Professional Clustering Based on the Graduates Profile Using K-Means Method

The Information Systems department of Pelita Indonesia Institute of Business and Technology produces graduates with education knowledge to face the professional work, but the majority of students after graduating do not work according to their graduate profiles/educational background. This research aimed to help students in determining the appropriate graduate profile. The proposed system was built using the K-means method for the classification process of graduate profiles; hence, the results can be used as recommended profession to be taken. The data used in this study is the data of students of class 2016, and these results are compared with their current professional record data with the aim of knowing the percentage of professional suitability obtained with the current profession. After this research is tested, the results of the classification of the graduate profile can be obtained where there are 10 students in the administrator database cluster, 11 students of the web design and developer cluster, one student of the cluster information system manager, and 8 students of the cluster system analysis. The percentage of suitability was 43.33%. This program is designed using the PHP programming language.

Implementasi Sistem Database Terdistribusi Dengan Metode Multi-Master Database Replication

Databases are the main need for every computer application to store, process and modify data. One important problem faced in databases is the availability of adequate information technology infrastructure in managing and securing data contained in the database. Data stored on the database must have protection against threats and disturbances. Threats and disruptions can result from a variety of things, such as maintenance, data damage, and natural disasters. To anticipate data loss and damage, replication of the database system needs to be done. The replication mechanism used by researchers is multi-master replication. The replication technique is able to form a database cluster with replication time of fewer than 0.2 seconds.

AIM Data Services

AIM Data Services as a virtual facility provides virtual 3D reference tracks for simulation applications in the domain of automotive and railway systems. It offers tools for management and analysis of experiment data and a platform for survey and processing of vehicle data in the public transport domain. Collected spatial data is bundled in a database cluster and published through common web mapping interfaces.