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All Journal Indonesian Journal of Electrical Engineering and Computer Science Journal of Computing Theories and Applications
Rume Elizabeth Yoro
Dennis Osadebay University Asaba
Computer Science & IT Decision Sciences, Operations Research & Management

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Improved services traceability and management of a food value chain using block-chain network: a case of Nigeria Maureen Ifeanyi Akazue; Rume Elizabeth Yoro; Bridget Ogheneovo Malasowe; Obinna Nwankwo; Arnold Arnold Ojugo
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1623-1633

Abstract

Competitive asset markets and increased globalization have continued to ripple the food value chain with complex dynamics, which has led to a range of challenges such as food safety and quality, traceability, and overall supply chain inefficiency. These have further continued to endanger the general well-being of society. With rice as a staple food in Nigeria, the rice food supply value chain consists of a series of tasks, processes, and activities that are linked together from freshly harvested products to consumer demand and supply. Study advances the SmartRice, a sensor-based block-chain framework that decentralizes as well as provides a decision-support for the food supply value chain process by first ensuring that accurate data of harvested goods are reported, and passed on to a chain. The study advances a decentralized framework to eliminate various forms of fraud rippled across the existing centralized system, minimize corruption through its sensor-based layered model as well as minimize the error in reported data along the value chain.
Effects of Data Resampling on Predicting Customer Churn via a Comparative Tree-based Random Forest and XGBoost Rita Erhovwo Ako; Fidelis Obukohwo Aghware; Margaret Dumebi Okpor; Maureen Ifeanyi Akazue; Rume Elizabeth Yoro; Arnold Adimabua Ojugo; De Rosal Ignatius Moses Setiadi; Chris Chukwufunaya Odiakaose; Reuben Akporube Abere; Frances Uche Emordi; Victor Ochuko Geteloma; Patrick Ogholuwarami Ejeh
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 Arnold Adimabua Ojugo Arnold Arnold Ojugo Bridget Ogheneovo Malasowe Chris Chukwufunaya Odiakaose De Rosal Ignatius Moses Setiadi Fidelis Obukohwo Aghware Frances Uche Emordi Margaret Dumebi Okpor Maureen Ifeanyi Akazue Obinna Nwankwo Patrick Ogholuwarami Ejeh Reuben Akporube Abere Rita Erhovwo Ako Victor Ochuko Geteloma