Snort is a well-known, signature-based network intrusion detection system (NIDS). The Snort sensor must be placed within the same physical network, and the defense centers in the typical NIDS architecture offer limited network coverage, especially for remote networks with a restricted bandwidth and network policy. Additionally, the growing number of sensor instances, followed by a quick increase in log data volume, has caused the present system to face big data challenges. This research paper proposes a novel design for a cloud-based Snort NIDS using containers and implementing big data in the defense center to overcome these problems. Our design consists of Docker as the sensor’s platform, Apache Kafka, as the distributed messaging system, and big data technology orchestrated on lambda architecture. We conducted experiments to measure sensor deployment, optimum message delivery from the sensors to the defense center, aggregation speed, and efficiency in the data-processing performance of the defense center. We successfully developed a cloud-based Snort NIDS and found the optimum method for message-delivery from the sensor to the defense center. We also succeeded in developing the dashboard and attack maps to display the attack statistics and visualize the attacks. Our first design is reported to implement the big data architecture, namely, lambda architecture, as the defense center and utilize rapid deployment of Snort NIDS using Docker technology as the network security monitoring platform.

The main factor for plant growth is fertilization. Fertilization is one of the important processes in plant growth that aims to add nutrients that are completely absorbed by plants. But excessive fertilization can damage the soil structure as well as plants become vulnerable to pests and wasting costs. However, until now, many farmers still apply fertilizer without knowing for sure the nutrient content of the soil; Meanwhile, checking the nutritional content of plants uses chemical solutions and sensors which are relatively expensive, making it difficult for farmers to implement. Based on this problem, this research aims to propose a new approach in the accuracy of fertilization based on soil pH sensors., by utilizing Internet of Things technology, this research focuses on providing recommendations for IoT-based fertilizers using soil pH sensors, the results of the sensors will be correlated with nutrients contained in the soil. Prediction of soil nutrient content is obtained from the correlation between plant environmental conditions. With this system, farmers can monitor the soil density around the plant and get fertilization recommendations through smartphones, and will get notifications of dosage recommendations and types of fertilizers if the pH condition is beyond the normal limit that has been determined. Based on the trials that have been carried out, the system can run well.

Based on Ikatan Dokter Anak Indonesia (IDAI), one of the indicators used to monitor the physical growth and development of healthy children is body weight. It is recommend that in infancy, parents routinely monitor the baby's weight and height. In Indonesia, there is a program of Posyandu that facilitates regular checking of a baby's weight. Currently, the monitoring system for baby weight and height at Posyandu Anyelir 1 Surabaya is still do manually, namely weighing babies on traditional scales and manual height, then manually recording them on the Towards Healthy Card (KMS) both in the cadre records and parents of toddlers. This makes monitoring less well recorded, especially if the KMS is lost. So the PENS Community Service program makes Smart Posyandu Products: Applications and Toddler Nutrition Monitoring Systems Through Baby Weight and Height for Posyandu Services Based on the Internet of Things. By applying the case study method to implementing Smart Posyandu Products at Posyandu, Smart Posyandu Products can be accepted by the Posyandu. So the results of community service activities can help the duties of Posyandu cadres and parents of toddlers in monitoring toddler nutrition effectively and efficiently.

Wireless sensor network (WSN) uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme. Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.