Numerous firms accumulate large quantities of data or transactions after importing information systems and services, which leads to troubles with data procedure. Firms also have demands to find customers’ information from large datasets and to understand how to develop marketing strategies accurately to adjust their operational methods. Therefore, this study proposed customer ranking combined Big Data process based on the RFM model (Recency, Frequency, Monetary) to develop a recommendation algorithm using an association rule, which finds greater recommendation to promote operational effects of firms. We adjust the weight of potential information to perform the customer ranking, which is conducted by using agglomerate hierarchical clustering. Finally, we present the recommendation by the association rule for each customer level.The datasets in this study use actual sales data; therefore, they are authentic and have been practically applied. The metrics of evaluation showed that the recommended system his study proposes is highly accurate.

The great popularity of cloud services, together with the increasingly important aim of providing Internet context-aware services, has spurred interest in developing diverse agriculture applications. This paper presents a cloud-based service built by incrementally integrating state-of-the-art models of deep learning, photography, object recognition and the multi-functionalities of cloud services. This study consists of an object detection phase with a convolutional neural network (CNN) model, which involves enabling simultaneous image data gathered from drones. The experimental results show 97% accurate watermelon recognition. Our results also include a two-model comparison in the cloud-based service, with the main findings demonstrating the feasibility of developing accurate object recognition using a CNN model without the need for additional hardware. Finally, this study adopted a confusion matrix to validate the result with RetinaNet for recognizing images taken on the watermelon farm with an average precision in recognizing watermelon quantity of up to 98.8%.

In recent years, the electronic commerce provided by Internet and Web is about to establish itself as a significant economic factor worldwide. For this reason, corporations have been seeking to develop a system to assist business process. More of all electronic commerce websites aim to improve and realize business process. In addition to the telecom corporation also started to provide their services on the interneet, but sometimes their services cannot communicate with the backend systems. Hence, we consider an intelligent agent approach to solve above problem. Our intelligent agent is designed by web service technology and communicated with each backend system. The methodology is also applied to a real case that involves receiving user's request to accomplish the telecomm company's services.