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All Journal Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat International Journal of Mathematics, Statistics, and Computing
Agatha, Dhela Asafiani
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Mathematics Nursing

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Workshop Peran Statistika Data Sains untuk Siswa-siswi SMA WASKITO Wiyanti, Wiwik; Agatha, Dhela Asafiani; Widjaya, Ferdinand Nathaniel
Abdimas Galuh Vol 6, No 2 (2024): September 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v6i2.15099

Abstract

Permintaan data saintis yang mumpuni di Indonesia saat tulisan ilmiah ini dibuat sedang terus meningkat. Pengetahuan dasar statistika yang berhubungan dengan data sains tentunya diharapkan dapat dibekalkan kepada generasi muda sedini mungkin. Penelitian ini bertujuan untuk mengedukasi peran statistika dalam data sains kepada siswa-siswi SMA Waskito. Metode penelitian yang digunakan untuk keperluan analisa data adalah penelitian Mixed-Method. Adapun parameter kuantitatif yang diukur adalah apakah nilai rata-rata hasil pembelajaran melalui workshop peran statistika data sains untuk kelas XII SMA Waskito lebih dari 70 secara signifikan atau tidak. Sampel yang digunakan dalam penelitian ini adalah 176 siswa kelas XII SMA Waskito. Adapun analisa data menggunakan inferensia One Mean . Dari hasil analisa data diperoleh kesimpulan bahwa dari data post-test yang diperoleh tidak cukup bukti untuk mengatakan bahwa rata-rata nilai post-test lebih besar dari 70. Adapun saran untuk PKM selanjutnya adalah mengelola kelas secara virtual ataupun menggunakan laboratorium untuk praktikum, supaya hasil pembelajaran efektif dan tepat guna.
Prediction of The Electricity Capacity Ready to Sell in DKI Jakarta Using Holt's Linear Exponential Smoothing and Arima Methods Agatha, Dhela Asafiani; Wiyanti, Wiwik
International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 3 (2025): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v3i3.209

Abstract

The point of this study is to look at how well Holt's Linear Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA) can predict time series data that have trend and non-seasonal characteristics. The information on the power capacity available for sale (kWh) at DKI Jakarta serves as the case study. It is anticipated that this study will serve as a guide for choosing efficient techniques for data types with trend and non-seasonal characteristics. This study uses a quantitative methodology with the application of Holt's Linear Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA). A total of 36 data points—monthly data from January 2020 to December 2022—were used in this study. From the analysis results, the error accuracy level was obtained based on the MAPE calculation, namely 3.18% for Holt's Linear Exponential Smoothing. Meanwhile, the best model with the ARIMA method is ARIMA(3,1,1) with a MAPE value of 3.124%. Based on the forecast results from January to March 2023, the predictions with the best model, namely ARIMA(3,1,1), are 3,140,106,571 kWh, 3,149,746,276 kWh and 3,154,664,915 kWh.
Co-Authors Widjaya, Ferdinand Nathaniel Wiwik Wiyanti Wiwik Wiyanti, Wiwik