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Trend Analysis Comparison of Forecasts For New Student

Yulia Yudihartanti1

Section:Research Paper, Product Type: Journal Paper
Volume-4 , Issue-4 , Page no. 145-148, Apr-2016

Online published on Apr 27, 2016

Copyright © Yulia Yudihartanti . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Yulia Yudihartanti, “Trend Analysis Comparison of Forecasts For New Student,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.145-148, 2016.

MLA Style Citation: Yulia Yudihartanti "Trend Analysis Comparison of Forecasts For New Student." International Journal of Computer Sciences and Engineering 4.4 (2016): 145-148.

APA Style Citation: Yulia Yudihartanti, (2016). Trend Analysis Comparison of Forecasts For New Student. International Journal of Computer Sciences and Engineering, 4(4), 145-148.

BibTex Style Citation:
@article{Yudihartanti_2016,
author = {Yulia Yudihartanti},
title = {Trend Analysis Comparison of Forecasts For New Student},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2016},
volume = {4},
Issue = {4},
month = {4},
year = {2016},
issn = {2347-2693},
pages = {145-148},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=876},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=876
TI - Trend Analysis Comparison of Forecasts For New Student
T2 - International Journal of Computer Sciences and Engineering
AU - Yulia Yudihartanti
PY - 2016
DA - 2016/04/27
PB - IJCSE, Indore, INDIA
SP - 145-148
IS - 4
VL - 4
SN - 2347-2693
ER -

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Abstract

The number of new students who register annually less stable, increasing and decreasing. This has caused difficulties in the adjustment including adjustment of the number of classrooms and lecturers that will impact on the ratio of lecturers. Thus the need to do forecasting or prediction of the number of new students each year. To get the most precise predictions in this study used four methods on Trend Analysis namely methods of semi on average, the least squares method, the method of quadratic trend, exponential trend method, which will be compared to determine the method with the smallest error rate.

Key-Words / Index Term

Prediction; Forecast; Comparison; Trend Analysis

References

[1] Santoso, B., “Comparative Analysis of Algorithms Naïve Bayes and C4.5 for Prediction Student Registration at the Dian Nuswantoro University”, Department of Computer Science, Journal of Dian Nuswantoro University, Page No. (1-4), 2015.
[2] Rahanimi, “Forecasting Number of Students Apply search was interest and ability of the Department of Mathematics Automatic Clustering Method Using Fuzzy Logic And Relationships (Case Study at the Institute of Technology Surabaya)”, ITS Undergraduate Paper 13455, Page No. (1-3), Dec 2013.
[3] Abdullah, M. F., “Methods of Use Automatic Clustering and Fuzzy Logical Relationship To Predict Number of New Students Bogor Agricultural Institute”, Departement of Mathematics dan Natural Science Bogor Agricultural Institute, Bogor, 2015.
[4] Arpit Baheti and Durga Toshniwal, “Trend Analysis of Time Series Data Using Data Mining Techniques”, IEEE International Congress on Big Data, 2014, pp.430-437.
[5] Suharyadi, and Purwanto, “Statistics: For Economics & Finance Modern Book 1”, Four Salemba Publisher, First Edition-2003, ISBN: 979-691-162-0.