lmplementasi Metode Holt Exponential Smoothing (Peramalan) Minat Pengunjung Web Penerimaan Mahasiswa Baru lnstitut Teknologi- PLN
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Aslam, Aflahurif’atmi Wahyu
Putra, Rakhmadi lrfansyah
Dahroni, Andi
Putra, Rakhmadi lrfansyah
Dahroni, Andi
Subject
Teknik Informatika
Datestamp
2022-09-27 02:14:18
Abstract :
The ITPLN new student admission system already uses a web-based information system, but the number of web visitors is still small, therefore social media is used to create interesting content so that more registrants are made, but the topics made are still general and based on various sources. Therefore, this study was conducted to predict the interest data of new ITPLN student web visitors to determine the topic or marketing strategy of the ITPLN Marketing and Admissions Agency (BPA) using the Holt's Method of Exponential Smoothing. This method is used to predict data in the form of a linear trend in the 2020 student admission period which previously carried out pre-processing from the original data obtained from Google Analytics. The process of calculating the method is carried out to determine the alpha and beta from 0.1 to 0.9 which is seen from the smallest root median square error (RMSE) and results in alpha 0.1 and beta 0.1. Then the calculation process is carried out using the alpha and beta results obtained with the RMSE results that vary according to each topic, then the top 5 topics are obtained from the forecasting results.
The ITPLN new student admission system already uses a web-based information system, but the number of web visitors is still small, therefore social media is used to create interesting content so that more registrants are made, but the topics made are still general and based on various sources. Therefore, this study was conducted to predict the interest data of new ITPLN student web visitors to determine the topic or marketing strategy of the ITPLN Marketing and Admissions Agency (BPA) using the Holt's Method of Exponential Smoothing. This method is used to predict data in the form of a linear trend in the 2020 student admission period which previously carried out pre-processing from the original data obtained from Google Analytics. The process of calculating the method is carried out to determine the alpha and beta from 0.1 to 0.9 which is seen from the smallest root median square error (RMSE) and results in alpha 0.1 and beta 0.1. Then the calculation process is carried out using the alpha and beta results obtained with the RMSE results that vary according to each topic, then the top 5 topics are obtained from the forecasting results.
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