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Journal : The Indonesian Journal of Computer Science

analisis Analisis Pengaruh Dimensi Budaya Terhadap Penggunaan Aplikasi Capcut Menggunakan UTAUT2 Ariyansir, Sigit; Syaifullah; Khairil Ahsyar, Tengku; Jazman, Muhammad; Marsal, Arif
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4430

Abstract

This research aims to determine the factors that influence the intention and use of the Capcut application, using Hofstede's extended UTAUT2 model with cultural variables. Data was collected through observation, interviews, document review and questionnaires. The analytical method used is PLS-SEM, with external models, internal models and hypothesis testing. The research results show that of the many hypotheses tested, only H3 (social influence on behavioral intentions), H7b (habits on usage behavior) and H14 (passion/restraint usage behavior) were accepted. Other hypotheses, such as performance expectations, effort expectations, and other cultural dimensions, did not show significant influence on usage intentions and behavior. In conclusion, habitual factors and social influence are the main drivers for adopting the Capcut application, while other factors do not have much influence in the context of this research
Analisis Kepuasan Pengguna Aplikasi LinkAja Menggunakan Metode TAM dan EUCS Nisa', Sayyidatun; Megawati; Zarnelly; Permana, Inggih; Marsal, Arif
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4511

Abstract

Aplikasi LinkAja banyak digunakan karena memudahkan bertransaksi. Namun banyak pengguna mengalami kendala seperti, tidak dapat melakukan pembayaran QRIS, transaksi gagal namun saldo sudah terpotong, dan kesulitan mengupgrade ke LinkAja full service. Penelitian ini bertujuan menganalisis tingkat kepuasan pengguna aplikasi LinkAja dengan mengintegrasikan metode Technology Acceptance Model (TAM) dan End User Computing Satisfaction (EUCS). Berdasarkan perhitungan Lemeshow, responden dalam penelitian ini sebanyak 100 orang. Pengumpulan data dilakukan dengan menyebarkan kuesioner kepada pengguna aplikasi LinkAja. Temuan penelitian menunjukkan bahwa 5 hipotesis diterima, yaitu persepsi kemanfaatan, isi, akurasi, bentuk, dan sikap terhadap penggunaan. Sementara 3 hipotesis ditolak, yaitu persepsi kemudahan penggunaan, kemudahan penggunaan, dan ketepatan waktu. Hasil PLS-SEM menunjukkan bahwa kepuasan pengguna memiliki pengaruh positif. Ditunjukkan oleh korelasi kuat antara tiap variabel, dengan nilai R-Square kepuasan pengguna sebesar 84,6%. Ini menunjukkan bahwa aplikasi LinkAja menjalankan fungsinya dengan baik sehingga pengguna merasa puas ketika menggunakannya.
Analisis Kepuasan Pengguna Aplikasi iRiau Menggunakan Metode EUCS dan TAM Praniffa, Anisya Caty; Ahsyar, Tengku Khairil; Jazman, Muhammad; Syaifullah; Marsal, Arif
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4604

Abstract

iRiau is a digital platform that makes it easier for people to access the Soeman HS library. User satisfaction assessments are made to access the extent of iRiau application being relevant and effective. The study use the EUCS and TAM methods to identify factors affecting user satisfaction. The study sample involved 125 analyzed respondents using SPSS. According the research, five of the seven hypotheses tested were accepted. Variable Perceived Usefulness, Content, Accuracy, Format, and Timeliness significantly impact user satisfaction. However, variables of Perceived of Use and Ease of Use are insignificant. Variables with the most significant influences are Perceived Usefulness and Timelliness. The linar regression model produces an R-Square of 0.959, showing that such independent variables explain 95.9% of user satisfaction.