Alternative Strategy to Improve the Conservation of Javan Deer in Pangandaran Nature Reserve, West Java, Indonesia

The habitat of Javan deer in Pangandaran Nature Reserve (PNR) faced natural changes, particularly due to the succession process of vegetation community in grazing areas, and inadequate infrastructures that affected the deer to roam outside PNR. This study aimed to formulate strategies for the conservation of Javan deer in PNR, focusing on ecological aspects and conservation management. The methods were encountering Javan deer individuals; scan sampling and continuous recording to observe the behaviour of Javan deer; calculating the productivity of grazing area by defoliation experiment and vegetation analysis; reviewing documents, reports and interviews; and analysing strategy using SWOT-QSPM. Results showed there were 43 Javan deer encountered roaming in PNR and outside the conservation area, and nine individuals gathered in Cikamal grassland. The productivity of the grazing areas (5.61 ha) was 93,826 kg of feed annually and was only sufficient for 23 individuals. The grazing areas were dominated by Cynodon dactylon. Javan deer spent their time feeding. Javan deer herd in Cikamal is more intolerant to humans compared to the herd in Pangandaran Nature Tourist Park (PNTP). This study recommends: considering the management status of Javan deer in the conservation management of PNR and PNTP; improving the conservation management of Javan deer and its habitat; improving facilities and the management system of those facilities and conservation-supporting infrastructures; collaboration with researchers to perform some research and innovations for Javan deer conservation; improving the capability of PNR staff theoretically and practically; and educating and empowering the local people in terms of Javan deer conservation.

IoT and fuzzy logic integration for improved substrate environment management in mushroom cultivation

The current era witnesses the advent of the Internet of Things (IoT), a transformative force giving rise to various technological innovations, most notably connected objects. This paradigm shift catalyzes the widespread adoption of autonomous decision-making systems, particularly in sectors like agriculture, where the aim is to amplify productivity. As a result of the agricultural domain, mushrooms have concurrently emerged as a significant component of daily diets, offering additional vitamins and flavor. Despite their popularity, cultivating mushrooms in open environments poses challenges in maintaining optimal environmental conditions, prompting numerous research efforts. Recognizing the inconsistencies in existing approaches to safeguard vital parameters in mushroom farms, this paper introduces an innovative system utilizing intelligent sensors whose real-time records are managed based on the fuzzy sets concept. These sensors, encompassing the Capacitive Soil Moisture Sensor v1.2, DHT22 Sensor, Light Dependent Resistor (LDR sensor), and Passive Infrared Receiver (PIR sensor), collectively capture essential data for decision-making in mushroom farming. Employing fuzzy logic, the system addresses pivotal aspects such as substrate watering, environmental control, light management, and pest detection. Through experimental results, it becomes evident that the proposed system not only exemplifies the potential of IoT technologies in agriculture but also offers a comprehensive and efficient approach to real-time decision-making. By aggregating sensor data, the system proves instrumental in enhancing the quality and yield of mushroom crops, showcasing a promising trajectory for sustainable and technologically driven agricultural practices