Analisis Model Autoregressive Distributed Lag Pada Data Google Search Console Pesantren Online - Muhammad Abdul Rohman; Nurfala Safitri; Muhammad Afif Rifqi; Wulan Yuliawanty (Asyafina Akademik Press, 2022)
This study aims to determine the analysis of visits to the Google Search Console Islamic Boarding School data. The website analyzed is asyafina.com, this study uses the Autoregressive Distributed Model with data from July 11, 2021 to February 14, 2022. The results of this study indicate that in the long term, impressions and position on Google have a significant relationship with the number of clicks to visit the web. While in the short term, these variables are not significant. This result is different when using the CTR approach: Position is significant in the short term. This result calls for content creators to use the CTR indicator if they focus on the short term, but if the target indicator is the number of visits, make it a long-term target, so keep on creating content for the long term. Keywords: Autoregressive Distributed Lag, Google Search Console, SEO, content, online Islamic Boarding School