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Menampilkan 1–5 dari 5 artikel
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)
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 ense...
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IMANoBAS: An Improved Multi-Mode Alert Notification IoT-based Anti-Burglar Defense System
Omede, Edith Ugochi
; Edje, Abel E
; Akazue, Maureen Ifeanyi
; Utomwen, Henry
; Ojugo, Arnold Adimabua
Journal of Computing Theories and Applications
Vol 1
, No 3
(2024)
Burglary involves forced or unauthorized entry, which leads to damage or loss of property having monetary or emotional value and, more severely, puts lives at risk. The dire need for the safety of lives and properties has attracted so much research on burglary alert system using Internet of Things (IoT) technology. Most of the research focused on alerting the users of burglary attempts using any or a combination of two notification methods: SMS, call, and email. This study emphasizes three-mode...
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22 Sitasi
UNMASKING FRAUDSTERS: Ensemble Features Selection to Enhance Random Forest Fraud Detection
Akazue, Maureen Ifeanyi
; Debekeme, Irene Alamarefa
; Edje, Abel Efe
; Asuai, Clive
; Osame, Ufuoma John
Journal of Computing Theories and Applications
Vol 1
, No 2
(2023)
Fraud detection is used in various industries, including banking institutes, finance, insurance, government agencies, etc. Recent increases in the number of fraud attempts make fraud detection crucial for safeguarding financial information that is confidential or personal. Many types of fraud problems exist, including card-not-present fraud, fake Marchant, counterfeit checks, stolen credit cards, and others. An ensemble feature selection technique based on Recursive feature elimination (RFE), In...
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36 Sitasi
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)
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. Noda...
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10 Sitasi
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)
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 begi...
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20 Sitasi