Prediction of New Student Numbers using Least Square Method
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2015, Vol 4, Issue 11
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
Method for Vigor Diagnosis of Tea Trees based on Nitrogen Content in Tealeaves Relating to NDVI
Method for vigor diagnosis of tea trees based on nitrogen content in tealeaves relating to NDVI is proposed. In the proposed method, NIR camera images of tealeaves are used for estimation of nitrogen content in tea...
Design and Implementation of Rough Set Algorithms on FPGA: A Survey
Rough set theory, developed by Z. Pawlak, is a powerful soft computing tool for extracting meaningful patterns from vague, imprecise, inconsistent and large chunk of data. It classifies the given knowledge base app...
Outlier-Tolerance RML Identification of Parameters in CAR Model
The measured data inevitably contain abnormal data under the normal operating conditions. Most of the existing algorithms, such as least squares identification and maximum likelihood estimation, are easily affected...
A Registration Method for Multimodal Medical Images Using Contours Mutual Information
In recent years, mutual information has developed as a popular image registration measure especially in multimodality image registration. For different modality medical images, the contour of tissues or organs is s...
Method for 3D Object Reconstruction Using Several Portion of 2D Images from the Different Aspects Acquired with Image Scopes Included in the Fiber Retractor
Method for 3D object reconstruction using several portions of 2D images from the different aspects which are acquired with image scopes included in the fiber retractor is proposed. Experimental results show a great possi...