Prediction of New Student Numbers using Least Square Method

Abstract

 STMIK BANJARBARU has acquired less number of new students for the last three years compared to the previous years. The numbers of new student acquisition are not always the same every year. The unstable number of new student acquisition made the difficulty in designing classes, lecturers, and other charges. Knowing the prediction number of new student acquisition for the coming period is very important as a basis for further decision making. Least Square method as the method of calculation to determine the scores prediction is often used to have a prediction, because the calculation is more accurate then moving average. The study was aimed to help the private colleges or universities, especially STMIK BANJARBARU, in predicting the number of new students who are accepted, so it will be easier to make decisions in determining the next steps and estimating the financial matters. The prediction of the number of new student acquisition will facilitates STMIK BANJARBARU to determine the number of classes, scheduling, etc. From the results of the study, it can be concluded that prediction analysis by using Least Square Method can be used to predict the number of new students acquisition for the coming period based on the student data in the previous years, because it produces valid results or closer to the truth. From the test results in the last 3 years, the validity shows 97.8%, so it can be said valid.

Authors and Affiliations

Dwi Mulyani

Keywords

Related Articles

An Interval-Based Context Reasoning Approach

Context-aware computing is an emerging computing paradigm that provides intelligent context-aware application. Context reasoning is an important aspect in context awareness, by which high level context can be derived fro...

Wearable Computing System with Input-Output Devices Based on Eye-Based Human Computer Interaction Allowing Location Based Web Services

Wearable computing with Input-Output devices Base on Eye-Based Human Computer Interaction: EBHCI which allows location based web services including navigation, location/attitude/health condition monitoring is proposed. T...

 A Multi_Agent Advisor System for Maximizing E-Learning of an E-Course

 Web-based learning environments have become popular in e-teaching throw WWW as a distance learning. There is an urgent need to enhance e-learning to be suitable to the level of learner knowledge. The presented pape...

 Preliminary Study on Phytoplankton Distribution Changes Monitoring for the Intensive Study Area of the Ariake Sea, Japan Based on Remote Sensing Satellite Data

 Phytoplankton distribution changes in the Ariake Sea areas, Japan based on remote sensing satellite data is studied. Through experiments with Terra and AQUA MODIS data derived chlorophyll-a concentration and suspen...

 Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules

 This research aims to calculate the execution time for software modules, using Particle Swarm Optimization (PSO) and Parallel Particle Swarm Optimization (PPSO), in order to calculate the proper time. A comparison...

Download PDF file
  • EP ID EP148750
  • DOI 10.14569/IJARAI.2015.041105
  • Views 125
  • Downloads 0

How To Cite

Dwi Mulyani (2015).  Prediction of New Student Numbers using Least Square Method. International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(11), 30-35. https://europub.co.uk/articles/-A-148750