SOSIALISASI e-ARSIP SEBAGAI PENGOLAHAN DATA DINAS LUAR PADA KANTOR KESEHATAN PELABUHAN PEKANBARU

Kantor Kesehatan Pelabuhan (KKP) Pekanbaru merupakan Kantor pemerintahan yang bergerak di bidang kesehatan khususnya mengenai lingkungan. Dalam kegiatan dinas luar seperti surveilans kesehatan kapal, surveilans kesehatan masyarakat, bimbingan teknis, pengawasan dokumen kesehatan, surveilans faktor penyakit tidak menular pada kantor cabang kesehatan pelabuhan di provinsi riau seperti Kantor Selat Panjang, Kantor Tanjung Buton, Kantor Siak Sri Indrapura, Kantor Buatan, Kantor Sei. Duku, Kantor Kampung Dalam, kantor KKP Bangkinang dan Kantor Kuantan Singingi. Adapun pengolahan data masih belum teritegrasi dengan baik sehingga susah dalam melakukan pendataan dokumen dan informasi dari hasil kegiatan dinas luar, sementara pengadaan komputer dan sumber daya ada. Dan kegiatan ini selalu dilakukan tiap kegiatan sehingga diperlukan sebuah sistem yang dapat mengontrol data-data kegiatan dan dokumen yang dibutuhkan dalam pembuatan laporan kegiatan. Hal inilah yang menjadi ketertarikan penulis untuk membantu permasalahan yang dihadapi karyawan di Kantor Kesehatan Pelabuhan Pekanbaru supaya lebih efisien dalam menjalankan kegiatan. Relational Database management System (RDBMS) adalah kumpulan data yang disimpan secara sistematis di dalam komputer yang dapat diolah atau dimanipulasi menggunakan perangkat lunak (program aplikasi) untuk menghasilkan informasi. Dengan memanfaatkan teknologi informasi RDBMS sehingga aplikasi berbasis online dapat diakses kapan dan dimana saja dari tempat karyawan melakukan kegiatan dinas luar dapat langsung meng-input dan pengolahan data untuk penyajian informasi yang lebih cepat ke kantor pusat pelabuhan pekanbaru dan dengan pendekatan metode System development Life Cycle (SDLC) dalam penyelesaian masalah kegiatan dinas luar, sehingga diharapkan pengolahan data dapat terintegrasi dan lebih efisien dalam pendataan informasi, dengan demikian diharapkan dapat membantu pihak kantor dalam pengolahan data yang lebih efisien dan lebih aman khususnya dalam pengolahan data dinas luar pada kantor kesehatan pelabuhan pekanbaru

Big Data Analytics Using Apache Hive to Analyze Health Data

A large volume of data is stored electronically. It is very difficult to measure the total volume of that data. This large amount of data is coming from various sources such as stock exchange, which may generate terabytes of data every day, Facebook, which may take about one petabyte of storage, and internet archives, which may store up to two petabytes of data, etc. So, it is very difficult to manage that data using relational database management systems. With the massive data, reading and writing from and into the drive takes more time. So, the storage and analysis of this massive data has become a big problem. Big data gives the solution for these problems. It specifies the methods to store and analyze the large data sets. This chapter specifies a brief study of big data techniques to analyze these types of data. It includes a wide study of Hadoop characteristics, Hadoop architecture, advantages of big data and big data eco system. Further, this chapter includes a comprehensive study of Apache Hive for executing health-related data and deaths data of U.S. government.

Performance evaluation of various deployment scenarios of the 3-replicated Cassandra NoSQL cluster on AWS

A concept of distributed replicated NoSQL data storages Cassandra-like, HBase, MongoDB has been proposed to effectively manage Big Data set whose volume, velocity and variability are difficult to deal with by using the traditional Relational Database Management Systems. Tradeoffs between consistency, availability, partition tolerance and latency is intrinsic to such systems. Although relations between these properties have been previously identified by the well-known CAP and PACELC theorems in qualitative terms, it is still necessary to quantify how different consistency settings, deployment patterns and other properties affect system performance.This experience report analysis performance of the Cassandra NoSQL database cluster and studies the tradeoff between data consistency guaranties and performance in distributed data storages. The primary focus is on investigating the quantitative interplay between Cassandra response time, throughput and its consistency settings considering different single- and multi-region deployment scenarios. The study uses the YCSB benchmarking framework and reports the results of the read and write performance tests of the three-replicated Cassandra cluster deployed in the Amazon AWS. In this paper, we also put forward a notation which can be used to formally describe distributed deployment of Cassandra cluster and its nodes relative to each other and to a client application. We present quantitative results showing how different consistency settings and deployment patterns affect Cassandra performance under different workloads. In particular, our experiments show that strong consistency costs up to 22 % of performance in case of the centralized Cassandra cluster deployment and can cause a 600 % increase in the read/write requests if Cassandra replicas and its clients are globally distributed across different AWS Regions.

MzS Tools: GIS Methods and Tools for Seismic Microzonation Mapping

MzSTools is a plugin for QGIS developed by the National Research Council (CNR) as part of the activities concerning the coordination of seismic microzonation studies in Italy. It train from the need to create a practical and easy-to-use tool to carry out seismic microzonation (SM) studies by producing standards compliant geographic database and maps, thus making them accurate, homogeneous and uniform for all municipalities in Italy. A geodatabase based on SQLite/SpatiaLite Relational Database Management System (RDBMS). It has been designed to collect and store data related to elements such as: geognostic surveys; bedrocks and cover terrains; superficial and buried geomorphological elements; tectonic-structural elements; elements of geological instability such as landslide zones, liquefaction zones and zones affected by active and capable faults; homogeneous microzones in seismic perspective, microzones characterized by a seismic amplification factor. The QGIS plugin provides tools such as data entry forms designed with Qt Designer; a QGIS project template with layers, symbol libraries and graphic styles; layouts for the SM Maps. MzSTools assembles in a single software environment a set of useful tools for those who work in. The plugin is open source, whose code hosted on the GitHub platform, and is published via the official QGIS plugins repository (https://plugins.qgis.org/plugins/MzSTools/).

Pengembangan dan Validasi Rancang Bangun Sistem Informasi Surat Elektronik Poliklinik Berbasis Website

Polyclinic at State University of Padang is one of technical services unit or UPT that still uses manual system for documenting medical records and administration. The purpose of this project is to make a design about information system in polyclinic at State University of Padang. It will be an effective project for many activities and also for a process of health services, so that, all of activities in Polyclinic will being computerized. Beside of that, this system also uses online system that will help the patient in the clinic to get good services easily. The system of this design uses a PHP's programming language with Framework Codeigniter. Moreover, the design of this information system in the clinic also uses Relational Database Management System (RDBMS) MySQL. Designing and Planning this project uses Bootstrap CSS Framework that functioning to make the system more dynamist and responsive. The output of this project in the clinic at State University of Padang is a system that will fulfill the requirements of health services by an online system. And for an employee, this system is useful to make a monthly or yearly report, so that their job will be easier than before. However, the designing and planning of information systems in that clinic still needing a development in many aspects to get the maximum result. The development of this project will include such as a system or even the people around the clinic at State University of Padang.

Comparative Case Study Difference Between Azure Cloud SQL and Mongo Atlas MongoDB NoSQL Database

Azure SQL and Atlas Mongodb NoSQL(Azure instance) databases are the most popular, systematic process to database solutions. Which Azure SQL database is also referred to as RDBMS (Relational Database Management Systems). The data are structured into tables or associations. The Atlas Mongodb NoSQL database is called a non-relational database management systems. The data are included in unstructured tables or associations. In this research, evaluate both the Azure SQL and Atlas Mongodb NoSQL databases. During the experiment compare the loading time, response time, and retrieval time of both Azure SQL and Atlas Mongodb NoSQL databases, and justify which one is fast, efficient and better performance.