Alicia Arifin Anggraiwan, Yonathan Barus, Simon Prananta Brigita Tiara Elgityana Melantika Clara Della Evania Dhela Asafiani Agatha Dhela Asafiani Agatha Evania, Clara Della F. Anthon Pangruruk F. Anthon Pangruruk F. Anthon Pangruruk Ferdinand Nathaniel Widjaya Gregoria Illya Gunawan, Naftali Brigitta Januaviani, Trisha Magdalena Adelheid Jeffry Wijaya Jimy, Valensius Jocelyn Irene Gani kalfin Kalfin Kalfin, Kalfin Kefas Ronaldo Immanuel Natalie, Karen Pangruruk, F. Anthon Permana, Garry Julius Prya Artha Widjaja Riswandi, Calvin Sawaluddin Nasution Sherly Taurin Siridion Siridion, Sherly Taurin Sukono Sukono Tulus Tulus Valensius Jimy Vanessa Supit Widjaja, Preya Artha Windjaya, Putri Angelina Wiwik Wiyanti Wiwik Wiyanti Yosia Yosia Yosia Yosia, Yosia