Zt_1+et; , 1.00 , 0.70 Pendekatan Space Time Autoregressive (Star) Dan Generalized Space Time Autoregressive (Gstar) Melalui Metode Autoregressive (Ar) Dan Vector Autoregressive (Var).

Lampiran 2 Program SAS 9.3 pembangkitan data ordo waktu berbeda DATA Lokasi_1; Zt_1=RANNOR 1 ; Zt_2=RANNOR 2 ; DO i= - 50 TO 100 ; TIME=i; et=RANNORi; Zt1=

1.3 Zt_1 -

0.5 Zt_2 + et; IF i THEN OUTPUT ; Zt_2=Zt_1; Zt_1=Zt1; END ; RUN ; DATA Lokasi_2; Zt_1=RANNOR 123 ; DO i= - 50 TO 100 ; TIME=i; et=RANNORi; Zt2= 0.2 Zt_1+et; IF i THEN OUTPUT ; Zt_1=Zt2; END ; RUN ; DATA Lokasi_3; Zt_1=RANNOR 13 ; Zt_2=RANNOR 3 ; DO i= - 50 TO 100 ; TIME=i; et=RANNORi; Zt3=

1.6 Zt_1 -

0.8 Zt_2 + et; IF i THEN OUTPUT ; Zt_2=Zt_1; Zt_1=Zt3; END ; RUN ; DATA LOKASI_KORELASI; MERGE LOKASI_1 LOKASI_2 LOKASI_3; RUN ; PROC IML ; USE LOKASI_KORELASI; READ ALL VAR {Zt1 Zt2 Zt3} INTO Zt; K={

1.00 0.25

0.85 ,

0.25 1.00

0.70 ,

0.85 0.70

1.00 }; C=rootK; Y=ZtC; N=NROWY; T= 1 :N; Y1=Y[, 1 ]; Y2=Y[, 2 ]; Y3=Y[, 3 ]; CREATE SPACE VAR {T Y1 Y2 Y3}; APPEND ; QUIT ; Lampiran 3 Program Macro SAS 9.3 Perbandingan Kinerja Model Ordo Waktu Sama MACRO PERBANDINGAN; DO UL= 1 TO 100 ; DATA Lokasi_1; Zt_1=RANNOR ; DO i= - 50 TO 100 ; TIME=i; et=RANNOR ; Zt1= 0.6 Zt_1+et; IF i THEN OUTPUT; Zt_1=Zt1; END; RUN; DATA Lokasi_2; Zt_1=RANNOR ; DO i= - 50 TO 100 ; TIME=i; et=RANNOR ; Zt2= 0.7 Zt_1+et; IF i THEN OUTPUT; Zt_1=Zt2; END; RUN; DATA Lokasi_3; Zt_1=RANNOR ; DO i= - 50 TO 100 ; TIME=i; et=RANNOR ; Zt3= 0.8 Zt_1+et; IF i THEN OUTPUT; Zt_1=Zt3; END; RUN; DATA LOKASI_KORELASI; MERGE LOKASI_1 LOKASI_2 LOKASI_3; RUN; PROC IML; USE LOKASI_KORELASI; READ ALL VAR{Zt1 Zt2 Zt3} INTO Zt; K={

1.00 0.25

0.85 ,

0.25 1.00

0.70 ,

0.85 0.70

1.00 }; C=rootK; Y=ZtC; N=NROWY; T= 1 :N; Y1=Y[, 1 ]; Y2=Y[, 2 ]; Y3=Y[, 3 ]; CREATE SPACE VAR{T Y1 Y2 Y3}; APPEND; QUIT; DATA SPACE_1; SET SPACE; IF 1 = T = 90 THEN OUTPUT SPACE_1; RUN; DATA RAMAL_SPACE_1; SET SPACE; IF 91 = T = 100 THEN OUTPUT RAMAL_SPACE_1; RUN; PROC ARIMA DATA=SPACE_1; IDENTIFY VAR=Y1 MINIC STATIONARITY=adf= 1 NLAG= 15 SCAN; ESTIMATE P= 1 NOINT NOPRINT; FORECAST LEAD= 10 OUT=DUGAAN1 NOPRINT; RUN; PROC IML; USE RAMAL_SPACE_1; READ ALL VAR{Y1} INTO Y_AKTUAL; USE DUGAAN1; READ ALL VAR{FORECAST} INTO Y_DUGA; Y_DUGA=Y_DUGA[ 91 : 100 ,]; e=ABSY_AKTUAL-Y_DUGA; SSE=e`e; N=NROWY_DUGA; RMSE_LOKASI1=SQRT 1 NSSE; CREATE RMSE_AR_LOK1 VAR{RMSE_LOKASI1}; APPEND; QUIT; DATA SPACE_2; SET SPACE; IF 1 = T = 90 THEN OUTPUT SPACE_2; RUN; DATA RAMAL_SPACE_2; SET SPACE; IF 91 = T = 100 THEN OUTPUT RAMAL_SPACE_2; RUN; PROC ARIMA DATA=SPACE_2; IDENTIFY VAR=Y2 MINIC STATIONARITY=adf= 1 NLAG= 15 SCAN; ESTIMATE P= 1 NOINT NOPRINT; FORECAST LEAD= 10 OUT=DUGAAN2 NOPRINT; RUN;