One of the indicators in achieving the goal of sustainable forest management is maintaining forest health. Forest health can describe the good and bad conditions of forest management. Management is carried out based on the functions owned by the forest. With these different managements, there is a need to assess and map the current state of forest health across various parts. This study aimed to obtain values of forest health status in each plot for different forest functions and generate a cluster map of forest health status in other forest functions. This study was on three types of forest based on their functions: conservation forest, production forest, and protection in Lampung Province. The method used is the Forest Health Monitoring (FHM). Method to determine the health of forests using indicators of vitality, productivity, and biodiversity and using Web-GIS to create a map of the distribution of cluster plots. The sample plot used is in the form of cluster plots, with the number of each forest function is divided into 3 clusters whose status is categorized as good, moderate, and bad. Based on the research, it was found that the protected forest cluster 1 had bad health status, cluster 2 was good, and cluster 3 was moderate. The overall health condition of the production function is bad, and the forest health status of the conservation forest function is all good. The current distribution map of the forest's sanitary conditions for the three localities helps guide management decisions to be made soon. The conclusion obtained from this study is that existing forest functions influence forest health status because forest management is adjusted to forest functions so that each function has a different status of forest health conditions.
Dengue fever is a one of the dangerous diseases and very often causes casualties every year, especially in the tropics or subtropics countries. Dengue fever cases increase during the rainy season, many factors affect the spread of dengue fever, such as vegetation, population and landfills. The aim of this research is to predict the number of cases of Dengue fever using support vector machine. The data used are dengue data in Bandar Lampung City, weather data, population data and distance matrix data between dengue fever events with each other. The amount of data used is 1,080 data with 3 kernels: linear, gaussian and polynomial. In this study four experiments were carried out, the first two experiments were carried out without Feature Selection and the next two experiments were carried out with Feature Selection. After the experiment was found The best performance in the experiment with Feature Selection with 44 Variables. From the experiments conducted, Gaussian kernel achieved the highest R 2 value which is 75.52%, while the Linear kernel and Polynomial Kernel achieved R 2 value of 74.61% and 75.15%, respectively.
SIMIPA is an integrated information system for the faculty of mathematics and natural sciences based on a website that functions as a system that can provide services for students and lecturers in the faculty scope. SIMIPA development is based on a pre-existing system. SIMIPA's business process is centered on service form administration, where in its application there are still several problems that must be resolved using the system. One of them is making service forms which are still done manually and student data is not stored in the database, so students must fill in their personal data repeatedly every time they submit a form. The purpose of developing SIMIPA is to add some features needed as well as management of student data in SIMIPA to make it easier for students to get services. This system was developed using the Scrum method which consists of 23 product backlogs with 7 iterations of sprint stages with development targets for 67 days of work.
Forests play a major role in supporting the survival of all living things in the world. A sustainable forest area certainly makes the wildlife live, e.g mentok rimba. A Geographic Information System for Monitoring mentok rimba (Asarcornis scutulata) applying the V-model approach. This research was conducted under programme of Way Kambas National Park and ALeRT (Aliansi Lestari Rimba Terpadu). The purpose of this research is to assist the monitoring team in Way Kambas National Park for updating mentok rimba data. Black Box Testing and User Acceptance Testing were applied. A Geographic Information System (GIS) which contains the distribution of forest stagnation in Way Kambas National Park was built.
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