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All Journal Jurnal Ilmiah Farmasi Indonesian Journal of Pharmaceutical Science and Technology Jurnal Pendidikan Matematika RAFA Science and Technology Indonesia Jurnal Penelitian Sains BAREKENG: Jurnal Ilmu Matematika dan Terapan Sains Natural: Journal of Biology and Chemistry Ensiklopedia of Journal Jurnal Informatika Global Jurnal Abdimas Mandiri Babul Ilmi Jurnal Ilmiah Multi Science Kesehatan Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Ilmiah Bakti Farmasi JUARA: JURNAL WAHANA ABDIMAS SEJAHTERA Innovative: Journal Of Social Science Research Inovasi Gagasan Abdimas & Kuliah Kerja Nyata
Ensiwi Munarsih, Ensiwi
Sekolah Tinggi Ilmu Farmasi Bhakti Pertiwi Palembang
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Journal : Jurnal Informatika Global

 1 
Analisa Penerimaan Sistem Pembelajaran E-Learning Pada Masa Pandemic Menggunakan Structural Equation Model-Partial Least Square Ensiwi Munarsih; Agnes Rendowaty; Rini Yunita
Jurnal Informatika Global Vol 12, No 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v12i2.1941

Abstract

The Covid 19 pandemic has had a major influence on the order of human life at this time, including in the world of education. Teachers and educators as essential elements in teaching are required to undertake an unprecedented large-scale migration from traditional face-to-face education to online education or distance education. One of the learning systems used is the e-learning learning system. E-learning is a learning system that is carried out using electronic media. This research was conducted to test user acceptance of the e-learning learning system using the Technology Acceptance Model (TAM). TAM is an analytical model to determine user behavior regarding the acceptance of a technology Testing is done by measuring the influence between variables in the TAM model which includes the variables Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Behavioral Intention, and Actual Usage. Testing the influence of factors is carried out using the Structural Equation Model (SEM) - Partial Least Squares (PLS). Evaluation data is obtained from questionnaires distributed to users of the e-learning system. The results show that there is a direct influence between perceived usefulness and perceived ease of use on user behavioral attitudes which have implications for behavioral intentions to use technology (e-learning). This means that users of the e-learning system have the perception that the e-learning system is easy to use so that users can accept the e-learning system and continue to use it in their daily lives Keywords : e-learning, Technology Acceptance Model, Structural Equation Model, Partial Least Squares
Model Hybrid Menggunakan Dekomposisi-Neural Network Untuk Data Indeks Harga Saham Gabungan Imelda Saluza; Dewi Sartika; Ensiwi Munarsih
Jurnal Ilmiah Informatika Global Vol. 13 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v13i3.2696

Abstract

 The development of Covid-19 has worsened the economy not only nationally but also globally. Since its spread, the price movement of the Jakarta Composite Index (IHSG) has continued to be volatile. JCI price volatility shows risk and uncertainty in investing. Volatility is used as a barometer to determine portfolio management strategies for financial actors. Therefore, financial actors should find a strategy to be able to predict JCI price movements to reduce risks and gain profits. One way that can be done is to predict the JCI price as a reference in investing. This study uses a hybrid model between the decomposition model and the Neural Network (NN) in predicting JCI price volatility. The decomposition uses two approaches, namely additive and multiplicative, the two approaches will then be combined with NN and the NN algorithm used is Feed Forward Neural Network (FFNN) where the results of the decomposition in the form of seasonal, trend, and random data are used as input in the FFNN architecture. The FFNN architecture in this study differs from the hidden layer nodes and the epochs used. Furthermore, the prediction results from the model are compared with a single NN. The performance of each architecture will be measured using the Mean Absolute Error (MAE) and Mean Square Error (MSE). The results show that the hidden layer with more nodes can provide good performance while the epoch used provides good performance depending on the learning process carried out. The prediction results using the hybrid model can outperform the performance of a single NN.Keywords : time series, volatilitas, studi perbandingan, kecerdasan buatan, statistik.
Co-Authors Ade Arinia Rasyad Ahmad Fatoni Alfionita, Hafiza Amrullah, Hafizh Anggraini, Leriza Desitama Anggun ARIE FIRDIAWAN Bella Maharani Des Alwine Z Dini Aprilianti Duvadilan Wibowo, Viko Egata, Neisa Faradillah, Faradillah Fizmawati Hilma Hilma Hilma Hilma, Hilma Imelda Saluza, Imelda J, Tri Kurnia Rahayu. Jacky Kadek Asmadi Lasmaryna Sirumapea Lidia Lidia Maharani, Bella Martha, Septiani Mauizatul Hasanah Mauizatul Hasanah Mauizatul Hasanah, Mauizatul Noprizon Nurleni, Novi Nurlisa Hidayati Patmayuni, Dewi Pebyanti, Intan Puspa Rini Ratu Handayani Rendowaty, Agnes Reza Agung Sriwijaya Rini Isromarina Rini Yunita Romsiah Romsiah Romsiah Romsiah Rosanta Sihombing, Esra Sartika, Dewi Tetty Aisyah Veriza` Aprilita Vika Natasia Rahajeng Yeyen Anggraini Yopi Rikmasari, Yopi Yuli Andriani