Genetic Programming Approach for Classification Problem using GPU

Genetic programming (GP) is a machine learning technique that is based on the evolution of computer programs using a genetic algorithm. Genetic programming have proven to be a good technique for solving data set classification problems but at high computational cost. The objectives of this research is to accelerate the execution of the classification algorithms by proposing a general model of execution in GPU of the adjustment function of the individuals of the population. The computation times of each of the phases of the evolutionary process and the operation of the model of parallel programming in GPU were studied. Genetic programming is interesting to parallelize from the perspective of evolving a population of individuals in parallel

Genetic Programming Approach for Classification Problem using GPU

Genetic programming (GP) is a machine learning technique that is based on the evolution of computer programs using a genetic algorithm. Genetic programming have proven to be a good technique for solving data set classification problems but at high computational cost. The objectives of this research is to accelerate the execution of the classification algorithms by proposing a general model of execution in GPU of the adjustment function of the individuals of the population. The computation times of each of the phases of the evolutionary process and the operation of the model of parallel programming in GPU were studied. Genetic programming is interesting to parallelize from the perspective of evolving a population of individuals in paralle

Data Warehouse with Big Data Technology for Higher Education

Nowadays, data warehouse tools and technologies cannot handle the load and analytic process of data into meaningful information for top management. Big data technology should be implemented to extend the existing data warehouse solutions. Universities already collect vast amounts of data so the academic data of university has been growing significantly and become a big academic data. These datasets are rich and growing. University’s top-level management needs tools to produce information from the records. The generated information is expected to support the decision-making process of top-level management. This paper explores how big data technology could be implemented with data warehouse to support decision making process. In this framework, we propose Hadoop as big data analytic tools to be implemented for data ingestion/staging. The paper concludes by outlining future directions relating to the development and implementation of an institutional project on Big Data

Integration Between ERP Software and Business Intelligence in Odoo ERP: Case Study A Distribution Company

Odoo is an open-source ERP software. Odoo has advantage in price because it’s free. And from the functional side, Odoo has been equipped with more than 4500 modules, one of them is business intelligence (BI). BI is a solution and technique that helps company to understand about the business situation to make effective business decisions and meet their objectives. A study about the integration between Enterprise Resource Planning and BI in Odoo ERP will be explained in this paper. In the case study, we used sales data from a distribution compan

Predicting student performance in higher education using multi-regression models

Supporting the goal of higher education to produce graduation who will be a professional leader is a crucial. Most of universities implement intelligent information system (IIS) to support in achieving their vision and mission. One of the features of IIS is student performance prediction. By implementing data mining model in IIS, this feature could precisely predict the student� grade for their enrolled subjects. Moreover, it can recognize at-risk students and allow top educational management to take educative interventions in order to succeed academically. In this research, multi-regression model was proposed to build model for every student. In our model, Learning Management System (LMS) activity logs were computed. Based on the testing result on big students datasets, courses, and activities indicates that these models could improve the accuracy of prediction model by over 15%

Academic Decision Support System for Top Management

The ability to analyze and act on data is increasingly important to businesses, including in the education industry. Academic records of student of XYZ University which have been stored so far have not been used to generate some insights. XYZ University’s top-level management needs a tools to produce information from the records. The generated information is expected to support the decision-making process of top-level management. Effective business intelligence (BI) tools assist managers with decision making. BI tools provide decision-makers with the information that they need to make insightful decisions. Before starting the application development, analysis and design of the student academic records and the needs of Top-level management are done. The design stage produces a number of modeling that will be used to create the application. The final process of the development is an Academic Decision Support System application for XYZ University

Integration Between ERP Software and Business Intelligence in Odoo ERP: Case Study A Distribution Company

. Odoo is an open-source ERP software. Odoo has advantage in price because it’s free. And from the functional side, Odoo has been equipped with more than 4500 modules, one of them is business intelligence (BI). BI is a solution and technique that helps company to understand about the business situation to make effective business decisions and meet their objectives. A study about the integration between Enterprise Resource Planning and BI in Odoo ERP will be explained in this paper. In the case study, we used sales data from a distribution company

Data Warehouse with Big Data Technology for Higher Education

Nowadays, data warehouse tools and technologies cannot handle the load and analytic process of data into meaningful information for top management. Big data technology should be implemented to extend the existing data warehouse solutions. Universities already collect vast amounts of data so the academic data of university has been growing significantly and become a big academic data. These datasets are rich and growing. University�s top-level management needs tools to produce information from the records. The generated information is expected to support the decision-making process of top-level management. This paper explores how big data technology could be implemented with data warehouse to support decision making process. In this framework, we propose Hadoop as big data analytic tools to be implemented for data ingestion/staging. The paper concludes by outlining future directions relating to the development and implementation of an institutional project on Big Data