Browsing by Author "Dahalin, Zulkhairi Md"
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Item EXPLORATORY ANALYSIS OF MOBILE NETWORK TRAFFIC DATA: A CASE OF A MAJOR MOBILE NETWORK OPERATOR IN NIGERIA(E- Academia Journal, 2017-11-30) Yusuf- Asaju, Ayisat Wuraola; Dahalin, Zulkhairi Md; Ta’a, AzmanThe most effective and common method of assessing mobile network operator’s (MNO) performance is through customer perception, usually gathered using mail, telephone, or internet-based surveys. However, previous studies have observed that the percentage of responses received from customers are extremely low, because customers do not return and complete the surveys at the stipulated time. To overcome the surveys’ drawbacks, recent studies suggested the use of customer experience data obtained from the mobile network traffic. Therefore, this article explores the data collected from a major mobile network operator in Nigeria to determine whether the variables constituted in the dataset can be used in future to evaluate mobile network operator’s performance. The dataset (data tariff, customer complaints and network quality (uplink and downlink throughput) used in this article was gathered from mobile network traffic. The study examined the gathered dataset in R Programming and the result shows that there is a relationship between data tariff and number of internet subscribers, as well as uplink and downlink throughput, which represents the network quality. Overall, the results from the study suggests the dataset can be used to evaluate the MNOs internet service performance to determine mobile internet customers’ satisfactionItem FRAMEWORK FOR MODELLING MOBILE NETWORK QUALITY OF EXPERIENCE THROUGH BIG DATA ANALYTICS APPROACH(Journal of Information and Communication Technology (JICT), 2018) Yusuf-Asaju, Ayisat Wuraola; Dahalin, Zulkhairi Md; Ta’a, AzmanThe increase in the usage of different mobile internet applications can cause deterioration in the mobile network performance. Such deterioration often declines the performance of the mobile network services that can influence the mobile Internet user’s experience, which can make the internet users switch between different mobile network operators to get good user experience. In this case, the success of mobile network operators primarily depends on the ability to ensure good quality of experience (QoE), which is a measure of users’ perceived quality of mobile Internet service. Traditionally, QoE is usually examined in laboratory experiments to enable a fixed contextual factor among the participants even though the results derived from these laboratory experiments presented an estimated mean opinion score representing perceived QoE. The use of user experience dataset involving time and location gathered from the mobile network traffic for modelling perceived QoE is still limited in the literature. The mobile Internet user experience dataset involving the time and location constituted in the mobile network can be used by the mobile network operators to make data-driven decisions to deal with disruptions observed in the network performance and provide an optimal solution based on the insights derived from the user experience data. Therefore, this paper proposed a framework for modelling mobile network QoE using the big data analytics approach. The proposed framework describes the process of estimating or predicting perceived QoE based on the datasets obtained or gathered from the mobile network to enable the mobile network operators effectively to manage the network performance and provide the users a satisfactory mobile Internet QoE.Item Mobile Network Quality of Experience using Big Data Analytics Approach(2017) Yusuf- Asaju, Ayisat Wuraola; Dahalin, Zulkhairi Md; Ta’a, AzmanTraditionally, Quality of experience is mostly examined in a laboratory experiments to enable a fixed contextual factor. While the results present an estimated mean opinion score representing perceived QoE. It is imperative to estimate mean opinion score employing large data (big data) gathered from the mobile network comprising of different user’s location and time for a specific service. Because time and location can have a huge influence on the user perceived quality of experience. Therefore, this paper proposed a framework for modelling perceived QoE through big data analytics. The proposed framework describes the process of estimating perceived quality of experience to assist the mobile network operators effectively manage the network performance and aid satisfactory provision of mobile internet services.Item A Proposed Analytical Customer Satisfaction Prediction Model for Mobile Internet Networks(Association for Information Systems AIS Electronic Library (AISeL), 2017) Yusuf- Asaju, Ayisat Wuraola; Dahalin, Zulkhairi Md; Ta’a, AzmanSubjective method (such as survey, interview, etc.) has been the most common and reliable method used in analyzing customer satisfaction. However, the subjective method is expensive, time consuming, lacks repeatability in real-time and may not capture the technical aspect of the telecoms network service performance in telecommunication industry. As a result, perceived quality of experience (QoE) has been traditionally used to evaluate the satisfaction of telecommunication services from both Internet service providers and customer’s perspective. However, the result of perceived QoE in relation to mean opinion score found not suitable enough to quantify customer satisfaction, and it eliminates the diversity of customer assessment while quantifying satisfaction. Therefore, this paper proposed an analytical customer satisfaction prediction model based on perceived QoE, perceived QoE influence factors, perceived QoE measurements and perceived QoE estimations to overcome the limitations of the subjective measurement. The paper presents how the mean opinion score can be used to quantify customer satisfaction by ensuring the diversity of customer’s assessment is not eliminatedItem A Proposed Framework for Mobile Internet QoS Customer Satisfaction Using Big Data Analytics Techniques(School of Computing, Universiti Utara Malaysia. Malaysia, 2016) Yusuf- Asaju, Ayisat Wuraola; Dahalin, Zulkhairi Md; Ta’a, AzmanIn the past few years, the Nigeria telecommunication industry has experienced tremendous growth and changes to the extent that customers find it much easier to access the internet through their mobile phones. However, the growth in mobile telecoms subscribers comes with challenges of quality of service, which lead to fluctuations in customer satisfaction. Therefore, the present study proposed a customer satisfaction prediction model through the Key performance indicators obtained from the objective measurement of the network traffic using extended and exhaustive study of the literature. The proposed framework would guide mobile network operators on strategies to embark on in order to retain their customers within the network