Metode Peramalan Permintaan Jasa Penerjemahan Bahasa Asing Dengan Algorithma Linear Regression, Menggunakan Rapidminer. Studi Kasus : Azzam Translator Bekasi

Authors

  • Warsino Warsino

DOI:

https://doi.org/10.37150/jsa.v7i2.657

Keywords:

data mining, forecasting, translation, linear regression, rapidminer

Abstract

Along with the world’s business progress nowadays, business
relationships between countries are no longer limited by territory. This
provides an economical value for those who carefully see the chances.
One of the chances is foreign language translation business. As any
other businesses, a foreign language translation business should face some problems. One of the causes of the problems is: a foreign language
translation company cannot predict the volumes of orders of coming
years, which make them should employ translators on a part-time basis.
As a result, the company frequently losses chances to obtain big orders.
For that reason, it is required a method to assist the company in
predicting the volumes of sales. Linear Regression is one of the methods
by using data mining that has the capability to predict the datasets of
previous years. By using the Linear Regression method and a tool named
Rapidminer 8.1, a research successfully proves that a volume of
translation order can be promptly acknowledged, seen from the RMSE
(Root Mean Square Error) score at the amount of 0.823.

Downloads

Published

2017-12-22

Issue

Vol. 7 No. 2 (2017): SANTIKA

Section

Articles

License

Authors who publish articles in SANTIKA Journal is a scientific journal  agree to the following terms:

  1. Authors retain copyright of the article and grant the journal right of first publication with the work simultaneously licensed under a CC-BY-SA or The Creative Commons Attribution–ShareAlike License.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Abstract viewed = 104 times