Peramalan Jumlah Penumpang LRT Sumsel dengan Metode Exponential Smoothing

Riski Rahmatul Lailiyah, Riza Agustiani
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Abstract

Forecasting is critical in the pandemic sector as part of the effort to adapt the post-pandemic system, particularly in transportation. This research carried out on the South Sumatra Integrated Railroad (LRT) in the post-pandemic Covid-19 period. Forecasting is done in this study using the exponential smoothing method using alpha that is α=0.1, α=0.5, and α= 0.9. Comparison with the smallest error using the exponential smoothing method dropped the choice at alpha 0.1 with the smallest error calculation value. Forecasting using the exponential smoothing method with 0.1 alpha sample data on the number of LRT Sumsel passengers during the Covid-19 period in 2020 produces a forecast of 66,538 passengers with an error rate of Mean Absolute Deviation (MAD)=9,486, Mean Square Error (MSE)=1,150, and Mean Absolute Percentage Error (MAPE)=24.58%. Meanwhile, from the sampel data on the number of South Sumatra LRT passengers on post-pandemic Covid-19 period in 2022, it produced a forecast of 187,566 passengers with Mean Absolute Deviation (MAD) = 25,816, Mean Square Error (MSE) = 9,477, and Mean Absolute Percentage Error (MAPE) = 16.60%.
作为适应大流行后系统努力的一部分,预测在大流行部门至关重要,特别是在运输方面。本研究是在Covid-19大流行后时期对南苏门答腊综合铁路(LRT)进行的。本研究采用指数平滑法进行预测,采用α=0.1, α=0.5, α= 0.9。与最小误差比较,使用指数平滑法降低了选择在alpha 0.1处具有最小误差的计算值。利用0.1 alpha样本数据的指数平滑法对2020年新冠肺炎期间Sumsel轻轨乘客人数进行预测,得出预测人数为66538人,平均绝对偏差(MAD)= 9486,均方误差(MSE)= 1150,平均绝对百分比误差(MAPE)=24.58%。同时,根据2019冠状病毒病大流行后的2022年南苏门答腊岛轻轨乘客数量的样本数据,预测出187566名乘客,平均绝对偏差(MAD) = 25816,均方误差(MSE) = 9477,平均绝对百分比误差(MAPE) = 16.60%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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