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Buletin Teknik Elektro dan Informatika
Article . 2022 . Peer-reviewed
License: CC BY SA
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Article . 2022
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Prediction of internet user satisfaction levels in Bangladesh using data mining and analysis of influential factors

Authors: Md. Hasan Imam Bijoy; Sumiya Alam Akhi; Md. Ali Ashraf Nayeem; Md. Mahbubur Rahman; Md. Jueal Mia;

Prediction of internet user satisfaction levels in Bangladesh using data mining and analysis of influential factors

Abstract

Today the world has already acknowledged as a global village by the inter-net which has technologically evolved into a significant performance instrument for individuals, businesses, and countries seeking to achieve betterment. This study is based on data mining techniques to predict the satisfaction level of internet users from the context of Bangladesh. After conducting a public survey with 18 questions, we were able to acquire 451 responses from participants. Data for user satisfaction was associated with end-user characteristics including certain getting high speed, internet packages, cable type of Wi-Fi connection with targeting various age groups and occupations. The research's most key conceptual breakthrough was the reliability of magnitude predictions of user satisfaction level based on their experience with internet use. The empirical findings indicate that people in Bangladesh have high expectations in existing internet technology, and they are very dissatisfied with their facilities of internet use and to measure satisfaction level related with monthly limit of the Wi-Fi packages and the elements affecting internet speed. Several classifier models were applied to our dataset and among them, Random Forest (RF) performance reaches the top position with 91.53% accuracy.

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Keywords

Bangladesh, Internet, User satisfaction level, Internet users, Data mining

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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