<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="ms">
<Esri>
<CreaDate>20240916</CreaDate>
<CreaTime>14195800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="TRUE">DBO.PS02_trend_jenayah2019_2024</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<itemSize Sync="TRUE">0.000</itemSize>
<itemLocation>
<linkage Sync="TRUE">Server=10.29.57.215; Service=sde:sqlserver:10.29.57.215; Database=prod_muo; User=sa; Version=dbo.DEFAULT</linkage>
<protocol Sync="TRUE">ArcSDE Connection</protocol>
</itemLocation>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_WGS_1984</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<peXml Sync="TRUE">&lt;ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&amp;quot;,GEOGCS[&amp;quot;GCS_WGS_1984&amp;quot;,DATUM[&amp;quot;D_WGS_1984&amp;quot;,SPHEROID[&amp;quot;WGS_1984&amp;quot;,6378137.0,298.257223563]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Mercator_Auxiliary_Sphere&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,0.0],PARAMETER[&amp;quot;False_Northing&amp;quot;,0.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,0.0],PARAMETER[&amp;quot;Standard_Parallel_1&amp;quot;,0.0],PARAMETER[&amp;quot;Auxiliary_Sphere_Type&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,3857]]&lt;/WKT&gt;&lt;XOrigin&gt;-20037700&lt;/XOrigin&gt;&lt;YOrigin&gt;-30241100&lt;/YOrigin&gt;&lt;XYScale&gt;10000&lt;/XYScale&gt;&lt;ZOrigin&gt;0&lt;/ZOrigin&gt;&lt;ZScale&gt;1&lt;/ZScale&gt;&lt;MOrigin&gt;0&lt;/MOrigin&gt;&lt;MScale&gt;1&lt;/MScale&gt;&lt;XYTolerance&gt;0.001&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;WKID&gt;102100&lt;/WKID&gt;&lt;LatestWKID&gt;3857&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
<projcsn Sync="TRUE">WGS_1984_Web_Mercator_Auxiliary_Sphere</projcsn>
</coordRef>
<lineage>
<Process Date="20200103" Time="134109" ToolSource="c:\program files (x86)\arcgis\desktop10.2\ArcToolbox\Toolboxes\Data Management Tools.tbx\Dissolve">Dissolve PENGUNAAN_JENIS_BEKALAN_AIR_2014_2016 S:\PROJECT2019\GIS_W_2019_RFN4\MY_GIS_RFN4\DATA_FOR_KARTO\MY_NEGERI_POLY.shp NEGERI # MULTI_PART DISSOLVE_LINES</Process>
<Process Date="20201118" Time="115046" ToolSource="c:\program files (x86)\arcgis\desktop10.5\ArcToolbox\Toolboxes\Data Management Tools.tbx\Project">Project NEGERI C:\Users\HQL\Documents\ArcGIS\Default.gdb\NEGERI_Project GEOGCS['GCS_GDM_2000',DATUM['D_GDM_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] 'Kertau_To_WGS_1984 + MRT48-GDM2000' GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] NO_PRESERVE_SHAPE # NO_VERTICAL</Process>
<Process Date="20201123" Time="110809" ToolSource="c:\program files (x86)\arcgis\desktop10.5\ArcToolbox\Toolboxes\Data Management Tools.tbx\CalculateField">CalculateField NEGERI NAMA [NEGERI] VB #</Process>
<Process Date="20220513" Time="105947" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\CopyFeatures">CopyFeatures NEGERI C:\Users\Map2u_Shaili\Desktop\RFN4_2020_GDB\01_PENTADBIRAN\PENTADBIRAN.gdb\NEGERI # # # #</Process>
<Process Date="20240916" Name="Export Features" Time="141957" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Conversion Tools.tbx\ExportFeatures">ExportFeatures C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb\Sempadan_Negeri # NOT_USE_ALIAS "FCODE "FCODE" true true false 6 Text 0 0,First,#,C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI,FCODE,0,5;KOD_NEGERI "KOD_NEGERI" true true false 2 Text 0 0,First,#,C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI,KOD_NEGERI,0,1;LUAS_HA "LUAS_HA" true true false 4 Float 0 0,First,#,C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI,LUAS_HA,-1,-1;NAMA "NAMA" true true false 30 Text 0 0,First,#,C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI,NAMA,0,29;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,C:\Users\shail\OneDrive\Desktop\MUO\DATA\RFN\GIS_DB_RFN4_2020\PENTADBIRAN.gdb\NEGERI,Shape_Area,-1,-1" #</Process>
<Process Date="20240916" Name="Project" Time="141958" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\Project">Project C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb\Sempadan_Negeri C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb\Negeri GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]] 'GDM2000 To WGS84' GEOGCS["GCS_GDM_2000",DATUM["D_GDM_2000",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]] NO_PRESERVE_SHAPE # NO_VERTICAL</Process>
<Process Date="20240916" Name="Join Field" Time="142000" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\JoinField">JoinField C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb\Negeri KOD_NEGERI addjoinjenayah.csv "Kod Negeri" Tahun;Negeri;'Kod Negeri';'Kes Jenayah Kekerasan';'Jenayah Harta Benda';'Peratusan Insiden Kemiskinan Mutlak';'Peratusan Insiden Kemiskinan Relatif';'Peratusan Insiden Kemiskinan Tegar';'Kemudahan keselamatan';CCTV;'Tiada Pendidikan Formal';'Tahap Pendidikan Sekolah Rendah';'Tahap Pendidikan Sekolah Menengah';'Tahap Pendidikan Pengajian Tinggi';'Pendapatan Isi Rumah';'Bilangan Penganggur';'Keluasan Tepu Bina';'bilangan penduduk';'warga asing';'kos sara hidup' "Select transfer fields" # "Do not add indexes"</Process>
<Process Date="20240916" Time="144828" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\UpdateSchema">UpdateSchema "CIMDATA=&lt;CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'&gt;&lt;WorkspaceConnectionString&gt;DATABASE=C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb&lt;/WorkspaceConnectionString&gt;&lt;WorkspaceFactory&gt;FileGDB&lt;/WorkspaceFactory&gt;&lt;Dataset&gt;Negeri&lt;/Dataset&gt;&lt;DatasetType&gt;esriDTFeatureClass&lt;/DatasetType&gt;&lt;/CIMStandardDataConnection&gt;" &lt;operationSequence&gt;&lt;workflow&gt;&lt;DeleteField&gt;&lt;field_name&gt;Tahun&lt;/field_name&gt;&lt;field_name&gt;Negeri&lt;/field_name&gt;&lt;field_name&gt;Kod_Negeri_1&lt;/field_name&gt;&lt;field_name&gt;Kes_Jenayah_Kekerasan&lt;/field_name&gt;&lt;field_name&gt;Jenayah_Harta_Benda&lt;/field_name&gt;&lt;field_name&gt;Peratusan_Insiden_Kemiskinan_Mutlak&lt;/field_name&gt;&lt;field_name&gt;Peratusan_Insiden_Kemiskinan_Relatif&lt;/field_name&gt;&lt;field_name&gt;Peratusan_Insiden_Kemiskinan_Tegar&lt;/field_name&gt;&lt;field_name&gt;Kemudahan_keselamatan&lt;/field_name&gt;&lt;field_name&gt;CCTV&lt;/field_name&gt;&lt;field_name&gt;Tiada_Pendidikan_Formal&lt;/field_name&gt;&lt;field_name&gt;Tahap_Pendidikan_Sekolah_Rendah&lt;/field_name&gt;&lt;field_name&gt;Tahap_Pendidikan_Sekolah_Menengah&lt;/field_name&gt;&lt;field_name&gt;Tahap_Pendidikan_Pengajian_Tinggi&lt;/field_name&gt;&lt;field_name&gt;Pendapatan_Isi_Rumah&lt;/field_name&gt;&lt;field_name&gt;Bilangan_Penganggur&lt;/field_name&gt;&lt;field_name&gt;Keluasan_Tepu_Bina&lt;/field_name&gt;&lt;field_name&gt;bilangan_penduduk&lt;/field_name&gt;&lt;field_name&gt;warga_asing&lt;/field_name&gt;&lt;field_name&gt;kos_sara_hidup&lt;/field_name&gt;&lt;/DeleteField&gt;&lt;/workflow&gt;&lt;/operationSequence&gt;</Process>
<Process Date="20240916" Name="Join Field" Time="144948" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\JoinField">JoinField C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb\Negeri KOD_NEGERI C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb\CombineNegeri negeri_code Tahun;Negeri;negeri_code;Kes_Jenayah_Kekerasan;Jenayah_Harta_Benda;Peratusan_Insiden_Kemiskinan_Mutlak;Peratusan_Insiden_Kemiskinan_Relatif;Peratusan_Insiden_Kemiskinan_Tegar;Kemudahan_keselamatan;CCTV;Tiada_Pendidikan_Formal;Tahap_Pendidikan_Sekolah_Rendah;Tahap_Pendidikan_Sekolah_Menengah;Tahap_Pendidikan_Pengajian_Tinggi;Pendapatan_Isi_Rumah;Bilangan_Penganggur;Keluasan_Tepu_Bina;bilangan_penduduk;warga_asing;kos_sara_hidup "Select transfer fields" # "Do not add indexes"</Process>
<Process Date="20240916" Time="145108" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\UpdateSchema">UpdateSchema "CIMDATA=&lt;CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'&gt;&lt;WorkspaceConnectionString&gt;DATABASE=C:\Users\shail\OneDrive\Desktop\baru\Final\PublishTablePvalue.gdb&lt;/WorkspaceConnectionString&gt;&lt;WorkspaceFactory&gt;FileGDB&lt;/WorkspaceFactory&gt;&lt;Dataset&gt;Negeri&lt;/Dataset&gt;&lt;DatasetType&gt;esriDTFeatureClass&lt;/DatasetType&gt;&lt;/CIMStandardDataConnection&gt;" &lt;operationSequence&gt;&lt;workflow&gt;&lt;DeleteField&gt;&lt;field_name&gt;Tahun&lt;/field_name&gt;&lt;field_name&gt;Negeri&lt;/field_name&gt;&lt;field_name&gt;negeri_code&lt;/field_name&gt;&lt;field_name&gt;Kes_Jenayah_Kekerasan&lt;/field_name&gt;&lt;field_name&gt;Jenayah_Harta_Benda&lt;/field_name&gt;&lt;field_name&gt;Peratusan_Insiden_Kemiskinan_Mutlak&lt;/field_name&gt;&lt;field_name&gt;Peratusan_Insiden_Kemiskinan_Relatif&lt;/field_name&gt;&lt;field_name&gt;Peratusan_Insiden_Kemiskinan_Tegar&lt;/field_name&gt;&lt;field_name&gt;Kemudahan_keselamatan&lt;/field_name&gt;&lt;field_name&gt;CCTV&lt;/field_name&gt;&lt;field_name&gt;Tiada_Pendidikan_Formal&lt;/field_name&gt;&lt;field_name&gt;Tahap_Pendidikan_Sekolah_Rendah&lt;/field_name&gt;&lt;field_name&gt;Tahap_Pendidikan_Sekolah_Menengah&lt;/field_name&gt;&lt;field_name&gt;Tahap_Pendidikan_Pengajian_Tinggi&lt;/field_name&gt;&lt;field_name&gt;Pendapatan_Isi_Rumah&lt;/field_name&gt;&lt;field_name&gt;Bilangan_Penganggur&lt;/field_name&gt;&lt;field_name&gt;Keluasan_Tepu_Bina&lt;/field_name&gt;&lt;field_name&gt;bilangan_penduduk&lt;/field_name&gt;&lt;field_name&gt;warga_asing&lt;/field_name&gt;&lt;field_name&gt;kos_sara_hidup&lt;/field_name&gt;&lt;/DeleteField&gt;&lt;/workflow&gt;&lt;/operationSequence&gt;</Process>
<Process Date="20240917" Time="143304" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Conversion Tools.tbx\ExportFeatures">ExportFeatures "ModelBuilder\Negeri (3):Negeri" C:\Users\shail\OneDrive\Desktop\baru\Final\Processing_Jenayah.gdb\Negeri_WGS1984 # NOT_USE_ALIAS "FCODE "FCODE" true true false 6 Text 0 0,First,#,ModelBuilder\Negeri (3):Negeri,FCODE,0,5;KOD_NEGERI "KOD_NEGERI" true true false 2 Text 0 0,First,#,ModelBuilder\Negeri (3):Negeri,KOD_NEGERI,0,1;LUAS_HA "LUAS_HA" true true false 4 Float 0 0,First,#,ModelBuilder\Negeri (3):Negeri,LUAS_HA,-1,-1;NAMA "NAMA" true true false 30 Text 0 0,First,#,ModelBuilder\Negeri (3):Negeri,NAMA,0,29;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,ModelBuilder\Negeri (3):Negeri,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,ModelBuilder\Negeri (3):Negeri,Shape_Area,-1,-1" #</Process>
<Process Date="20240917" Name="Export Features (3)" Time="144008" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Conversion Tools.tbx\ExportFeatures">ExportFeatures Negeri_WGS1984_Layer C:\Users\shail\OneDrive\Desktop\baru\Final\Processing_Jenayah.gdb\Pencegahan_Jenayah2019_2024 # NOT_USE_ALIAS "FCODE "FCODE" true true false 6 Text 0 0,First,#,Negeri_WGS1984_Layer,Negeri_WGS1984.FCODE,0,5;KOD_NEGERI "KOD_NEGERI" true true false 2 Text 0 0,First,#,Negeri_WGS1984_Layer,Negeri_WGS1984.KOD_NEGERI,0,1;LUAS_HA "LUAS_HA" true true false 4 Float 0 0,First,#,Negeri_WGS1984_Layer,Negeri_WGS1984.LUAS_HA,-1,-1;NAMA "NAMA" true true false 30 Text 0 0,First,#,Negeri_WGS1984_Layer,Negeri_WGS1984.NAMA,0,29;Kon "Kon" true true false 50 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Kon,0,49;Tahun "Tahun" true true false 255 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Tahun,0,254;JenKat "JenKat" true true false 255 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.JenKat,0,254;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.FREQUENCY,-1,-1;COUNT_Kon "COUNT_Kon" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.COUNT_Kon,-1,-1;COUNT_Tahun "COUNT_Tahun" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.COUNT_Tahun,-1,-1;Data_Asal "Data_Asal" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Data_Asal,-1,-1;kod "kod" true true false 255 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.kod,0,254;NAMA "NAMA" true true false 30 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.NAMA,0,29;Negeri "Negeri" true true false 8000 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Negeri,0,7999;Kod_Negeri_1 "Kod Negeri" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Kod_Negeri_1,-1,-1;bilangan_penduduk "bilangan penduduk" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.bilangan_penduduk,-1,-1;negeri_code "negeri_code" true true false 255 Text 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.negeri_code,0,254;Anggaran_Penjenayah "Anggaran_Penjenayah" true true false 8 Double 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Anggaran_Penjenayah,-1,-1;Data_Join "Data_Join" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Data_Join,-1,-1;Julat_Jenayah "Julat_Jenayah" true true false 0 Double 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Julat_Jenayah,-1,-1;Peratusan_Perubahan "Peratusan_Perubahan" true true false 0 Double 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.Peratusan_Perubahan,-1,-1;COUNT_JenKat "COUNT_JenKat" true true false 4 Long 0 0,First,#,Negeri_WGS1984_Layer,Jenayah19_24.COUNT_JenKat,-1,-1" #</Process>
<Process Date="20240918" Time="091755" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Conversion Tools.tbx\ExportFeatures">ExportFeatures Pencegahan_Jenayah2019_2024 C:\Users\shail\OneDrive\Desktop\baru\PublishToKet\Pencegahan_Jenayah.gdb\Pencegahan_Jenayah2019_2024 # NOT_USE_ALIAS "FCODE "FCODE" true true false 6 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,FCODE,0,5;KOD_NEGERI "KOD_NEGERI" true true false 2 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,KOD_NEGERI,0,1;LUAS_HA "LUAS_HA" true true false 4 Float 0 0,First,#,Pencegahan_Jenayah2019_2024,LUAS_HA,-1,-1;NAMA "NAMA" true true false 30 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,NAMA,0,29;Kon "Kon" true true false 50 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,Kon,0,49;Tahun "Tahun" true true false 255 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,Tahun,0,254;JenKat "JenKat" true true false 255 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,JenKat,0,254;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,FREQUENCY,-1,-1;COUNT_Kon "COUNT_Kon" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,COUNT_Kon,-1,-1;COUNT_Tahun "COUNT_Tahun" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,COUNT_Tahun,-1,-1;Data_Asal "Data_Asal" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,Data_Asal,-1,-1;kod "kod" true true false 255 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,kod,0,254;NAMA_1 "NAMA" true true false 30 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,NAMA_1,0,29;Negeri "Negeri" true true false 8000 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,Negeri,0,7999;Kod_Negeri_1 "Kod Negeri" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,Kod_Negeri_1,-1,-1;bilangan_penduduk "bilangan penduduk" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,bilangan_penduduk,-1,-1;negeri_code "negeri_code" true true false 255 Text 0 0,First,#,Pencegahan_Jenayah2019_2024,negeri_code,0,254;Anggaran_Penjenayah "Anggaran_Penjenayah" true true false 8 Double 0 0,First,#,Pencegahan_Jenayah2019_2024,Anggaran_Penjenayah,-1,-1;Data_Join "Data_Join" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,Data_Join,-1,-1;Julat_Jenayah "Julat_Jenayah" true true false 8 Double 0 0,First,#,Pencegahan_Jenayah2019_2024,Julat_Jenayah,-1,-1;Peratusan_Perubahan "Peratusan_Perubahan" true true false 8 Double 0 0,First,#,Pencegahan_Jenayah2019_2024,Peratusan_Perubahan,-1,-1;COUNT_JenKat "COUNT_JenKat" true true false 4 Long 0 0,First,#,Pencegahan_Jenayah2019_2024,COUNT_JenKat,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Pencegahan_Jenayah2019_2024,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,Pencegahan_Jenayah2019_2024,Shape_Area,-1,-1" #</Process>
<Process Date="20240918" Time="092136" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\Rename">Rename C:\Users\shail\OneDrive\Desktop\baru\PublishToKet\Pencegahan_Jenayah.gdb\Pencegahan_Jenayah2019_2024 C:\Users\shail\OneDrive\Desktop\baru\PublishToKet\Pencegahan_Jenayah.gdb\Trend_Jenayah2019_2024 FeatureClass</Process>
<Process Date="20240918" Time="101116" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\CopyFeatures">CopyFeatures PS02_trend_jenayah2019_2024 "C:\Users\ADMIN 10\Documents\ArcGIS\Projects\PUBLISH STAGING\SQLServer-10-prod_muo(sa).sde\DBO.PS02_pencegahan_jenayah\DBO.PS02_trend_jenayah2019_2024" # # # #</Process>
</lineage>
</DataProperties>
<SyncDate>20240918</SyncDate>
<SyncTime>10110700</SyncTime>
<ModDate>20240918</ModDate>
<ModTime>10110700</ModTime>
</Esri>
<dataIdInfo>
<envirDesc Sync="TRUE">Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.2.0.49743</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="MYS"/>
</dataLang>
<idCitation>
<resTitle Sync="TRUE">PS02_trend_jenayah2019_2024</resTitle>
<presForm>
<PresFormCd Sync="TRUE" value="005"/>
</presForm>
</idCitation>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="001"/>
</spatRpType>
<idAbs/>
<searchKeys>
<keyword>PS02</keyword>
<keyword>trend_jenayah</keyword>
<keyword>2019</keyword>
<keyword>2024</keyword>
<keyword>analitik perancangan sosial</keyword>
</searchKeys>
<idPurp>Trend Jenayah Bagi Setiap Negeri di Malaysia (Termasuk Sabah dan Sarawak) pada Tahun 2019 Hingga ke Tahun 2024</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<mdLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="MYS"/>
</mdLang>
<mdChar>
<CharSetCd Sync="TRUE" value="004"/>
</mdChar>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Enterprise Geodatabase Feature Class</formatName>
</distFormat>
<distTranOps>
<transSize Sync="TRUE">0.000</transSize>
</distTranOps>
</distInfo>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005"/>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="3857"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">6.18.3(9.3.1.2)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spatRepInfo>
<VectSpatRep>
<geometObjs Name="DBO.PS02_trend_jenayah2019_2024">
<geoObjTyp>
<GeoObjTypCd Sync="TRUE" value="002"/>
</geoObjTyp>
<geoObjCnt Sync="TRUE">0</geoObjCnt>
</geometObjs>
<topLvl>
<TopoLevCd Sync="TRUE" value="001"/>
</topLvl>
</VectSpatRep>
</spatRepInfo>
<spdoinfo>
<ptvctinf>
<esriterm Name="DBO.PS02_trend_jenayah2019_2024">
<efeatyp Sync="TRUE">Simple</efeatyp>
<efeageom Sync="TRUE" code="4"/>
<esritopo Sync="TRUE">FALSE</esritopo>
<efeacnt Sync="TRUE">0</efeacnt>
<spindex Sync="TRUE">TRUE</spindex>
<linrefer Sync="TRUE">FALSE</linrefer>
</esriterm>
</ptvctinf>
</spdoinfo>
<eainfo>
<detailed Name="DBO.PS02_trend_jenayah2019_2024">
<enttyp>
<enttypl Sync="TRUE">DBO.PS02_trend_jenayah2019_2024</enttypl>
<enttypt Sync="TRUE">Feature Class</enttypt>
<enttypc Sync="TRUE">0</enttypc>
</enttyp>
<attr>
<attrlabl Sync="TRUE">OBJECTID</attrlabl>
<attalias Sync="TRUE">OBJECTID</attalias>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Internal feature number.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape</attrlabl>
<attalias Sync="TRUE">Shape</attalias>
<attrtype Sync="TRUE">Geometry</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Feature geometry.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Coordinates defining the features.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">FCODE</attrlabl>
<attalias Sync="TRUE">FCODE</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">6</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">KOD_NEGERI</attrlabl>
<attalias Sync="TRUE">KOD_NEGERI</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">2</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">LUAS_HA</attrlabl>
<attalias Sync="TRUE">LUAS_HA</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">38</atprecis>
<attscale Sync="TRUE">8</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">NAMA</attrlabl>
<attalias Sync="TRUE">NAMA</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">30</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Kon</attrlabl>
<attalias Sync="TRUE">Kon</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Tahun</attrlabl>
<attalias Sync="TRUE">Tahun</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">JenKat</attrlabl>
<attalias Sync="TRUE">JenKat</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">FREQUENCY</attrlabl>
<attalias Sync="TRUE">FREQUENCY</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">COUNT_Kon</attrlabl>
<attalias Sync="TRUE">COUNT_Kon</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">COUNT_Tahun</attrlabl>
<attalias Sync="TRUE">COUNT_Tahun</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Data_Asal</attrlabl>
<attalias Sync="TRUE">Data_Asal</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">kod</attrlabl>
<attalias Sync="TRUE">kod</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">NAMA_1</attrlabl>
<attalias Sync="TRUE">NAMA</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">30</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Negeri</attrlabl>
<attalias Sync="TRUE">Negeri</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">1073741822</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Kod_Negeri_1</attrlabl>
<attalias Sync="TRUE">Kod Negeri</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">bilangan_penduduk</attrlabl>
<attalias Sync="TRUE">bilangan penduduk</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">negeri_code</attrlabl>
<attalias Sync="TRUE">negeri_code</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Anggaran_Penjenayah</attrlabl>
<attalias Sync="TRUE">Anggaran_Penjenayah</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">38</atprecis>
<attscale Sync="TRUE">8</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Data_Join</attrlabl>
<attalias Sync="TRUE">Data_Join</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Julat_Jenayah</attrlabl>
<attalias Sync="TRUE">Julat_Jenayah</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">38</atprecis>
<attscale Sync="TRUE">8</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Peratusan_Perubahan</attrlabl>
<attalias Sync="TRUE">Peratusan_Perubahan</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">38</atprecis>
<attscale Sync="TRUE">8</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">COUNT_JenKat</attrlabl>
<attalias Sync="TRUE">COUNT_JenKat</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape.STArea()</attrlabl>
<attalias Sync="TRUE">Shape.STArea()</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape.STLength()</attrlabl>
<attalias Sync="TRUE">Shape.STLength()</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<mdDateSt Sync="TRUE">20240918</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
</metadata>
