Browsing by Author "Yusuf- Asaju, Ayisat Wuraola"

Now showing 1 - 6 of 6
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    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, Azman
    The 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’ satisfaction
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    Mobile Network Quality of Experience using Big Data Analytics Approach
    (2017) Yusuf- Asaju, Ayisat Wuraola; Dahalin, Zulkhairi Md; Ta’a, Azman
    Traditionally, 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.
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    On the relationship between Human Immunology and Computer Immunology.
    (IEEE Computer Nigeria Chapter, 2016) Yusuf- Asaju, Ayisat Wuraola; Salau- Ibrahim, Taofeeqoh Tosin; Jimoh, Rasheed Gbenga
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    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, Azman
    Subjective 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 eliminated
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    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, Azman
    In 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
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    ROLES OF BIG DATA ANALYTICS IN NIGERIAN TELECOMMUNICATIONS INDUSTRY: A CONCEPTUAL EXPLORATION
    (Computer Science & Engineering Department, Obafemi Awolowo University, Ile Ife., 2017) Yusuf- Asaju, Ayisat Wuraola; Salau- Ibrahim, Taofeeqoh Tosin; Salihu, Shakirat A
    Nigerian telecoms industry has witnessed a rapid growth in the last two decades. The growth has contributed to the economic-social growth and development of the country. In fact, Nigerian telecoms industry is presently referred to as the fastest growing industry in Africa. However, the growth does not come without the difficulties of inadequate quality of service and customer dissatisfaction with the mobile network services. These challenges has caused an increase in customer churn and attrition rate. Therefore, this study conducted a Critical review on previous studies to highlights the challenges facing the Nigerian telecoms industry. This study observed the main challenges facing the Nigerian telecoms industry are weak infrastructure, improper management of customer expectations, damages of network infrastructures and inadequate power supply. Based on the stated challenges, this study proposed the use of big data analytics that can be used by the MNOs to ensure adequate management of mobile network performance. The study envisaged that the use of big data analytics in Nigerian telecoms industry will enable the mobile network operators to understand the deterioration in the network traffic, kind of resources utilised, where the future traffic problems may occur and plan on how to efficiently reallocate infrastructural mobile network resources.