Data mining being an experimental science is very important especially in the health sector where we have large volumes of data. Since data mining is an experimental science, getting accurate predictions could be tasking. Getting maximum accuracy of each classifier is necessary. It is therefore important that the appropriate feature selection method should be selected. Feature selection is highly relevant in predictive analysis and should not be overlooked. It helps reduce the execution time and provide a more accurate and reliable result. Therefore, more researches on predictive analysis and how reliable these predictions are needs to be delved into. Application of data mining techniques in the health sector ensures that the right treatment is given to patients. This study was implemented using WEKA. This study is aimed at using 3 classifiers: multilayer perceptron, naive bayes and J48 decision tree in the prediction of chronic kidney disease dataset. The aim of this research is to evaluate the performance of the classifiers used based on the following metrics-accuracy, specificity, sensitivity, error rate and precision. Based on the performance metrics mentioned above, results shows that J48 decision tree gave the best result but naive bayes had the lowest execution time therefore making it the fastest classifier.

Background: Globally, women and their unborn babies continue to die from preventable causes. This study aims to highlight the causes of maternal and perinatal deaths and bring to the fore areas that need to be improved in order to improve maternal and perinatal health indices in Gombe State. Methodology: Information for this report was obtained from Maternal and Perinatal Deaths Surveillance and Response (MPDSR) desk officers and chairmen across MPDSR supported health facilities in the state. Secondary data abstraction from registers was conducted using an electronic questionnaire and was analysed using SPSS version 23. Findings: The Maternal Mortality Ratio (MMR) was 1,092/100,000 livebirths in 2019 and 993/100,000 live births in 2020. Majority of the women (84.3% and 86.7% in 2019 and 2020 respectively) were severely ill at presentation, while most maternal deaths were as a result of eclampsia/pre-eclampsia and Post Partum Haemorrhage (PPH). Only 15.9% and 14.4% of maternal deaths in 2019 and 2020 respectively were reviewed. Perinatal asphyxia accounted for 36.4% and 31.8% of perinatal deaths in 2019 and 2020 respectively, while prematurity resulted in 24.7% and 35.6% of deaths in 2019 and 2020 respectively. The Perinatal Mortality Rates (PMR) were 78.3/1000 births in 2019 and 76.1/1000 births in 2020. Conclusion: Although MMR and PMR have been on a decline in Gombe state from 2018 till date, these figures are still far from achieving the SDG 2030 target. There is therefore the need to revive MPDSR activities in the state and improve emergency obstetric health care services.

Dwindling Economy is otherwise known as depression economy or economy depression interchangeably and/or recess economy. It is an occurrence wherein an economy is in a state of financial turmoil, often the result of a period of negative activity based on the country’s Gross Domestic Product (GDP) rate. However, this has become a global phenomenon; a good example of a necessitating factor is the global oil crash market and pandemics virus (Covid-19) ravaging the human race. That has conjointly led to the decline in the GDP growth per capital of a country; which forces degradation in the performances of economic sectors, retrenchment of staff and wrapping-up of industries. It is a lot worse than a recession, with GDP falling significantly, and lasts for periods of time. Pen ultimately, Nigeria has been in deteriorating financial state for years; her economy in the last few years has been going through some turbulence. A country that had recorded an average GDP growth of 6.5 per cent, one of the highest in the world less than a decade ago, is now projected to grow at about 2.3 per cent in 2016. It is no longer news that Nigeria's economy is experiencing total collapse and if nothing is done to put the peg in the right spot something worse than what we are witnessing may soon be on sight. Based on some of all these issues and other, Nigeria was said to be technically recess.In this paper, efforts were made to explore the state of the Nigeria economy in the last 36 years (1981-2017) and correlate it with the recent phenomena that conjointly constitute to its dwindling economy. Our comprehensive and elusive literary survey and extemporariness suggested way forwards to rescue the raveling situation of Nigeria dwindling economics, if not providing lasting solution but temporarys’ one that could stand test of time.

SIMBox or Interconnect Bypass Fraud is one of the most rapidly emerging frauds in today's telecommunications industry, costing the industry between $3 and $7 billion USD in annual revenue losses. This was spread as a result of calls made over the internet and routed to SIMboxes (machines that contain SIM cards) that redirect illegitimate VoIP traffic onto mobile networks. Fraudsters effectively avoid the inter-connect toll charging points by exploiting the difference between the high interconnect rates and the low retail price for on-network calls, thereby avoiding payment of an Operator's or MVNO's official call termination fee. This paper is a fact-finding type that investigates the impact of SIMBox fraud on the telecom industry and the economic development of nations. By disclosing the fraud detection approaches used for its abolition and identifying their flaws. For this study, a quantitative method was used. The study's literary material spans the years 1994 to 2021. Journals, white papers, M.Sc., and Ph.D. theses on the subject are examples.

Institutions such as banks, airlines, hospitals and telecommunication industries employ queuing theory to help in assisting the capacity levels needed to experience demand in a more optimized way for service improvement. In this article, we studied and employed the queuing theory activities of the Federal University Gusau Health Services Clinic. The distributions of patients’ arrival and service times were identified. The system was treated as a single, time-independent arrival with multiple service points. Based on the data obtained on the arrival and service processes, appropriate distributions were fitted and tested using the Chi-squared goodness of fit-test.