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All Journal Journal of Computing Theories and Applications Journal of Fuzzy Systems and Control (JFSC)
Emordi, Frances Uche
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering

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Journal : Journal of Computing Theories and Applications

 1 
Forging a User-Trust Memetic Modular Neural Network Card Fraud Detection Ensemble: A Pilot Study Ojugo, Arnold Adimabua; Akazue, Maureen Ifeanyi; Ejeh, Patrick Ogholuwarami; Ashioba, Nwanze Chukwudi; Odiakaose, Christopher Chukwufunaya; Ako, Rita Erhovwo; Emordi, Frances Uche
Journal of Computing Theories and Applications Vol. 1 No. 2 (2023): JCTA 1(2) 2023
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jcta.v1i2.9259

Abstract

The advent of the Internet as an effective means for resource sharing has consequently, led to proliferation of adversaries, with unauthorized access to network resources. Adversaries achieved fraudulent activities via carefully crafted attacks of large magnitude targeted at personal gains and rewards. With the cost of over $1.3Trillion lost globally to financial crimes and the rise in such fraudulent activities vis the use of credit-cards, financial institutions and major stakeholders must begin to explore and exploit better and improved means to secure client data and funds. Banks and financial services must harness the creative mode rendered by machine learning schemes to help effectively manage such fraud attacks and threats. We propose HyGAMoNNE – a hybrid modular genetic algorithm trained neural network ensemble to detect fraud activities. The hybrid, equipped with knowledge to altruistically detect fraud on credit card transactions. Results show that the hybrid effectively differentiates, the benign class attacks/threats from genuine credit card transaction(s) with model accuracy of 92%.
CoSoGMIR: A Social Graph Contagion Diffusion Framework using the Movement-Interaction-Return Technique Ojugo, Arnold Adimabua; Ejeh, Patrick Ogholuwarami; Akazue, Maureen Ifeanyi; Ashioba, Nwanze Chukwudi; Odiakaose, Christopher Chukwufunaya; Ako, Rita Erhovwo; Nwozor, Blessing; Emordi, Frances Uche
Journal of Computing Theories and Applications Vol. 1 No. 2 (2023): JCTA 1(2) 2023
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jcta.v1i2.9355

Abstract

Besides the inherent benefits of exchanging information and interactions between nodes on a social graph, they can also become a means for the propagation of knowledge. Social graphs have also become a veritable structure for the spread of disease outbreaks. These and its set of protocols are deployed as measures to curb its widespread effects as it has also left network experts puzzled. The recent lessons from the COVID-19 pandemic continue to reiterate that diseases will always be around. Nodal exposure, adoption/diffusion of disease(s) among interacting nodes vis-a-vis migration of nodes that cause further spread of contagion (concerning COVID-19 and other epidemics) has continued to leave experts bewildered towards rejigging set protocols. We model COVID-19 as a Markovian process with node targeting, propagation and recovery using migration-interaction as a threshold feat on a social graph. The migration-interaction design seeks to provision the graph with minimization and block of targeted diffusion of the contagion using seedset(s) nodes with a susceptible-infect policy. The study results showed that migration and interaction of nodes via the mobility approach have become an imperative factor that must be added when modeling the propagation of contagion or epidemics.
Effects of Data Resampling on Predicting Customer Churn via a Comparative Tree-based Random Forest and XGBoost Ako, Rita Erhovwo; Aghware, Fidelis Obukohwo; Okpor, Margaret Dumebi; Akazue, Maureen Ifeanyi; Yoro, Rume Elizabeth; Ojugo, Arnold Adimabua; Setiadi, De Rosal Ignatius Moses; Odiakaose, Chris Chukwufunaya; Abere, Reuben Akporube; Emordi, Frances Uche; Geteloma, Victor Ochuko; Ejeh, Patrick Ogholuwarami
Journal of Computing Theories and Applications Vol. 2 No. 1 (2024): JCTA 2(1) 2024
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.10562

Abstract

Customer attrition has become the focus of many businesses today – since the online market space has continued to proffer customers, various choices and alternatives to goods, services, and products for their monies. Businesses must seek to improve value, meet customers' teething demands/needs, enhance their strategies toward customer retention, and better monetize. The study compares the effects of data resampling schemes on predicting customer churn for both Random Forest (RF) and XGBoost ensembles. Data resampling schemes used include: (a) default mode, (b) random-under-sampling RUS, (c) synthetic minority oversampling technique (SMOTE), and (d) SMOTE-edited nearest neighbor (SMOTEEN). Both tree-based ensembles were constructed and trained to assess how well they performed with the chi-square feature selection mode. The result shows that RF achieved F1 0.9898, Accuracy 0.9973, Precision 0.9457, and Recall 0.9698 for the default, RUS, SMOTE, and SMOTEEN resampling, respectively. Xgboost outperformed Random Forest with F1 0.9945, Accuracy 0.9984, Precision 0.9616, and Recall 0.9890 for the default, RUS, SMOTE, and SMOTEEN, respectively. Studies support that the use of SMOTEEN resampling outperforms other schemes; while, it attributed XGBoost enhanced performance to hyper-parameter tuning of its decision trees. Retention strategies of recency-frequency-monetization were used and have been found to curb churn and improve monetization policies that will place business managers ahead of the curve of churning by customers.
Co-Authors Abere, Reuben Akporube Agboi, Joy Aghaunor, Tabitha Chukwudi Aghware, Fidelis Obukohwo Akazue, Maureen Ifeanyi Ako, Rita Erhovwo Ashioba, Nwanze Chukwudi Binitie, Amaka Patience De Rosal Ignatius Moses Setiadi Eboka, Andrew Okonji Ejeh, Patrick Ogholuwarami Ezzeh, Peace Oguguo Geteloma, Victor Ochuko Idama, Rebecca Okeoghene Jumbo, Evans Fubara Nwozor, Blessing Nwozor, Blessing Uche Odiakaose, Chris Chukwufunaya Odiakaose, Christopher Chukwufunaya Odoh, Anne Ojugo, Arnold Adimabua Okpor, Margaret Dumebi Onochie, Christopher Chukwudi Onoma, Paul Avwerosuoghene Oweimieotu, Amanda Enaodona Ugbotu, Eferhire Valentine Yoro, Rume Elizabeth