MODEL PREDIKSI TRAFIK PEMAKAIAN WIFI (STUDI KASUS PADA WIFI.ID PT TELKOM)

In developing the new product would need a judgment on it. Consideration has been done by PT Telkom currently wifi.id in developing new products is through the level of internet usage is based on two things, namely the use of a home phone number and use flexi smartphones. Considerations based intern...

全面介紹

Saved in:
書目詳細資料
Main Authors: , DWI RIZKI SEPTIARI, , Nur Aini Masruroh, S.T., M.Sc., Ph.D.
格式: Theses and Dissertations NonPeerReviewed
出版: [Yogyakarta] : Universitas Gadjah Mada 2014
主題:
ETD
在線閱讀:https://repository.ugm.ac.id/131872/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=72381
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Universitas Gadjah Mada
實物特徵
總結:In developing the new product would need a judgment on it. Consideration has been done by PT Telkom currently wifi.id in developing new products is through the level of internet usage is based on two things, namely the use of a home phone number and use flexi smartphones. Considerations based internet usage 2 that, can not predict the use of technology in every province wifi.id. The problem faced by PT Telkom Internet usage today is far below the target. Making a prediction model is one way to evaluate the variables that affect the use wifi.id. Currently, PT Telkom needs a model that can determine the factors that affect the use of the internet. A study of the factors that may influence and use of predictive models appropriate to the wifi on a region required in order to reduce the gap between the target and actual use of the wifi in a province so that predictive models can be used as one alternative tools for companies in targeting the use of wifi in a region. In this study, the object of study is a national wifi.id users. This research will use the data to use wifi internet usage overall nationally. The study was conducted by making use of prediction models wifi.id. level The prediction model using the software Statistical Package for the Social Science 16.0. In this study using three considerations, namely linear regression model, quadratic, exponential, and a combination of all three. From the research conducted, it has been obtained based on the results of the correlation analysis of nine factors derived factors that significantly affect the rate of use of wifi is coming of promotional activity, percentage of use of existing wifi and Gross Domestic Product. With the best prediction model using a combination of regression R-square value of 84.9% (Cross Validation).