Penelitian ini bertujuan untuk mengetahui pengaruh Word of Mouth mengenai live streaming TikTok shop terhadap keputusan pembelian konsumen. Teknik analisis data yang digunakan dalam penelitian ini adalah statistik inferensial parametrik. Pengujian hipotesis menggunakan uji signifikansi dengan penetapan hipotesis nol (Ho) dan hipotesis alternative (Ha). Penelitian ini bersifat kuantitatif dengan metode pengumpulan data dilakukan melalui penyebaran kuisioner online berupa link google form melalui media sosial Whatsapp. Sampel dalam penelitian ini menggunakan dengan rumus Slovin maka diperoleh jumlah sampel sebanyak 68 responden mahasiswa Prodi Ilmu Komunikasi Universitas Muhammadiyah Cirebon yang mempunyai akun TikTok. Hasil penelitian menunjukkan bahwa word of mouth (X) berpengaruh signifikan terhadap live streaming TikTok shop (Z) R square sebesar 0,485 yang berarti 48,5%. Diperoleh nilai t hitung 7,891 ˃ t tabel 1.699 dengan nilai signifikansi 0,000 ˂ 0,005. Fitur live streaming TikTok shop (Z) berpengaruh signifikan terhadap keputusan pembelian (Y) R square sebesar 0,676 berarti 67,6%. Diperoleh t hitung sebesar 11,732 ˃ t tabel sebesar 1.699 dengan nilai signifikan 0,000 ˂ 0,005. word of mouth (X) terhadap keputusan pembelian (Y) R square adalah 0,505 atau 50,5%. diperoleh t hitung sebesar 8,205 ˃ t tabel sebesar 1.699 dengan nilai signifikan 0,000 ˂ 0,005. Word of mouth (X) mengenai live streaming TikTok shop (Z) terhadap keputusan pembelian (Y) R square adalah sebesar 0,713 yang berarti 71,3%. Maka dapat disimpulkan bahwa hubungan yang sebenarnya adalah tidak langsung sebesar 0,443. Seluruh hipotesis Ho ditolak dan Ha diterima.
Liu-Type Regression (LTR) is one of the statistical methods to overcome multicollinearity in multiple regression models. LTR is the development of Ridge regression and Liu estimator. When there is a strong collinearity, selected k parameter in the ridge regression does not fully overcome the multicollinearity. This study aimed to estimate the rainfall data in Pangkep Regency (as response variable) with LTR approach on Statistical Downscaling (SD) models. Precipitation (as predictor variables) is the result of a simulation of a grid on the Global Circulation Model (GCM). This study uses a size 8 8 grid of GCM (64 predictor variables) over an area of Pangkep Regency so that there is a high multicollinearity. Three dummy variables were determined from k-means cluster technique used as predictor variables to overcome the heterogeneity of residual variance. LTR model with dummy variables are able to explain the diversity of rainfall data properly. The value of R2 produced ranges 85.23% -88.99% with Root Mean Square Error (RMSE) ranges 117.732-136.377. Validation of the model generates a high correlation value between the actual rainfall and alleged rainfall period of 2017 (about 0.977-0.979). The value of Root Mean Square Error Prediction (RMSEP) produced lower (about 57.625-61.120). SD analysis was also performed with and without the dummy variable in the Ridge regression and LTR. In general, LRT models with dummy (k = 0.652, d = -0.799) is the best model based on the value of R2, RMSE, correlation, and RMSEP.
The primary abilities of physics students at the University of Muhammadiyah Makassar against the scientific concepts learned at the secondary school level vary, resulting in a complex integrated science learning process. The university follows the conventional methods of learning science with little or no use of modern technology. Thus, the present study was conducted to develop interactive multimedia learning using the Macromedia Flash program on integrated science content. The research consisted of two stages. While the first stage included the identification and content analysis of integrated science materials, the second stage comprised designing interactive multimedia learning and testing its validity. Validation was carried out on seven participants and analyzed using the Aiken validation. The validation results showed that the interactive multimedia developed is valid and can be used in Integrated Science lectures. Keywords: interactive multimedia, integrated science, media development
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