Pengembangan layanan sarana pendidikan online terutama website e-learning saat ini sangat diperlukan untuk menunjang aktivitas pembelajaran jarak jauh khususnya di lingkungan Perguruan Tinggi. Pembuatan website e-learning Perguruan Tinggi untuk memfasilitasi pembelajaran jarak jauh perlu diukur efektifitasnya sebagai bahan evaluasi. Tujuan dari penelitian menganalisa dan mengidentifikasikan kepuasan pengguna website e-learning MyBest dengan menggunakan metode webqual 4.0. Webqual merupakan salah satu metode pengukuran kualitas website berdasarkan persepsi pengguna akhir. Variabel yang digunakan dalam pengukuran menggunakan webqual 4.0. adalah kegunaan (usability) informasi (information), interaksi layanan (interaction service) dan kepuasan pengguna (user satisfaction). Kuesioner dalam penelitian ini disusun sesuai dengan indikator webqual 4.0 terdiri dari 23 pertanyaan dan terbagi dalam 4 dimensi berdasar variabel webqual. Berdasarkan hasil pengumpulan dan analisis data dalam penelitian ini, maka dapat disimpulkan bahwa keempat variabel webqual yaitu usability, information quality, dan service interaction quality dan variabel pelengkap user satisfaction pada web e-learning universitas berada pada kategori yang cukup tinggi dengan nilai kepuasan pada kategori puas.
- Elearning is now a necessity to support the implementation of learning in various educational institutions. End User Computing Satisfaction (EUCS) is a method used to measure the level of satisfaction of users of an application system by comparing expectations and reality of an information system. In this study 5 EUCS indicators were measured which would determine the level of Elearning user satisfaction, namely content, accuracy, shape, ease of use and timeliness. In the Delone And McLean Model there are six factors which are indicators, namely system quality, information quality, service quality, usage, user satisfaction, net benefits. Of the two methods will be measured how the level of elearning user satisfaction at Bina Sarana Informatics University. This study uses random samples collected through electronic questionnaires. There are several limitations in this study and further studies are needed so that the level of elearning user satisfaction can be described correctly. Keywords: elearning, eucs, endusercomputingsatisfaction, delonemclean
Abstrak: Elearning merupakan pembelajaran jarak jauh yang menggunakan teknologi komputer. Banyak platform digunakan dalam proses penyelenggaran elearning di berbagai jenjang pendidikan ini diantaranya yang paling banyak digunakan, group whatsapp, Google Classroom, Trelo, Zoom meeting, Duo, Google Meeting dan aplikasi pembelajaran online lainnya. Studi kasus dalam penelitian ini akan diambil dari pengguna Google Classroom di Indonesia khususnya dikalangan pendidikan tinggi. Penelitian ini bertujuan untuk mengetahui skala penerimaan elearning berbasis Google Classroom oleh pengguna elearning khususnya mahasiswa Universitas Bina Sarana Informatika. TAM merupakan adaptasi dari Theory of Reason (TRA). David memaparkan bahwa tujuan utama TAM adalah untuk memberikan dasar untuk penelusuran fakor eksternal terhadap kepercayaan, sikap dan tujuan pengguna. Terdapat 5 komponen yang akan diukur menggunakan Technology Acceptance Model. Dari beberapa komponen yang ada pada Technology Acceptance Model dapat disimpulkan bahwa dari segi Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Behavioral Intention to Use mendapatkan skala penerimaan yang cukup tinggi dalam penerimaan Teknologi Google Classroom. Sedangkan komponen Actual Use mendapatkankan skala penerimaan tertinggi di antara komponen lainnya Abstract: Elearning is distance learning using computer technology. Many platforms are used in the process of organizing elearning at various levels of education that are most widely used, whatsapp groups, Google Classroom, Trelo, Zoom meetings, Duos, Google Meetings and other online learning applications. Case studies in this study will be taken from Google Classroom users in Indonesia specifically among higher education. This study offers to determine the scale of Google-based class learning by eearning users specifically for Bina Sarana Informatika University students. TAM is an adaptation of Theory of Reason (TRA). David explained that the main purpose of TAM is to provide a basis for external factors guiding the user's beliefs, attitudes and goals. It is estimated that there are 5 components that will use the Acceptance Model Technology. From some of the components in the Technology Acceptance Model, it can be concluded in terms of Perceived Uses, Easy Use Perceptions, Attitudes Towards Use, Behavior Interested in Using, get a high enough acceptance scale in accepting Google Classroom Technology. While the Actual Use component receives the highest acceptance scale among other components.
Enterprise information system architecture has covered various fields, one of which is the pharmaceutical industry which has also changed significantly. Pharmaceutical companies and all business lines around the world are forced to reconsider their business priorities and strategies to deal with uncertainty, volatility and complexity. Where it will be handled in the presence of an integrated system. In this research the implementation of information system technology is carried out by implementing the TOGAF ADM framework that will help companies in architectural modeling starting from designing system architecture, business process architecture, drug sales information system architecture, technology architecture, several proposed architectural designs for business opportunities, and proposals system changes running. The result is that the enterprise modeling information system sales architecture to produce architectural blueprints can be done in six stages in the TOGAF ADM framework. Keywords: TOGAF, Sales, Pharmaceutical
Univariate data prediction has been done by many researchers with various methods used. The research was conducted using one method, several methods to combine several methods. This research uses several methods and simultaneously combines several methods. The method is by applying the Ensemble, namely Stacking. Meanwhile, the univariate data used is the Indonesian Sharia Bank Monthly Profit Data. This study aims to prove the accuracy of ensemble stacking prediction results by applying the SVM, Random Forest, Neural Network, and General Linear Model algorithms. Based on the results of the study, it was found that by applying Stacking the most accurate results were obtained for predicting univariate time series data (Indonesian Islamic Bank profits), where the RMSE generated was 0.534
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