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All Journal Journal of Mathematics, Computation and Statistics (JMATHCOS) Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Bakti Siregar
Institut Teknologi Sains Bandung
Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance Engineering Mathematics Public Health Social Sciences

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Improving Data Science Literacy Through Training at the Auxano Indonesia Muda Foundation: Peningkatan Literasi Sains Data Melalui Pelatihan Di Yayasan Auxano Indonesia Muda Bakti Siregar; Monica Mayeni Manurung; Chello Frhino Mike Mandolang; Olivia Meilinda Davtin Pesireron
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 9 No. 2 (2025): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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Abstract

Data science literacy refers to an individual’s ability to understand, process, and utilize data effectively to support informed decision-making. In today’s digital era, where information is abundant, this competency has become essential across various segments of society. Responding to this need, a training program was designed and implemented to enhance the data literacy of members of the Auxano Indonesia Muda Foundation (YAIM). The program was conducted online in November 2024 by a team from the Data Science Study Program at the Institut Teknologi Sains Bandung (ITSB). The training adopted a participatory approach, incorporating conceptual materials, guided discussions, and hands-on data processing exercises. The evaluation results showed an improvement in participants’ understanding of basic data science principles and encouraged the application of data-driven approaches within their organizational activities. This initiative is expected to serve as a foundation for fostering a more analytical and structured working culture in social institutions.
Comparison of Holt Winter's and SARIMA Methods on the data of the Number of Foreign Tourist Visits in Bali Province Clara Della Evania; Bakti Siregar
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 Chello Frhino Mike Mandolang Clara Della Evania Monica Mayeni Manurung Olivia Meilinda Davtin Pesireron