The Experts below are selected from a list of 16647 Experts worldwide ranked by ideXlab platform
Anna Liu - One of the best experts on this subject based on the ideXlab platform.
-
empirical prediction models for adaptive resource provisioning in the cloud
Future Generation Computer Systems, 2012Co-Authors: Sadeka Islam, Jacky Keung, Kevin Lee, Anna LiuAbstract:Cloud computing allows dynamic resource scaling for enterprise Online Transaction systems, one of the key characteristics that differentiates the cloud from the traditional computing paradigm. However, initializing a new virtual instance in a cloud is not instantaneous; cloud hosting platforms introduce several minutes delay in the hardware resource allocation. In this paper, we develop prediction-based resource measurement and provisioning strategies using Neural Network and Linear Regression to satisfy upcoming resource demands. Experimental results demonstrate that the proposed technique offers more adaptive resource management for applications hosted in the cloud environment, an important mechanism to achieve on-demand resource allocation in the cloud.
Faihaputri Nabilla - One of the best experts on this subject based on the ideXlab platform.
-
PENGARUH KEPERCAYAAN, KEAMANAN, DAN KEMUDAHAN PENGGUNAAN APLIKASI TERHADAP MINAT BELI ULANG (STUDI KASUS DI E-COMMERCE JD.ID)
'STIE AAS Surakarta', 2021Co-Authors: Saripudin Saripudin, Faihaputri NabillaAbstract:The use of the internet not only for communication and finding information, but also for Online Transaction. One of e-commerce that is developing in Indonesia is JD.id. However, Indonesian people's interest in JD.id is still relatively low, where in Q2 2020 JD.id was ranked sixth, which means JD.id is still not the main choice of Indonesian people in using e-commerce. The purpose of this study is to find out and analyze how much effect of trust, security and ease of use of the application have on repurchase interest in JD.id. The sample in this study were 100 consumers who had used JD.id determined by purposive sampling technique. This research is a quantitative research with survey method, where this research is causal associative. The method of data collection in this research is using the method of distributing questionnaires through social media. The data analysis technique used in this research is path analysis using the SmartPLS 3.0 program. The results of the study found that trust, security and ease of use of the application partially and simultaneously had a significant positive effect on repurchase interest in JD.ID
Heriyanto Yayak - One of the best experts on this subject based on the ideXlab platform.
-
PENGARUH KEPERCAYAAN KONSUMEN DAN KEMUDAHAN PENGGUNAAN APLIKASI TERHADAP KEPUTUSAN PEMBELIAN PADA Online SHOP SHOPEE (Studi Kasus pada Mahasiswa Ilmu Administrasi Bisnis Institut Ilmu Sosial dan Manajemen STIAMI di Jakarta)
JAMBIS : Jurnal Administrasi Bisnis, 2021Co-Authors: Aisyah Aisyah, Heriyanto YayakAbstract:This thesis used a quantitative study on the influence of consumer trust and easiness to use an application on purchasing decision in shoppee Online shop to Students of Business Administration Science of Social and Management Science of STIAMI in Jakarta. In this study, multiple linear regression analysis using f and t tests was used. Samples were determined using purposive sampling technique. The amount of sample in this study was 53 students based on Online Transaction activities via shopee Online shop. This study used two variables, namely dependent and independent variables. The dependent variable is purchasing decision, while the independent variable includes Consumer Trust (X1) and Easiness to Use an Application (X2). The result of simultaneous regression coefficient testing was that Fcal of 24.029 Ftable of 3.18, thus the consument trust and easiness to use an application simultaneously influenced the purchasing decision. In partial t test statitistic testing was obtained consumer trust variable of Fcal of 6.860 and easiness to use an application variable Ftable of 1.675, which means each independent variable influences the dependent variable partially.s
Biswajit Purkayastha - One of the best experts on this subject based on the ideXlab platform.
-
a cost sensitive weighted random forest technique for credit card fraud detection
International Conference on Computing Communication and Networking Technologies, 2019Co-Authors: Debashree Devi, Saroj Kr Biswas, Biswajit PurkayasthaAbstract:The act of fraudulent credit card Transaction has been increased over the past recent years, as the era of digitization hits our day-to-day life, with people are getting more involved in Online banking and Online Transaction system. Machine learning algorithms have played a significant role in detection of credit card frauds. However, the unbalanced nature of the real-life datasets causes the traditional classification algorithms to perform low in detection of credit card fraud. In this work, a cost-sensitive weighted random forest algorithm has been proposed for effective credit card fraud detection. A cost-function has been defined in the training phase of each tree, in bagging which emphasizes to assign more weight to the minority instances during training. The trees are ranked according to their predictive ability of the minority class instances. The proposed work has been compared with two existing random-forest based techniques for two binary credit card datasets. The efficiency of the model has been evaluated in terms G-mean, F-measure and AUC values. The experimental results have established the proficiency of the proposed model, than the existing ones.
Anja Bog - One of the best experts on this subject based on the ideXlab platform.
-
benchmarking Transaction and analytical processing systems the creation of a mixed workload benchmark and its application
2013Co-Authors: Anja BogAbstract:Systems for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are currently separate. The potential of the latest technologies and changes in operational and analytical applications over the last decade have given rise to the unification of these systems, which can be of benefit for both workloads. Research and industry have reacted and prototypes of hybrid database systems are now appearing. Benchmarks are the standard method for evaluating, comparing and supporting the development of new database systems. Because of the separation of OLTP and OLAP systems, existing benchmarks are only focused on one or the other. With the rise of hybrid database systems, benchmarks to assess these systems will be needed as well. Based on the examination of existing benchmarks, a new benchmark for hybrid database systems is introduced in this book. It is furthermore used to determine the effect of adding OLAP to an OLTP workload and is applied to analyze the impact of typically used optimizations in the historically separate OLTP and OLAP domains in mixed-workload scenarios.
-
normalization in a mixed oltp and olap workload scenario
TPC Technology Conference, 2011Co-Authors: Anja Bog, Alexander Zeier, Kai Sachs, Hasso PlattnerAbstract:The historically introduced separation of Online analytical processing (OLAP) from Online Transaction processing (OLTP) is in question considering the current developments of databases. Column-oriented databases mainly used in the OLAP environment so far, with the addition of in-memory data storage are adapted to accommodate OLTP as well, thus paving the way for mixed OLTP and OLAP processing. To assess mixed workload systems benchmarking has to evolve along with the database technology. Especially in mixed workload scenarios the question arises of how to layout the database. In this paper, we present a case study on the impact of database design focusing on normalization with respect to various workload mixes and database implementations. We use a novel benchmark methodology that provides mixed OLTP and OLAP workloads based on a real scenario.
-
a composite benchmark for Online Transaction processing and operational reporting
2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises (AMIGE), 2008Co-Authors: Anja Bog, Jens Kruger, Jan SchaffnerAbstract:Up-to-date data is of immense importance for operational reporting. Global enterprises require such a high throughput during daily operations that reporting systems had to be separated from the Transactional system to avoid inhibiting performance. These architectures, however, do not provide the required reporting flexibility as the data set is a pre-defined subset of the actual data and updated only at certain time intervals, e.g. nightly. The composite benchmark for Online Transaction processing (OLTP) and operational reporting, henceforth CBTR, provides means to evaluate the performance of enterprise systems for a mixed workload of OLTP and operational reporting queries. Such a system offers up-to-date information and the flexibility of the entire data set for reporting. CBTR provokes the conflicts that were the reason for separating the two workloads on different systems. In this paper we introduce the concepts of CBTR, which is based on the original data set and real workloads of an existing, globally operating enterprise.
