This study aims to acknowledge how environmental performance, corporate governance, competitive advantage, and financial performance-linked each other in Japan. The data used are data from chemical, pharmaceutical, and machinery sub-sector companies listed on the Japan Exchange Group 2013 - 2018. This research was explanatory research using a quantitative approach and implemented Partial least Square (PLS). This study found that the board of directors and firm performance have no significant effect on the company's environmental performance, while corporate control and ownership structure provide a different result. Then, environmental performance and ownership structure have been proven to bring a significant contribution to the company's competitive advantage. Reflecting on Japan, this study suggests several recommendations to the Indonesian Ministry of Environment and Forestry to develop environmental conservation schemes and concepts implemented by public companies in Indonesia and the Indonesian Ministry of Finance to develop applicable environmental accounting concepts for public companies in Indonesia.
Sasak’s script is the one of Indonesia's cultural heritages which is endangered language category and it needs to be preserved so its not become extinct script. If there is no preservation, Sasak’s script will be close to extinction. Given the importance of conservation efforts, a reserch was carried out to recognize the Sasak’s script handwriting patterns. This reserch aims to see the optimal model for recognizing Sasak script patterns and to see how accurate the Linear Discriminant Analysis method as extraction features and Backpropagation Neural Network as a classification method for recognizing Sasak’s script patterns. The dataset in this reserch consisted of three variations amount of data which are 13500, 10800 and 2700. According to the final results of the study the best accuracy was obtained in the 10800 dataset, 92.20% with 92% precision and 92% recall with 250,691s computing time. The test is based on the best paramater of DCT coefficient test parameters, eigen value, number of neurons, number of hidden layers and learning rate that has been tested before.
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