Data Refinement in a Market Research Applications’ Data Production Process

2005 ◽  
pp. 293-314
Author(s):  
Thomas Ruf ◽  
Thomas Kirsche
Keyword(s):  
Production Process ◽  
Market Research ◽  
Data Refinement ◽  
Data Production

scholarly journals Can citizen science complement official data sources that serve as evidence-base for policies and practice to improve water quality?

2020 ◽  
pp. 1-16
Author(s):  
Ariane König ◽  
Karl Pickar ◽  
Jacek Stankiewicz ◽  
Kristina Hondrila
Keyword(s):  
Water Quality ◽  
Production Process ◽  
Citizen Science ◽  
Policy Making ◽  
Evidence Base ◽  
Project Work ◽  
Evidence Based ◽  
Evidence Based Policy ◽  
Data Production ◽  
Official Data

Addressing environmental issues in policy making requires recognising these issues as part of a complex socio-ecological system. The evidence base for such policies and associated monitoring and implementation measures, as well as related official indicators, statistics and environmental accounts are receiving increasing attention. This paper explores the potential of citizen science as a non-traditional source of data to complement the current data production process for evidence-based policy-making, using pollution of surface waters and its effect on associated ecosystems as an example. The paper develops a framework that helps to explore the official data production process in relation to different purposes of environmental policies. This highlights different challenges that the current official data production process sees itself confronted with in relation to the different purposes of the policies and associated monitoring regimes. These questions are explored with reference to the case of evidence-based policy making on water quality of surface freshwater in the EU, with a focus on Luxembourg. The analysis is based on extensive documentary analysis and literature review, as well as a series of interviews and participatory workshops with various stakeholders, and first results of a pilot project work with engaged citizen volunteers to solicit data on water quality with a focus on its nutrient content. On this basis, this paper argues that citizen science has the clear potential to meaningfully contribute both to the evidence base for policy and practice, as well as to an improved governance process.

eMaintenance ontologies for data quality support

2015 ◽  
Vol 21 (3) ◽  
pp. 358-374 ◽  
Author(s):  
Mustafa Aljumaili ◽  
Karina Wandt ◽  
Ramin Karim ◽  
Phillip Tretten
Keyword(s):  
Data Quality ◽  
Production Process ◽  
Quality Data ◽  
Literature Study ◽  
High Quality ◽  
Control Data ◽  
Management Tools ◽  
High Quality Data ◽  
Content Type ◽  
Data Production

Purpose – The purpose of this paper is to explore the main ontologies related to eMaintenance solutions and to study their application area. The advantages of using these ontologies to improve and control data quality will be investigated. Design/methodology/approach – A literature study has been done to explore the eMaintenance ontologies in the different areas. These ontologies are mainly related to content structure and communication interface. Then, ontologies will be linked to each step of the data production process in maintenance. Findings – The findings suggest that eMaintenance ontologies can help to produce a high-quality data in maintenance. The suggested maintenance data production process may help to control data quality. Using these ontologies in every step of the process may help to provide management tools to provide high-quality data. Research limitations/implications – Based on this study, it can be concluded that further research could broaden the investigation to identify more eMaintenance ontologies. Moreover, studying these ontologies in more technical details may help to increase the understandability and the use of these standards. Practical implications – It has been concluded in this study that applying eMaintenance ontologies by companies needs additional cost and time. Also the lack or the ineffective use of eMaintenance tools in many enterprises is one of the limitations for using these ontologies. Originality/value – Investigating eMaintenance ontologies and connecting them to maintenance data production is important to control and manage the data quality in maintenance.

scholarly journals OPTIMIZATION OF LAMPUNG BATIK PRODUCTION USING THE SIMPLEX METHOD

2021 ◽  
Vol 15 (2) ◽  
pp. 297-304
Author(s):  
Ahmad Ari Aldino ◽  
Marchamah Ulfa
Keyword(s):  
Production Process ◽  
Simplex Method ◽  
Raw Material ◽  
Time Data ◽  
Total Cost ◽  
Price Comparison ◽  
Profit Optimization ◽  
Data Production ◽  
Excel Solver ◽  
Python Programming

The Production and Profit optimization application in this Batik company was built to solve their problems. This application has the ability to process raw material data, working time data, production requirements data and load data for optimization calculations. The basis for calculations carried out includes optimization calculations using the Simplex Method and the tools used are Excel Solver and Python Programming. The output of this application is that how many Batik are produced based on available resources, the total cost of expenses incurred during the production process as well as gross profit and net of sales. This application can increase company profits and the percentage level of profit depending on the price comparison of sales between one product to another

scholarly journals QUALITY CONTROL ANALYSIS WITH SIX SIGMA-DMAIC METHOD IN EFFORT REDUCE NUMBER OF SUGAR PRODUCTS AT PT. PG. GORONTALO

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Ida Ayu Nuh Kartini ◽  
Dwi Jayanthi Syarief
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Six Sigma ◽  
Human Factor ◽  
Control Analysis ◽  
Quality Control Analysis ◽  
Data Production ◽  
Quality Of Products ◽  
Dmaic Method

Companies need to maintain and improve the quality of products derived by applying a good quality control, because quality is an important factor in improving satisfaction and loyalityas consumers, as well as PT. PG .Gorontalo ; Six Sigma methods that have high discipline can help develop and deliver near-perfect products. The purpose of this study was to determine how the value of sigma PT .PG . Gorontalo and what factors of product defects. In this analyzis , researchers took 3 months of data production and analyze the Six Sigma DMAIC method. Researchers examined / analyzed using a questionnaire and the report of production to help get the material of analyzis. From this research , it has been showed that the presence of defects of products in the production process of PT. PG. Gorontalo at 5.664, 72 DPMO. It is also known that the cause is the human factor , machines, methods, materials, and environment. Based on these results , we can conclude that the value of sigma PT. PG. Gorontalo is located at 4 to 4.5 sigma, the factor most dominant cause of disability is due to lack of proper vacuum pressure

Optimization of the production process of special purpose pasta with the addition of carrots and pectin

2019 ◽  
Vol 28 (9) ◽  
pp. 50-53
Author(s):  
N.N. Martynov ◽  
◽  
G.A. Sidorenko ◽  
G.B. Zinyukhin ◽  
E.Sh. Maneeva ◽  
...  
Keyword(s):  
Production Process

IMPLEMENTASI JOB ORDER COSTING METHOD DALAM PERHITUNGAN HARGA POKOK PRODUKSI MAP

2018 ◽  
Vol 4 (2) ◽  
pp. 43-55
Author(s):  
Ika Yulianti ◽  
Endah Masrunik ◽  
Anam Miftakhul Huda ◽  
Diana Elvianita
Keyword(s):  
Production Process ◽  
Quantitative Data ◽  
Production Cost ◽  
Qualitative Data ◽  
Cost Data ◽  
Method Calculation ◽  
Cost Of Production ◽  
The Right ◽  
The Cost

This study aims to find a comparison of the calculation of the cost of goods manufactured in the CV. Mitra Setia Blitar uses the company's method and uses the Job Order Costing (JOC) method. The method used in this study is quantitative. The types of data used are quantitative and qualitative. Quantitative data is in the form of map production cost data while qualitative data is in the form of information about map production process. The result of calculating the cost of production of the map between the two methods results in a difference of Rp. 306. Calculation using the company method is more expensive than using the Job Order Costing method. Calculation of cost of goods manufactured using the company method is Rp. 2,205,000, - or Rp. 2,205, - each unit. While using the Job Order Costing (JOC) method is Rp. 1,899,000, - or Rp 1,899, - each unit. So that the right method used in calculating the cost of production is the Job Order Costing (JOC) method

PENETAPAN KEBIJAKAN PERIKLANAN ATAS DASAR PERILAKU KONSUMEN (Studi Kasus : Produk Shampoo)

2018 ◽  
Vol 1 (01) ◽  
pp. 01
Author(s):  
Ismulyana Djan
Keyword(s):  
Consumer Behavior ◽  
Market Research ◽  
Advertising Effectiveness ◽  
Target Market

There are three things that should be into consideration in advertising certain product, ic,; the extent of similar products advertised at the same target market and media, cost of advertising, and difficulty in measuring advertising effectiveness. These three factors force management people to launch a market research concerning consumer behavior.Research carried out on 110 respondent asking them to mention: the brand of shampoo they used from ten different alternatives, seven usefulness of that product, and the kind of advertising media that is most often seen, heard, or read, shows that advertising shampoo product should pay attention to the: characteristic of the shampoo user, objective of advertising, target market to be achieved, advertising theme, press media used, and coordination with other marketing factors.That conclusion become the basic formulation on considering advertising policy of shampoo product that pay attention to consumer behavior.

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