Satellite-based early warning of extreme atmospheres through the website has been used for various purposes such as early warning of a flood, early warning of strong winds, early warning of tidal wave height, and early warning of transportation. One of the network-based extreme atmosphere early warning systems is the Satellite Disaster Early Warning System (SADEWA). SADEWA obtains data automatically from the Automatic Weather Station (AWS) displayed on the website. The weather parameters displayed are temperature, humidity, and rainfall. Technology Acceptance Model (TAM) and Best Worst Method (BWM) seem appropriate enough to examine individual perceptions of SADEWA acceptance because there has been no similar research in this field. Data on the 50 perceptions of user behavior were analyzed using multiple linear regression and BWM to determine the factors that influence and also the level of user acceptance of SADEWA. There are 4 (four) factors that influence user acceptance of SADEWA, namely Perceived Usefulness (PU), Perceived Risk (PR), Attitude to Use (AU), and Environmental Influence (EI). The level of acceptance is in receiving SADEWA.


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    Titel :

    Study on satellite disaster early warning system (SADEWA) acceptance with technology acceptance model


    Beteiligte:

    Kongress:

    THE 9TH INTERNATIONAL SEMINAR ON AEROSPACE SCIENCE AND TECHNOLOGY – ISAST 2022 ; 2022 ; Bogor, Indonesia


    Erschienen in:

    Erscheinungsdatum :

    11.12.2023


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch