The schooling of tertiary level is a source of culture for any nation and this issue has always been a major public concern. The success of this level depends on various issues that can influence the students to gather knowledge. Among them, class participation is vital for understanding the course contents. The education system of Bangladesh is almost sound and well-organized in all levels including tertiary stage. Even so sometimes, students are unwilling to attend in the classroom for a number of reasons. In this study, we measured how previous absence of a student impact on their further absence. Markov Chain is a mathematical tool that identified the chance of previous absence effect on the recent absent. In another methods, logistic regression showed the dependency of today’s absence on previous absence. In this work, we got, the previous day absence influenced the student to continue his/her absent on the current day. Therefore, students’ continuous class participation is important and any sorts of discontinuity makes a barrier to participate in the next class

In this paper, we develop a mathematical model combining forecasting and linear programming for a business organization of Bangladesh to calculate optimum order quantity and inventory cost. We test the model using raw data of the demand for the raw materials and spare inventory for the industry and find out minimum total inventory cost along with ordering cost and inventory holding cost. The developed model make a match between the forecasted demand of raw materials and spare inventory and the minimum total cost of inventory. Finally comparing minimum cost, we observe that our estimated appropriate forecasting method gives optimal inventory cost. Dhaka Univ. J. Sci. 68(1): 65-70, 2020 (January)

Demand forecasting and inventory control of printing paper is crucial that is frequently used every day for the different purposes in all sectors of educational area especially in Universities. A case study is conducted in a University store house to collect all historical demand data of printing papers for last 6 years (18 trimesters), from January (Spring) 2011 to December (Fall) 2016. We will use the different models of time series forecasting which always offers a steady base-level forecast and is good at handling regular demand patterns. The aim of the research paper is to find out the less and best error free forecasting techniques for the demand of printing paper for a particular time being by using the quantitative forecasting or time series forecasting models like weighted moving average, 3-point single moving average, 3-point double moving average, 5-point moving average, exponential smoothing, regression analysis/linear trend, Holt’s method and Winter’s method. According to the forecasting error measurement, we will observe in this research that the best forecasting technique is linear trend model. By using the quantities of data and drawing the conclusion with an acceptable accuracy, our analysis will help the university to decide how much inventory is absolutely needed for the planning horizon. Dhaka Univ. J. Sci. 66(1): 15-19, 2018 (January)