UMKM Tiga Bintang is one of the household-scale agro industries that processes roa fish, duo fish, moringa, and purple sweet potatoes as the basic ingredients into various kinds of snacks in the form of sticks. To get the best quality in accordance with the standards desired by consumers, quality control is needed, which aims to minimize deviations that are not in accordance with the standards set by the industry itself. The purpose of this study is to see whether quality control in the production process by UMKM Tiga Bintang is controlled or uncontrolled. The type of data used in this study is primary data. The analysis process carried out in this study uses the Statistical Quality Control (SQC) approach. Statistical Quality Control is a statistical technique that is widely used to control the quality of a product, by evaluating quality in terms of compliance with specified specifications. The SQC analysis results show that the number of products examined was 24800, where the average product damage was 0.095121 or 9.5121%, with the most type of damage occurring there was a brownish product colour. The upper control limit (UCL) and the lower control limit (LCL) for each production vary. Quality control of UMKM Tiga Bintang is not well controlled because of uncontrolled production time within the upper and lower control limits.

Money is a tool that can be used in exchanging goods and services in a certain area. Increasing and decreasing in the money supply excessively can have a negative impact on the economy. For this reason, in order to maintain financial system stability in Indonesia, it is necessary to conduct an analysis of the data on the amount of outflows of rupiah currency at each Bank Indonesia office. In this study, a relationship analysis will be carried out between the eastern region of Indonesia and the amount of outflows of Bank Indonesia banknotes during the 2016-2018 period using circular regression analysis. The results showed that 83.03% of the variation in the amount of outflows of BI banknotes could be explained by the circular regression model that was formed. In addition, in the process of forecasting data on the amount of outflows of BI banknotes in the eastern region of Indonesia for the 2019-2020 period, the time series forecasting method is used which is based on the use of analysis of the relationship pattern between the estimated variables and the time variable.