AbstrakSekarang ini kebutuhan akan akses informasi sangat penting karena informasi yang diperoleh tersebut dapat menentukan atau memberikan kenyamanan dan kemudahan dalam melakukan aktivitas sehari-hari. Salah satu contohnya adalah dengan menggunakan gadget seperti smartphone, notebook, tablet dan yang lain-lain, kita dapat mudah mengetahui informasi yang ada secara langsung tanpa harus datang ke tempat tersebut. Sistem ini bertujuan merancang sistem informasi di tempat parkir. Teknologi ini dapat memberikan gambaran mengenai jumlah ketersediaan tempat parkir yang sudah terisi maupun yang masih kosong. Dengan mengakses IP address yang diberikan sebelumnya, maka kita akan mengetahui ketersediaan tempat parkir secara langsung. Dari hasil pengujian dapat dikatakan bahwa sistem ini memiliki kelebihan mudah digunakan, penerapan yang sederhana dan dapat membantu meningkatkan kenyamanan/kemudahan bagi pengguna tempat parkir. Namun juga sistem ini memiliki kelemahan yaitu web server yang digunakan memiliki memori yang sangat kecil sehingga tidak dapat di akses oleh banyak pengguna dalam waktu bersamaan. AbstractNow the need for access to information is very important because the information obtained can specify or provide comfort and ease in performing daily activities. One example is to use gadgets such as smartphones, notebooks, tablets and others, we can easily find out information directly without having to come to the venue. This system aims to design information systems in the parking lot. This technology can provide an idea of the amount of available parking spots has been filled or empty. By accessing the IP address given earlier, then we will know the availability of parking space directly. From the test results, it can be said that this system has the advantages of easy to use, the application is simple and can help improve the comfort / convenience for users of the car park. But this system also has the disadvantage of a webserver which is used has a very small memory that can not be accessed by many concurrent users in one time.
Demand of higher data speed communication must be supported by good system and precise Evolved Node B allocation to give a good service quality. In the future especially Indonesia telecommunication network keep growing, data traffic with effective perfomance keep developed by mobile operator (service provider). Mobile telecomunication networking need cell planning with aim to meet cell coverage which is showed by number of base station, with minimal allocation but can meet the requirement of traffic capacity and coverage area.Chance to develope Long Term Evolution (LTE) Technology is at frequenies 1200 MHz, 1800 MHz, 2100 MHz and 2300 MHz. eNode B Allocation uses genetic algorithm and evolutionary programming. In Genetic Algorithm and evolutionary programming, searching technique is done by analyzing the size of the the population. Individual in one population is called by the term of chromosome. This chromosome is one of solution in the shape of symbol. In the beginning, population developed randomly, next population will be result of chromosomes evolution by iteration which is called by the term of generation. This eNode B allocation generates the best cell radius, observed by number of generations and eNode B allocation uses by using genetic algorithm and evolutionary programming which generate same cell radius.
The communication using of HF (High Frequency) is a system that depends on wave propagation using sky waves reflected by the earth's ionosphere layer so that it is highly effective for long distance communication, but highly dependent on varying ionospheric conditions from day and night (time after time) as well as the location of the transmitter and receiver radio. Currently, there is only one main frequency channel and one reserve frequency channel so that there are frequency constraints unable to communicate due to ionosphere changes. This research will predicted allocation of HF frequency to support long distance communication for marine monitoring using Genetic Algorithm method. Output or prediction results in the form of Optimum Work Frequency (OWF) for 24 hours and frequency graph.
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