ANALYSIS OF USER ACCEPTANCE OF SEABANK SERVICES USING THE TECHNOLOGY ACCEPTANCE MODEL (TAM) APPROACH
DOI:
https://doi.org/10.35457/tz2d2q56Keywords:
Digital Banking, Behavioral Intention, Perceived Ease of Use, Perceived Security, Technology Acceptance ModelAbstract
Abstrak: Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi penerimaan pengguna terhadap layanan digital SeaBank menggunakan pendekatan Technology Acceptance Model (TAM) yang diperluas. Model mencakup enam konstruk utama: Perceived Usefulness, Perceived Ease of Use, Perceived Security, Social Influence, Brand Image, dan User Behavior, yang dianalisis terhadap Behavioral Intention. Metodologi yang digunakan adalah pendekatan kuantitatif dengan pengumpulan data melalui survei terhadap 385 individu yang merupakan pengguna SeaBank.. Teknik analisis data menggunakan Structural Equation Modeling (SEM) melalui software WARPPLS. Hasil penelitian menunjukkan bahwa seluruh konstruk berpengaruh signifikan terhadap perilaku dan niat pengguna. Perceived Security dan Perceived Ease of Use menjadi faktor paling dominan terhadap perilaku pengguna, sementara User Behavior memiliki pengaruh paling kuat terhadap Behavioral Intention. Temuan ini menunjukkan pentingnya aspek keamanan, pengalaman pengguna, dan pengaruh sosial dalam membentuk niat penggunaan layanan digital. Penelitian ini berkontribusi pada pengembangan teori TAM dan UTAUT dalam konteks perbankan digital di Indonesia, serta memberikan masukan praktis bagi pengembangan strategi layanan SeaBank di masa depan.
Kata Kunci— Digital Banking, Behavioral Intention, Perceived Ease of Use, Perceived Security, Technology Acceptance Model
Abstract: This study aims to examine the key factors influencing users’ acceptance of SeaBank’s digital services by employing an extended framework of the Technology Acceptance Model (TAM). The model incorporates six core constructs: Perceived Usefulness, Perceived Ease of Use, Perceived Security, Social Influence, Brand Image, and User Behavior, each evaluated in relation to Behavioral Intention. A quantitative method was adopted, utilizing survey data collected from 385 SeaBank users. Data analysis was conducted using Structural Equation Modeling (SEM) via WARPPLS software. The findings reveal that all constructs significantly influence both user behavior and behavioral intention. Among these, Perceived Security and Perceived Ease of Use emerged as the most dominant factors impacting user behavior, while User Behavior demonstrated the strongest influence on Behavioral Intention. These results emphasize the importance of digital security, user experience, and social influence in shaping behavioral intentions toward digital banking services. The study contributes to the advancement of TAM and UTAUT theories within the Indonesian digital banking landscape and provides practical recommendations for future SeaBank service strategies.
Keywords— Digital Banking, Behavioral Intention, Perceived Ease of Use, Perceived Security, Technology Acceptance Model
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