scholarly journals A BIM-Integrated Relational Database Management System for Evaluating Building Life-Cycle Costs

2020 ◽  
Vol 24 (2) ◽  
pp. 75-86
Author(s):  
Hang Thu Thi Le ◽  
Veerasak Likhitruangsilp ◽  
Nobuyoshi Yabuki
Keyword(s):  
Life Cycle ◽  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Database Management System ◽  
Life Cycle Costs ◽  
Relational Database Management System ◽  
Building Life Cycle ◽  
Relational Database Management

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

2022 ◽  
Vol 2 (1) ◽  
pp. 84-91
Author(s):  
Bayu Febriadi Bayu Febriadi ◽  
Pandu Pratama Putra
Keyword(s):  
Life Cycle ◽  
Relational Database ◽  
Management System ◽  
Database Management ◽  
System Development ◽  
Database Management System ◽  
Relational Database Management System ◽  
Development Life Cycle ◽  
Relational Database Management

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

A RELATIONAL DATABASE MANAGEMENT SYSTEM FOR LIFE-CYCLE COST ANALYSIS OF BIM PROJECTS

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Veerarsak Likhitruangsilp ◽  
Hang T. T. Le ◽  
Nobuyoshi Yabuki ◽  
Photios G. Ioannou
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Database Management System ◽  
Information Modeling ◽  
Quality Data ◽  
Relational Database Management System ◽  
Relational Database Management

Life-cycle analysis (LCCA) has become a necessary tool for green procurement for construction projects in many countries. Calculating life-cycle costs (LCCs) requires a variety of data that need to be gathered from diverse sources throughout the project life span. This information is usually stored in paper-based documents and are not well organized. These practices cause poor-quality data, which lead to incorrect results. Consequently, current LCCA in practice is extremely challenging. Data management is a major component for executing this sustainable development concept. This paper develops a relational database management system (RDBMS) that can support in calculating the LCCs of building projects. The system is structured to manage a large volume of design and construction data in a multi-parametric form. This allows users to integrate the proposed system with other modern construction platforms, especially building information modeling (BIM). In this paper, Autodesk Revit, a most widely-used BIM software, is adopted for authoring BIM models of a building and estimating relevant costs. Microsoft Access is used for developing a database management system (DBMS), which is designed to collaborate with the BIM models for LCCA. The system can significantly expedite the LCCA for a building with minimal errors and mistakes in data management and accurate LCCs.

Relational Database Management System

2021 ◽  
pp. 47-78
Author(s):  
Jagdish Chandra Patni ◽  
Hitesh Kumar Sharma ◽  
Ravi Tomar ◽  
Avita Katal
Keyword(s):  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Database Management System ◽  
Relational Database Management System ◽  
Relational Database Management

Automating Quality Oncology Practice Initiative Quality Measure NHL78a

2017 ◽  
pp. 1-6
Author(s):  
Richard Mansour ◽  
Samip Master
Keyword(s):  
Hepatitis B ◽  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Quality Measurement ◽  
Database Management System ◽  
Quality Measure ◽  
Relational Database Management System ◽  
Oncology Practice ◽  
Relational Database Management

Purpose Quality measurement and improvement is a focus of ASCO. In the era of electronic health records (EHRs), computerized order entry, and medication administration records, quality monitoring can be an automated process. The EHR data are usually stored within tables in a relational database management system. ASCO Quality Oncology Practice Initiative measure NHL78a (hepatitis B virus antigen test and hepatitis B core antibody test within 3 months before initiation of obinutuzumab, ofatumumab, or rituximab for patients with non-Hodgkin lymphoma) presents an opportunity for automation of a quality measure using existing data in the EHR. Methods We used a locally developed Structured Query Language (SQL) language procedure in the Microsoft SQL Query Manager to access the EPIC CLARITY database. Access to the relational database management system of the EHR permits rapid case identification (the denominator set) of the unique ID of all of the patients who have received one of the target medications (ie, obinutuzumab, ofatumumab, or rituximab). Then, we went through a six-step process to find the number of patients who passed or failed the quality measure. Results When the final SQL procedure executes, it takes < 5 seconds to see the result set for a 12-month period. The procedure can be changed to incorporate a desired date range. Once the SQL procedure is created, there is essentially no labor and low costs to run the procedure at specific time intervals. Conclusion Our method of quality measurement using EHRs is cost effective, fast, and precise, and can be reproduced at other centers.

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