Browsing by Author "Katwale, Samwel"

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Development of a mobile application for sales and marketing: a case of Raha beverages company limited
(NM-AIST, 2022-03) Katwale, Samwel
Raha Beverage Company Limited is a wine-producing company based in Arusha Tanzania. It was experienced with the challenge of products advertisement to reach more customers. The problem extended to a lack of knowledge on market demand because there was no prior orders collection before product delivery, also the market demand fluctuation results in either less quantity delivery to wholesalers or delivery delay, causing wholesalers to stay out of stock for a while. Hence decreases customer satisfaction. The proposed RahaSales mobile application was designed to address and mitigate the encountered challenges by the company. The study showed that the mobile application would easily connect the company with their customers for instant communication and getting insights on the market ground. To reflect what was the exact puzzle to be solved; the data was collected from the sales representative and known customers through interviews, questionnaires, and observation. The mobile application was developed through the agile method known as scrum, and then the application was tested by both customers and sales representatives from the company to reflect what the application is required to do. The developed mobile application connects the supplier and wholesalers to enable them to share business information like market demand and product availability. According to the findings, mobile applications can be used to improve client loyalty as well as sales. From the developed application, I would like to recommend further studies to utilize the GPS locations collected from the customers to map all customers in the Google map for easy visualization of current customers and will help the company to determine where there is a gap in the market share and focus more in terms of advertisement and promotions.
Development of a smart ugali cooker
(International Journal of Advanced Technology and Engineering Exploration, 2021-02-21) Katwale, Samwel; Daudi, Ngollo; Hassan, Amran; Mduma, Neema; Dida, Mussa; Kisangiri, Michael
Ugali is a thick porridge that is one of the popular staple foods in East Africa. Traditional methods of ugali preparation, cooking, and consumption are described. Firewood has been used as the primary energy source followed by charcoal. In East Africa, electricity grids have expanded and reached a wider network, which has opened opportunities for electric cooking to domestic consumers, especially in urban that was previously dominated by charcoal, which is in scarce supply due to government regulations on environmental conservation. In this project, the smart ugali cooker was designed and developed to automate the process of cooking ugali in households which is faster, safer, and healthier. The smart Ugali cooker is an automated kitchen appliance designed to boil the mixture of water and maize flour into a dough mixture referred to as ugali. It consists of a driving motor, stirrer, flour dispenser, heat source, a cooking pan, a temperature sensor that measures the temperature of the boiling water in the pan, and the control system (Arduino board). The device has basic units that are a dispenser, stirring unit, electronic control unit, pan, and electric heater. These units were fabricated and integrated to form the complete cooking device. Thereafter, the Arduino board was programmed to control the cooking process. Cooking experiments were conducted, on the cooking duration and the texture of ugali based on water to flour ratio. The results showed that ugali was cooked after ten minutes and the quality was good for consumption. In recommendation, the rightful flour to water ratio must be applied to obtain the desired texture of ugali
Forecasting Financial Resilience: An Analysis of Practices and Limitations in Predicting Trends - A Case Study of Microcredit in Tanzania
(B P International., 2024-10-02) Fujo, Mwapashua; Katwale, Samwel; Dida, Mussa
This research paper delves into the intricate landscape of financial resilience within Tanzanian microcredit institutions, focusing on predictive methodologies and the integration of Artificial Intelligence (AI) for enhanced forecasting accuracy. Through an exhaustive exploration of traditional practices and emerging AI-driven solutions, this study examines the evolving strategies and limitations encounteredpredictive capacities within Tanzanian microcredit institutions. It emphasizes the imperative nature of investing in resources and expertise to leverage AI potential for sustainable growth and heightened forecasting accuracy in this rapidly evolving financial landscape. This study contributes essential insights into the challenges, opportunities, and potential pathways for leveraging advanced technologies in enhancing financial resilience within microcredit institutions, fostering a more sustainable and prosperous future for Tanzania microcredit sector. in predicting financial trends within this dynamic sector. Employing a mixed- methods approach encompassing diverse case studies across key Tanzanian regions - Dar-es-Salaam, Arusha, and Kilimanjaro - the research garnered insights into localized complexities, historical evolution, and direct impact on bolstering financial resilience. Findings underscored the multifaceted objectives pursued by microcredit institutions in trend projection, emphasizing the primary goals of optimizing investment strategies, managing liquidity effectively, and planning for sustainable growth and expansion. While traditional methodologies demonstrated some efficacy, challenges in data quality, interpretation, and predictive analytics expertise emerged as impediments to accurate trend projection. Proposed AI- based solutions offered promising outcomes, with anticipated benefits including improved prediction accuracy, enhanced decision-making, and potential cost savings. However, concerns regarding data security, expertise, and implementation costs pose notable challenges to widespread AI integration. Therefore, the research advocates for the integration of AI technologies to fortify