Matakuliah
Tahun
Versi
: T0234 / Sistem Informasi Geografis
: 2005
: 01/revisi 1
Pertemuan 05
Kualitas Data untuk SIG
1
Learning Outcomes
Pada akhir pertemuan ini, diharapkan mahasiswa
akan mampu :
• Menyesuaikan kualitas data yang
diperlukan dalam suatu aplikasi SIG
(C3, TIK05)
2
Outline Materi
• Materi 1 : Kualitas data untuk SIG
• Materi 2 : Errors pada SIG
3
Kualitas Data (1)
• Kualitas data
• Representation Affect
• Data sets for analysis
Kualitas data :
• Accuracy : Estimated data value approaches its true
value (Aronoff, 1989)
• Precision : Recorded level of detail of your data
• Bias : Systematic variation of data from reality
• Error : Physical difference between the real world and
the GIS data
4
Kualitas Data (2)
Representation Affect :
• Resolution : Describe the smallest feature in a data set
that can be displayed or mapped
• Generalization : Process of simplifying the complexities
of the real word to produce scale models and maps
Data sets for analysis :
•
•
•
•
Complete
Compatible
Consistent
Applicable
5
Error (1)
Jenis Error :
• Errors arising from our understanding & modelling of
reality
• Errors in source data for GIS
• Error in data encoding
• Error in data editing & Conversion
• Errors in data processing & analysis
• Errors in data output
6
Error (2)
Penanganan Error :
• Checking for errors
• Error Modeling
• Penanganan Errors
Checking for errors :
• Visual inspection
• Double digitizing
• Statistical Methods
7
Error (3)
Error Modeling :
• Epsilon Modeling
Based on an old method of line generalization developed by
Perkal (1956).
Blakemore (1984) adapted this idea by using the model to
define an error band about a digitized line that described the
probable distribution of digitizing error about the true line.
The epsilon model has been developed in various ways and with
various error distribution to produce a seemingly robust
means of error modeling.
• Monte Carlo Simulation
Simulates the effect of input data error by the addition of random
'noise' to the line coordinates in map data.
8
Error (4)
Penanganan Errors :
• Must track & document them
• Construct a data lineage
LINEAGE : A record of data history that presents
essential information about the development of data
from their source to their present format. Lineage
information should provide the data user with details of
their source, method of data capture, data model,
stages of transformation, editing and manipulation,
known errors and software and hardware used.
– Basic lineage requirements
– Benefits of lineage
• Repeatability
9
Error (5)
Basic Lineage requirements :
•
•
•
•
Description of source data
Transformation Document
Input / Output Specifications
Application-dependent information
Benefits of Lineage
•
•
•
•
Error detection
Management accountability
External Accountability
Quality Reporting
10
Penutup
• Mahasiswa diharapkan telah mampu
menyesuaikan kualitas data yang diperlukan
dalam suatu aplikasi SIG.
11