Pandeglang Regency is an area that has the potentiel to be hit by tsunamis. The plate subduction paths of Indo-Australia and Anak Krakatau Volcano make Pandeglang Regency a region with a high tsunami potential. One step that can be taken to overcome and minimize losses is to do spatial planning to protect it against potential tsunami damage. This research aimed to evaluate the spatial area of Pandeglang Regency based on the identification of potential tsunami hazards. The concept of modelling the tsunami inundation height developed by Berryman and based on Head Regulation No.4 of 2012 of the Indonesian National Board for Disaster Management has been used to identify potential tsunami hazards. The modelling was carried out by calculating the potential distribution of tsunami wave heights in coastal areas. Three scenarios were used to estimate the distribution. The results showed that the first scenario predicted a maximum tsunami height of 7.5 meters above sea level with the furthest tsunami inundation reaching 1,700.12 meters. Second scenario predicted maximum height of 15 meters, with the furthest tsunami inundation reaching 3,384.62 meters. Meanwhile, the last scenario was able to predict a height of 20 meters and showed the furthest tsunami inundation reaching 5.155,11 meters. These results proved that in all scenarios, the widest inundation would occur in Panimbang Regency. This is due to the relatively small variations in roughness and slope of the surface. The same condition also occurs in the last two scenarios, in which Sumur District was the area most ffected. Therefore, the spatial plan of Pandeglang Regency needs to be evaluated and the function of residential area changed to reduce and prevent large losses.
Temporal observation is a series of processes started by collecting the necessary data, which is then processed, so that valid information is obtained to support the right decision. To increase the ease of data collection, an automatic algorithm is needed to increase efficiency, shorten the time, and reduce the required resources. The automatic algorithm based on the geographic information system developed in this study was applied to monitoring mangrove forests in Gopek Beach, located on the north coast of Serang, Banten. Using the cloud computing process from an automatic algorithm, the results of vegetation monitoring showed increased efficiency in time and resources. Thus, this study can be used for Geographic Information Systems learning materials in schools or universities.
Energi merupakan kebutuhan dasar manusia. Seluruh fasilitas yang mendukung operasi dari energi terbarukan memerlukan lokasi strategis yang memadai dan memenuhi segala aspek yang dibutuhkannya, termasuk aspek geografis. Perbedaan kebutuhan karakter geografisnya didasari oleh kemampuan konversi energi yang berbeda beda pada setiap unit pembangkitan energi, hal ini menuntut pihak pengembang untuk menentukan lokasi yang strategis dan dapat menunjang pengkonversian energi secara maksimal. Untuk mempermudah dalam menentukan lokasi berdasarkan kriteria geografis tertentu dan sebagai penunjang keputusan, dapat mengoptimalisasi penggunaan Sistem Informasi Geografi. Sebuah studi telah dilakukan di Austrlia Selatan untuk mengebangkan dari erangkaian algoritma Sistem Informasi Geografi untuk pencaran lokasi yang tepat untuk pembngunan PHES. Tujuan pengulas adalah untuk memepelajari bagaiamana algoritma Sistem Informasi Geografi dapat diterapkan dalam mekanisme pencarian secara otomatis dan bagaimana alternatifnya. Sehingga diperoleh aspek-aspek implementatif dari metode yang diulas.
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