Dataset of Usability and Acceptance of Alboom: A Crowd-Based Early Warning System for Harmful Algal Blooms

Citation Author(s):
Lindung Parningotan
Manik
Hatim
Albasri
Reny
Puspasari
Zaenal
Akbar
Foni Agus
Setiawan
Aris
Yaman
Shidiq Al
Hakim
Al Hafiz Akbar Maulana
Siagian
Siti Kania
Kushadiani
Slamet
Riyanto
Dadan Ridwan
Saleh
Yulia Aris
Kartika
Ariani
Indrawati
Ika Atman
Satya
Lolita
Thesiana
Puput Fitri
Rachmawati
Meuthia Aula
Jabbar
Ramadhona
Saville
Masaaki
Wada
Submitted by:
Lindung Manik
Last updated:
Mon, 07/08/2024 - 15:59
DOI:
10.21227/txqy-3d55
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Abstract 

Alboom is a crowd-based smartphone application and database system to record, store, analyze, share, and provide early warning information regarding harmful algal blooms (HABs). Similar to other participatory-based applications, the willingness of community members to be actively involved is paramount to the success of the application implementation. The dataset is the investigation results of usability and acceptance of Alboom. The questionnaires were built using an augmented technology acceptance model (TAM) to identify factors that affect the continual use intention of the application. In addition to the native TAM variables, such as perceived ease of use and usefulness as well as attitude, other factors, including HAB awareness, social influence, and reward, were also studied. Furthermore, the usability factor was also examined, specifically using the System Usability Scale (SUS) approach.

Instructions: 

The column names in the data are self-explanatory.

Funding Agency: 
Japan International Cooperation Agency, Japan Science Technology Agency, and the Indonesian Ministry of Marine Affairs and Fisheries through the Science and Technology Research Partnership for Sustainable Development (SATREPS) Mariculture Project Grant.