Perluasan technology acceptance model (tam) pada konteks internet broadband (studi pada mahasiswa s1 fakultas ekonomi universitas sebelas maret solo)

Oleh :
Muhamad Irfani - F0203107 - Fak. Ekonomi dan Bisnis

ABSTRAK Studi ini melakukan perluasan Technology Acceptance Model (TAM) dengan menambahkan tiga variabel yaitu perceived enjoyment, compatibility dan perceived resources untuk mengungkap faktor-faktor yang menjadi variabel kunci pada konteks teknologi internet broadband dengan setting Indonesia. Permasalahan yang diangkat dalam penelitian ini adalah bagaimana pengaruh: (1) perceived enjoyment pada perceived usefulness, perceived ease of use, dan behavioral intention, (2) compatibility pada perceived usefulness dan perceived ease of use, (3) perceived resources pada perceived usefulness, perceived ease of use dan behavioral intention, (4) perceived usefulness pada behavioral intention, (5) perceived ease of use pada perceived usefulness dan behavioral intention. Penelitian ini merupakan penelitian kausal dengan metode survey melalui kuesioner. Teknik sampling yang digunakan pada studi ini adalah non probability sampling dengan metode purposive sampling. Target populasi adalah mahasiswa S1 FE UNS Solo yang sudah pernah menggunakan akses internet broadband Speedy dengan jumlah sampel yang diambil sebanyak 197 responden. Studi ini menggunakan analisis Structural Equation modeling (SEM) dengan estimasi Maximum Likelihood (ML) melalui Program AMOS versi 4.01. Goodness-of-fit setelah dilakukan modifikasi atas model yang diajukan menunjukkan hasil yang baik. Berikut ini adalah urutan hasil pengukuran model penelitian yang telah dimodifikasi: 2 = 169.412; probabilitas = 0.065; RMSEA = 0.032; GFI = 0.920; AGFI = 0.883; CMIN/DF = 1.185; TLI = 0.982; CFI = 0.987. Hasil pengujian hipotesis menunjukkan bahwa: (H1) perceived enjoyment berpengaruh positif pada perceived usefulness; (H2) perceived enjoyment berpengaruh positif pada perceived ease of use; (H3) perceived enjoyment berpengaruh positif pada behavioral intention; (H7) perceived resources berpengaruh positif pada perceived ease of use; (H10) perceived ease of use berpengaruh positif pada perceived usefulness dan (H11) perceived ease of use berpengaruh positif pada behavioral intention. Saran untuk studi selanjutnya adalah (1) Melakukan generalisasi model pada konteks subjek dan objek penelitian yang berbeda, (2) Melakukan perluasan pada TAM (3) Melakukan pendekatan penelitian longitudinal, (4) Menambahkan variabel usage behavior atau actual behavior sebagai variabel prediktor, (5) Melakukan pretest pada sampel kecil sebelum disebar pada sampel besar. ABSTRACT This study extend Technology Acceptance Model (TAM) by enhancing three constructs or variables which are perceived enjoyment, compatibility and perceived resources. This study aims to find some critical factors at broadband internet context in Indonesia. This study uses non probability sampling with purposive sampling method through questionnaire. Sample are 197 bachelor students in economics faculty university of Sebelas Maret that have been used broadband internet access of Speedy. As for analysis that use in this study is Structural Equation Modeling (SEM) with estimation of Maximum Likelihood (ML) by AMOS version 4.01 program. Result of data shows that goodness-of-fit after modify is good. Following are the result of measurement model after modified: 2 = 169.412; probability = 0.065; RMSEA = 0.032; GFI = 0.920; AGFI = 0.883; CMIN / df = 1.185; TLI = 0.982; CFI = 0.987. From result of data and hypothesis analysis find that: (H1) perceived enjoyment have a positive effect on perceived usefulness; (H2) perceived enjoyment have a positive effect on perceived ease of use; (H3) perceived enjoyment have a positive effect on behavioral intention; (H7) perceived resources have a positive effect on perceived ease of use; (H10) perceived ease of use have a positive effect on perceived usefulness; (H11) perceived ease of use have a positive effect on behavioral intention. Some suggestion for the future study are (1) Doing generalization model at different context of research subject and object in larger area, (2) Doing more extension with TAM (3) Doing longitudinal approach research, (4) Enhancing usage behavior or actual behavior as a predictor variable, (5) Doing pretest in small sample first before disseminated at big sample.