This study aims to analyze the relationship between the financial indicators contained in the financial statements and dividend policy. Companies that are listed on the Indonesia Stock Exchange and meet the criteria set out in the study are used as research samples. This study uses 631 observational data from 2017 - 2021 obtained from the company's official website and the Indonesia Stock Exchange. Panel data regression is used to examine the effect of each variable on dividend policy. The best regression model in this study is the Fixed Effect Model. This study shows that free cash flow; firm risk; and return on equity have a significant positive effect on dividend policy. In addition; market to book value ratio and net asset growth have a significant negative effect. Other variables used in this study do not affect dividend policy.
Keywords: Dividend Policy; Profitability; Liquidity; Financial Ratios.
Fish Image Classification Using Convolutional Neural Network is an application that helping classification process. The application is used by user for knowing an information about what is the name of fish species from image that visitor captured. The application is designed by Python programming language. Method of designing the application using System Development Life Cycle. The method used in training model is Convolutional Neural Network, Data used in training process are the species data set is more than 10 species and each species is more than 1000 images, The data collected has been divided into training data and test data. In training process, Fish Image Classifiation Program produce a train loss value of 0.189203, validation loss value of 0.033459 and accuracy value of 0.991029. The evaluation process is carried out using a Confusion Matrix where the diagonal data is the correct prediction data, while the other data is the wrong prediction. By evaluating the Confusion Matrix, predicted accuracy reaches 99.1%precision and recall is 0.98. The resulting accuracy is very good accuracy so that it can predict the image inputted by the user accurately.
Koi is a prospective fishery commodity that make a positive contribution to Indonesia National GDP. Subdistrict Ciseeng especially in Babakan Village became one of the areas that make a positive contribution because there is a koi farmers, but has a different price level koi farmers with the consumer level. The purpose of this research is to analyze the institution, functioning, marketing channels and efficiency of marketing channels koi. Methods of data collection using purposive sampling to farmers and marketing agencies using snowball sampling. The results showed marketing agencies involved include farmers, village merchants, merchant shops and suppliers with functions exchange, physical and facility in nine koi marketing channels in Babakan Village. The efficiency of marketing channels occurs in channels VII because it has a lower marketing margins, the farmer's share is higher and the ratio of benefits to costs relatively with sales volume 210 tail.
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