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The goal of this study is to use a Convolutional Neural Network to find the optimum architectural model for classifying cloud images. Cirrus Cumulus Stratus Nimbus uses a source dataset that includes 11 cloud classifications and 2545 cloud photos (CCSN). In this study, the best Convolutional Neural Network is retrained almost fast by transferring education from Google’s basic design. Based on the modified Googlenet architecture, the training and testing phases of the classification process are divided into two. The dataset is separated into three sections during the training phase: 70% of the training data, 15% of the validation data, and 15% of the test data. There are two trials to categorize cloud photographs during the test phase, one of which has ten cloud kinds that can be randomly chosen. The precision achieved throughout the training was 44.5%, according to the findings. The results of the two tests are 75%, with an average error of 0.2. In the testing phase, the percentage is 75%.

This research is intended to the Government at Binjai City of North Sumatra. Application of e-governance at regional work unit (SKPD) aims to strive the improvement of work performance based on several principles on good corporate governance (GCG) such as transparency and accountability on the government of Binjai City. Furthermore, this test is done by taking data to use questioners for all regional work (SKPD) in Binjai City. There are 52 people as budget user or author then the data is processed using some descriptive analysis methods. The result of research stated that even though the relation e budgeting is low with the accountability and transparency but the level of achievement of the use e-budgeting has been reached well in attempting to increase the function of transparency and accountability so it is concluded that the role of system e-budgeting in increasing value of transparency and accountability on the government of Binjai City has been achieved.

The current research uses the Confirmatory Factor Analysis and Multiple Linear Regression models to examine several factors that influence the improvement of rural development. The study was conducted in a village where is called Pahlawan Village, located in Tanjung Tiram sub-District, Batubara Regency, North Sumatra. The results of the Confirmatory Factor Test have found four factors that influence the improvement of village development. The intended factor is Government Policy, Economic Institution, Availability of Employment and the last is Community Institution. The results of multiple linear regression tests show that all variables have the positive effect on increasing rural development. The results of research findings for the t-test show that government policies and economic institutions have a positive and significant effect on improving rural development. While the availability of employment and community institutions have the positive but not significant effect on increasing rural development. The authors suggest that local and central government policies that are able to encourage the creation of employment in accordance with the potential of this region such as the fish canning industry. The role of economic institutions should be for economic empowerment, distribution of the production of fishermen and the increase in value added products.