Analisis dan Perancangan Software Pengukuran Metrik Skala dan Kompleksitas Database Relasional

Database relasional merupakan database yang di dalamannya terdapat tabel-tabel yang berhubungan antar satu tabel dengan yang lainnya. Pada database relasi terdapat kompleksitas relasional database. Untuk dapat mengetahui nilai kompleksitas relational database, diperlukan perhitungan kompleksitas database terlebih dahulu. Pada perhitungan kompleksitas database cara perhitungannya cukup rumit apabila menggunakan perhitungan manual karena kita harus membandingkan dengan database lain, selain itu perhitungan manual juga membutuhkan waktu yang lama. Oleh karena itu, kami melakukan penelitian yang bertujuan untuk menghasilkan suatu software yang dapat menentukan nilai kompleksitas sebuah database dengan menggunakan metrik skala. Untuk menentukan nilai kompleksitas database di berikan bobot pada tiap tabel, kolom, primary key, foreign key, secondary key, tipe data, lebar data, relation yang kemudian di hitung dengan menggunakan rumus yang telah kami tentukan.

Analisis Aspek-Aspek Kualitas Skema Database Kepegawaian Untuk Optimalisasi Perekrutan Karyawan

Permasalahan manajemen kepegawaian pada Kantor Kementerian khususnya kantor Pekerjaan Umum adalah pada data kepegawaian, data pegawai yang di setiap tahunnya mengalami pengurangan dan penambahan, sehingga perlunya analisis data pegawai untuk mengetahui kebutuhan pegawai (SDM) tersebut sesuai dengan jabatan dan kebutuhan. Solusi dari permasalahan diatas yaitu menganalisa database yang lama dan merekomendasikan skema database yang baru dengan menganalisis dari aspek-aspek kualitas skema database untuk memberikan rekomendasi langkah yang sesuai kebutuhan kepegawaian khususnya pada data pegawai yang berhubungan dengan data pensiun dan data jabatan minimal 3 tahun yang sudah ada, agar tidak adanya tumpang tindih pegawai dalam satu unit dan agar mempermudah dalam mendata kebutuhan SDM untuk keperluan rekrutmen karyawan yang lebih seimbang, terstruktur, efektif dan efisien. Hasil dari menganalisa database kepegawaian ini menggunakan acuan dari aspek-aspek kualitas skema database yang meliputi kebenaran dengan belum ada kejelasan pada kepemilikan constraint, konsistensi penghapusan pada primary key yang berpengaruh ke foreign key dan relevansi masih diperlukan reference primary key ada parent table ke child table.Kata Kunci — kualitas, skema database, kepegawaian, optimalisasiPersonnel management problems in the Office of the Ministry especially the Public Works office are on staffing data, the data of employees in each year experience a reduction and addition, so the need for employee data analysis to determine the needs of employees (HR) in accordance with their position and needs. The solution to the above problems is analyzing the old database and recommending a new database scheme by analyzing the quality aspects of the database schema to provide recommendations for steps that suit staffing requirements, especially on employee data relating to pension data and minimum 3-year occupational data that already exists In order to avoid overlapping employees in one unit and to make it easier to record HR needs for more balanced, structured, effective and efficient employee recruitment needs. The results of analyzing this personnel database use references from database aspects that contain truth with no clarity on constraint ownership, consistency in primary keys related to foreign keys and relevance still requires primary key references there are parent tables to child tables.Keywords— quality, scheme database, employee, optimization

Ameliorated Methodology for Base Design in Information System

The pragmatic Information retrieval technique is providing the responses to the users’ query depending on their choice. The clients are struggling hard to comprehend the semantic within the reports. The data recovery within common language content isn't organized and could be semantically equivocal. The unstructured data may contain non-key attributes. The joint operation takes place between the primary key and foreign key of different tables. The foreign key of one table must be the primary key of another table is the most common in a database and heavily optimized. Join is used to connect rows in another table (or even in the same table) based on the arbitrary condition for structured data but what it for unstructured data to retrieve an information? Information containing an unstructured data and Non-key attributes needs the establishment of relation between Non-key attributes as well as Non-key joins. This paper proposes a data base design to retrieve information with Non-key attributes and representing the knowledge with decision tree. From the decision tree the semiotic is extracted i.e. path from root node to leaf node.

A Framework for Protecting Users' Privacy in Cloud

Data and document privacy concerns are increasingly important in the online world. In Cloud Computing, the story is the same, as the secure processing of personal data represents a huge challenge. The main focus is to preserve and protect personally identifiable information (PII) of individuals, customers, businesses, governments and organisations. The current use of anonymization techniques is not quite efficient because of its failure to use the structure of the datasets under consideration and inability to use a metric that balances the usefulness of information with privacy preservation. In this work, an adaptive lossy decomposition algorithm was developed for preserving privacy in cloud computing. The algorithm uses the foreign key associations to determine the generalizations possible for any attribute in the database. It generates penalties for each obscured attribute when sharing and proposes an optimal decomposition of the relation. Postgraduate database of Federal University of Agriculture, Abeokuta, Nigeria and Adult database provided at the UCIrvine Machine Learning Repository were used for the evaluation. The result shows a system that could be used to improve privacy in cloud computing.

A Framework for Protecting Users' Privacy in Cloud

Data and document privacy concerns are increasingly important in the online world. In Cloud Computing, the story is the same, as the secure processing of personal data represents a huge challenge. The main focus is to preserve and protect personally identifiable information (PII) of individuals, customers, businesses, governments and organisations. The current use of anonymization techniques is not quite efficient because of its failure to use the structure of the datasets under consideration and inability to use a metric that balances the usefulness of information with privacy preservation. In this work, an adaptive lossy decomposition algorithm was developed for preserving privacy in cloud computing. The algorithm uses the foreign key associations to determine the generalizations possible for any attribute in the database. It generates penalties for each obscured attribute when sharing and proposes an optimal decomposition of the relation. Postgraduate database of Federal University of Agriculture, Abeokuta, Nigeria and Adult database provided at the UCIrvine Machine Learning Repository were used for the evaluation. The result shows a system that could be used to improve privacy in cloud computing.