Analisis pemanfaatan katalog online berbasis web (WebPac) dengan menggunakan google analytics

Ulpah Andayani

Abstract


Catalogue generally is used as a tool to help users in finding any information in a library. The emergence and the advancement of information technnology has emerged the technology of computer that transformed the form of catalogue into OPAC that locally can be accessed by multiple users in the sametime. In further development, the advancement of network and internet has emerged WebPac as well that provides users broaden access to any library’ resources either bibliographic or fulltext. Thus, it makes the library’s resources available online recognized by people in the world. WebPac (a web based catalogue) enables users to access library’s catalog remotely and globally through internet network. WebPac, moreover enables the library to analyze and measure the use of online catalog in different methodology. The study of online catalog mostly analyzed by survey methodology to know the potential users who visit and use the library, while WebPac is the study of OPAC that can be analyzed by another approach. The use of WebPac therefore can be measured by using Web analytics with the help of google analytics software.This will be very important for the libraries to know the segmentation of maximum access of remote users, besides it also can expose the ways they interact to the WebPac. At the same time, google analytics can measure user’s behavior when they access online catalog such as technology network and devices they used when they do access. The result of those processess then will give some beneficials directly to the library as the evaluation of library’s catalog performance such as improving the appearance of library’s catalog, examining the content of library’s catalog, giving quick access, etc, besides it can be facilitated the library to known popularly in the world.

 

 


Keywords


library’s catalogue; the advancement of information technology; WebPac; web based catalogue; Web analytics; google analytics; segmentation of remote users; user’s behavior; catalog performance

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DOI: https://doi.org/10.15408/almaktabah.v12i1.1593 Abstract - 0 PDF - 0

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