Aplikasi Safe Travel yang diluncurkan pada tahun 2017 oleh Kementerian Luar Negeri RI merupakan wujud pemanfaatan diplomasi digital untuk memberikan perlindungan bagi seluruh Warga Negara Indonesia (WNI) yang ada di luar negeri, khususnya yang bepergian untuk sementara waktu. Namun, hingga Juli 2021, aplikasi Safe Travel baru diunduh sebanyak ±100 ribu pengunduh, baik pada Google Play Store maupun Apple App Store. Dan diketahui hingga Juli 2021, tercatat bahwa sebanyak 98,8% users lost dari total user yang diperoleh pada aplikasi Safe Travel di Google Play Store. Sedangkan pada Apple App Store, diketahui bahwa tingkat retensi pengguna dan rata-rata penggunaan aplikasi per bulan untuk perangkat pengguna yang aktif sangat rendah. Jumlah users lost yang tinggi dan rendahnya penggunaan aplikasi Safe Travel menunjukkan kurangnya penerimaan terhadap aplikasi Safe Travel yang pada akhirnya berpengaruh terhadap upaya pemerintah dalam memberikan perlindungan bagi WNI yang ada di luar negeri, sesuai yang tertuang pada Permenlu Nomor 5 Tahun 2018. Berdasarkan permasalahan tersebut, digunakan tiga model utama, yaitu UTAUT-2, TAM, dan IS Success Model, yang membentuk model penelitian untuk mengetahui faktor-faktor yang memengaruhi penerimaan pengguna aplikasi Safe Travel. Pengolahan data dilakukan menggunakan Partial Least Square-Structural Equation Modeling (PLS-SEM) dengan alat bantu SmartPLS 3 pada 144 data yang berhasil dikumpulkan dengan menggunakan kuesioner online. Dari 21 hipotesis yang diuji dalam penelitian ini, didapatkan bahwa 8 hipotesis ditolak dan sisanya diterima. Faktor-faktor yang berpengaruh secara langsung terhadap penerimaan dan penggunaan aplikasi Safe Travel antara lain behavioral intention, facilitating condition, dan habit. Sedangkan faktor-faktor yang berpengaruh secara tidak langsung antara lain, information quality, system quality, service quality, perceived trust of e-government, attitude, dan effort expectancy. Wawancara dengan pihak pengelola dan pengguna aplikasi Safe Travel kemudian dilakukan, sehingga didapatkan 32 rekomendasi praktis yang dikelompokkan berdasarkan pengaruh dari setiap faktor.
The Safe Travel application, which was launched in 2017 by the Indonesian Ministry of Foreign Affairs, is a form of utilizing digital diplomacy to provide protection for all Indonesian citizens who are abroad, especially those traveling temporarily. However, until July 2021, the Safe Travel application has only been downloaded by ±100 thousand downloads, both on the Google Play Store and Apple App Store. And it is known that until July 2021, it was recorded that 98.8% of users were lost from the total users obtained in the Safe Travel application on the Google Play Store. Meanwhile, in the Apple App Store, it is known that the user retention rate and the average application usage per month for active devices are very low. The high number of users lost and the low use of the Safe Travel application indicate a lack of acceptance of the Safe Travel application which ultimately affects the government's efforts to provide protection for Indonesian citizens abroad, as stated in the Minister of Foreign Affairs Regulation Number 5 of 2018. Based on these problems, three main models are used, namely UTAUT-2, TAM, and IS Success Model, which form a research model to determine the factors that influence user acceptance of the Safe Travel application. Data processing was carried out using Partial Least Square-Structural Equation Modeling (PLS-SEM) with the SmartPLS 3 tool on 144 data that were collected using an online questionnaire. Of the 21 hypotheses tested in this study, it was found that 8 were rejected and the rest were accepted. Factors that directly influence the acceptance and use of the Safe Travel application include behavioral intention, facilitating conditions, and habit. While the factors that influence indirectly include information quality, system quality, service quality, perceived trust of e-government, attitude, and effort expectancy. Interviews with managers and users of the Safe Travel application were conducted, which resulted in 32 practical recommendations grouped based on the influence of each factor. |
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