Time Series Forecasting of Solid Waste Generation in Arusha City - Tanzania

Statistical time series modeling is widely used in prediction and forecasting studies. This study intends to analyze, compare and select the best time series model for forecasting amount of solid waste generation for the next years in Arusha city - Tanzania among ARMA/ARIMA and Exponential Smoothing models. The past data used are monthly amount of solid waste collected by the city authorities from year 2008 to 2013. The result indicated that ARIMA (1, 1, 1) outperformed other potential models in terms of MAPE, MAD and RMSE measures and hence used to forecast the amount of the solid waste generation for the next years. Keywords: ARIMA models, Exponential Smoothing models, time series, MAPE, MAD, RMS

Modeling the Impact of Immunization on the Epidemiology of Varicella Zoster Virus.

Chickenpox (also called varicella) is a disease caused by virus known as varicella-zoster virus (VZV) also known as human herpes virus 3. In this paper, a deterministic mathematical model for transmission dynamics of VZV with vaccination is formulated. The effective reproduction number is computed in order to measure the relative impact for individual or combined intervention for effective disease control.  Numerical simulations of the basic reproduction number of the model shows that, the combination of vaccination and treatment is the most effective way to combat the epidemiology of VZV in the community. Keywords: Modeling, Treatment, Vaccination, Epidemiolog

Estimation of Irrigation Water Demand in Rice Production Tanzania

The agriculture sector is one of the major users of water resource for irrigation activities. In Tanzania irrigation water demand for rice is still increasing due to the area being irrigated continues to expand while the amount of water for irrigation is decreasing. The purpose of this paper was to develop the demand function for estimation of irrigation water in rice production in Tanzania. The secondary data were collected from various sources such as the Ministry of Agriculture, Food Security and Cooperatives at Statistics Unit, and relevant basin authorities and zonal irrigation units. A demand function was estimated after carrying out the relevant statistical tests. The Breush and Pagan Lagrangian Multiplier Test were used to select whether to use the Pool or Panel Data approaches. The Panel model was verified to be more suitable than the Pool model. The fixed effect and random effect were compared in the Hausman’s specification test. The price elasticity of irrigation water demand and other elasticity were also estimated using Ordinary Least Squares facilitated by STATA 11. A panel data of 16 regions of Tanzania in the period of 2007 - 2012 were used. The estimated average water demand found to be 8000m3/ha whereas water productivity in rice cultivation found to be 0.3kg/m3. Keywords: Water demand function, Water productivity, Panel data, Rice, Irrigation wate

ANALYZING THE IMPACT OF HISTORICAL DATA LENGTH IN NON SEASONAL ARIMA MODELS FORECASTING

Different values of minimum data requirement for ARIMA models have been proposed. It also proposed to use as much data as they are available in formulating ARIMA models. This paper studied the impact of the size of the historical data on ARIMA models in forecasting accuracy. The study used 286 weekly records of amount of solid waste generated in Arusha City to formulate four ARIMA models using different data lengths or size. The first model, M1 used 30 observations, the second model, M2 used 60 observations, the third model M3 used 120 observations and the fourth model, M4 used 260 observations all of which are the most recent. A total of 26 observations were held out for validation. The precision in forecasting was tested using MAPE, RMSE and MAD.  The results indicated variation in precision. M3 performed best in one-week ahead and 9 – 12 weeks ahead while M4 did best in 2 – 8 weeks and also for 13 weeks  and above. M1 was the worst model in forecasting. Keywords: ARIMA models, MAPE, RMSE, MAD, Forecastin

Analysis of the Behaviour of Stocks of Dar es Salaam Stock Exchange (DSE)

A stock market is a place where investors trade certificates that indicate partial ownership in businesses for a set price. Different countries in the world have stock markets where other countries started their stock markets long time ago like the USA  and they have investigated the trend of their market if it is normally distributed or not. Also they have strong models that assist them in making predictions and also help the investors on the choice of the stocks to invest so as to gain the profit in the future. On the other hand other countries just started few years ago. Tanzania is among the countries where stock markets has just started recently and hence there is a need to study the nature of the stocks distribution and see whether the Dar-Es-Salaam Stock of Exchange (DSE) market do follow the theoretical conclusions or not. Thus in this study we adapt the Markowitz modern portfolio theory (MPT) and using the mean variance analysis theory together with the DSE data to investigate if the DSE stock market follows a normal distribution or not. The analysis shows that the DSE stocks log returns are reasonably normally distributed and its prices do change according to the change in other factors like the inflation rate, consumers (investors) interest, the policy of the country, and other exogenous factors. Keywords: portfolio, stock market, volatility (risk), expected return, covariance matrix

Modeling the SBC Tanzania Production-Distribution Logistics Network

The increase in customer expectation in terms of cost and services rendered, coupled with competitive business environment and uncertainty in cost of raw materials have posed challenges on effective supply chain engineering making it essential to do cost-benefit analysis before making final decisions on production distribution logistics. This paper provides a conceptual model that provide guidance in supply chain decision making for business expansion. It presents a mathematical model for production-distribution of an integrated supply chain derived from current operations of SBC Tanzania Ltd which is a major supply chain that manages products' distribution in whole of Tanzania. In addition to finding the optimal cost, we also carried out a sensitivity analysis on the model so as to find ways in which the company can expand at optimal cost, while meeting customers' demands. Genetic algorithms is used to run the simulation for their efficient in solving combinatorial problems

Modeling the SBC Tanzania Production-Distribution Logistics Network

The increase in customer expectation in terms of cost and services rendered, coupled with competitive business environment and uncertainty in cost of raw materials have posed challenges on effective supply chain engineering  making it essential to do cost-benefit analysis before making final decisions on production-distribution logistics. This paper provides a conceptual model that provide guidance in supply chain decision making for business expansion. It presents a mathematical model for production-distribution of an integrated supply chain derived from current operations of SBC Tanzania Ltd which is a major supply chain that manages products' distribution in whole of Tanzania. In addition to finding the optimal cost, we also carried out a sensitivity analysis on the model so as to find ways in which the company can expand at optimal cost, while meeting customers' demands. Genetic algorithms is used to run the simulation for their efficient in solving combinatorial problems. Key words: Business environment, supply chain engineering, production-distribution, genetic algorithms, optimal cost

A Deterministic Mathematical Model for the Control of Spread of Prosopis Juliflora Plants

This research article published by Journal of Mathematics and Informatics Vol. 19, 2020Prosopis juliflora plants are the most aggressive invasive species in the world. They spread by animal movement crossing from one place land to another. In this paper a deterministic model to examine the dynamics of Prosopis julifrola plants is formulated and presented by adopting a similar approach of a dynamical system as used in epidemiological modeling. The local and global stability analyses of the equilibrium points of the model performed by using next-generation for the basic reproduction number R0 computation and Lypunov function method. The finding from the study showed that the Prosopis free equilibrium of the model is both locally and globally asymptotically stable if and only if the number of secondary infections, is less than unit, that is R0 < 1. Furthermore, the study showed that there exist Prosopis endemic equilibrium for the spread when 0 R >1. The numerical simulation implemented in MATLAB ODE45 algorithm for solving linear ordinary differential equations. The study findings showed that as the number of ingested animals increase, the plant spread increases on land. Based on the findings, the study recommend the application of the model on endemic areas to improve through: Awareness on animal feeding the plant, provision of insight on plant invasion to policy makers and environmental stakeholders to include in environment framework, seminars and environment clubs by visiting community groups an educating them on plant invasion, through this the plant eradication could be achieved

Warehouse Management System Enhancement: A Case Study of ATOZ Textiles Limited

This conference paper was published by IEEE, 2021With technology advancement, the application of technology in conglomerate companies is crucial for company performance.Technology utilization in industry in developing countries is a challenge. Often there is a crisis of equipment, goods, and items destruction or loss in warehouses. The enhancement of the warehouse management system for the company helps to utilize resources effectively, thus improving company performance.This study aimed to enhance the management of warehouses through the use of information communication and technology. The study developed mobile applications for customer registration, order management, and stock management. The study also extended the web applications for account management, order management, invoice generation, client registration, and stock management. The study was conducted at AtoZ Textiles Company Limited located in the Kisongo area, Arusha Region

Mobile Application for Gate Pass Management System Enhancement

This Conference paper was published by IEEE, 2021Gate pass management is a vital measure to keep records of people’s entrance and exit of company premises. Technological improvement steered gate pass management from paper-based logbooks to web-based systems that rely on the internet. Usually, a web-based system can be accessed through a computer browser or mobile browser. The technological evolution of smartphones lures many users in using mobile phones for access internet and web-based systems. The use of smart phone offers portability, flexibility, and a good user experience. Due to the small screen size and input method of smartphones, it’s challenging to use mobile phones to access web-based gate pass management systems. The development of mobile applications introduces a better user experience and easy access to gate pass users. The application provides added advantage in simplifying the whole process of gate pass management. Mobile phone portability and accessibility are utilized to ensure users can have access to gate pass management at any time and anywhere. Mobile application camera is an added feature utilized for scanning gate pass barcodes and taking pictures of gate pass users for more security records. Therefore, the enhancement of the gate pass management system brings an easy way for the user to manage the gate pass process through their smartphone phones