5 research outputs found

    Pengoptimuman skema logikal pangkalan data hubungan : kajian kes pangkalan data sistem maklumat hidrologi Malaysia

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    It is important to ensure that storing, retrieving, and data manipulating could be done efficiently in a database. This research is focused on the data access in Sistem Maklumat Hidrologi Malaysia (SMHM). The main issue that attracts researchers is low execution time in accessing data. The factor that causes the problem is the structure of the database. Besides, there is such a huge amount of data in SMHM database. Hence, this research produces an optimization technique of relational database logical scheme in order to fix the problem. The technique that has been produced is based on equijoin technique in which two entities that hold the same attribute will be joined and also the tuple classification. In addition, query will be analyzed in order to produce a maximum optimal execution. Comparison has been done on the techniques that have been developed and the SMHM cube system which is the previous technique. The results of the research prove that the technique that has been produced could improve the execution time for query processor, and solve the issue that has been discussed

    Teknik pengoptimuman jadual gabungan kesamaan bagi data bersandarkan masa

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    Pengurusan data bersandarkan kepada masa adalah sangat penting dalam aplikasi-aplikasi sistem pengurusan alam sekitar. Kepentingan tersebut adalah untuk memastikan penyimpanan, capaian dan manipulasi terhadap data-data tersebut dapat dikendalikan dengan cepat dan berkesan. Fokus utama penyelidikan ini adalah terhadap capaian data bersandarkan masa. Isu yang mendapat perhatian penyelidik adalah meningkatkan masa capaian data. Isu ini berlaku di dalam satu sistem maklumatyang digunakan untuk menyimpan data hidrologi yang mana ia menggunakan sistem pangkalan data yang menggunakan kaedah kiub. Satu teknik telah dihasilkan iaitu Pengoptimuman Logikal Pangkalan Data Hubungan Berdasarkan Gabungan Kesamaan dan diimplementasikan terhadap sistem pangkalan data yang sedia ada. Berdasarkan teknik pengoptimuman yang dihasilkan, penyataan pertanyaan akan dianalisa untuk menentukan dan memilih kemungkinan perlaksanaan paling optimum. Keputusan yang diperolehi menunjukkan bahawa terdapat peningkatan masa tindakbalas bagi capaian data

    An equijoin-optimization technique for Malaysian Hydrological Information System (MHIS) data

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    Malaysian Hydrological Information System (MHIS) is one of the GIS applications that storing a large amount of data (such as rainfall, water level, evaporation and water quality). In such situation, it is important to ensure that the storage, retrieval and manipulation of these data are efficiently handled. However, the problem in MHIS is inefficient on retrieval data where it takes a long time to retrieve data. MHIS was developed based on cube system concept. The main objective introduced the cube system is to describe how the hydrology data will be store and retrieve in relational database. However, it is still lacking to handle a large amount of data. Thus, this paper proposed an Equijoin Optimization Technique to solve that problem. This technique was introduced based on modification of an equijoin method where an entity will be joined based on equijoin algorithm. In other words, the result relation is a new entity, T, contains tuples t made up of two tuples r and s, where r must be tuple in entity R and s must be tuple in entity S. Then, there are entity will be classified to other entity based on the appropriate attribute. Based on this technique, a SQL statement was created for data retrieval processing which is referring to the optimized entity. There are four main function in that process i) Select ii) Initialize iii) Operation and iv) Output. Also, in this research, testing and comparison analysis has been done between proposed technique, an Equijoin optimization and the previous technique MHIS Cube System. The result of the testing shows that the proposed technique can improve an execution time for query processing, then solve the issue has been discussed on this research
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