Page 444 - Contributed Paper Session (CPS) - Volume 4
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CPS2564 Tiffany Rizkika et al.
                  survey is done every week for volatile commodities, and every two weeks for
                  non-volatile products. The publication of this data is published every month.
                      In  making  decisions  related  to  fluctuating  food  prices,  data  with  a
                  collection time very close to the time of decision making is needed. The closer
                  the  time  span,  the  better  decisions  can  be  made.  Currently  the  consumer
                  prices are published every month. Nowadays when quick decision making on
                  prices  with  rapid  changes,  more  frequent  and  almost  real  time  data  and
                  prediction so called now casting is needed. The term "nowcasting" is originally
                  used in meteorology to forecast weather in the present and in the next few
                  hours.  Several approaches can be implemented to monitor the food prices in
                  almost real-time to maintain price transparency therefore government will be
                  easy detecting inflation early to reach the stability of economy.
                      Pramana, et al. (2016) shows a proof of concept of using crowdsourcing
                  data  as  one  resource  for  food  price  nowcasting.  They  also  discuss  that  in
                  general there is a similar movement of official price data patterns between
                  several  commodities  that  collected  by  BPS-Statistics  Indonesia,  with  data
                  collected through crowdsourcing techniques carried out by Pulse Lab Jakarta.
                  They used simple data cleaning and smoothing for nowcasting and only few
                  commodities.
                      One  of  big  challenges  in  big  data  is  its  veracity  and  followed  by  the
                  analysis. Hence, further research on nowcasting technique required, including
                  filtering and modelling, to obtain accurate prediction is needed.  Therefore, in
                  this study, several nowcasting approaches are investigated to obtain the best
                  nowcast for food price data.

                  2.  Methodology
                      a.  Data Sources. This study uses the following secondary sources:
                             1)  Crowdsourcing data obtained from collaboration of Pulse Lab
                                Jakarta,  United  Nation’s  Food  and  Organization  (FAO),  and
                                Premise Data Corporation in 2015.
                             2)  Market data obtained from google to identify places/markets
                             3)  Official  Consumer  Price  Data,  from  BPS  Statistics  Indonesia
                                consumer price survey.
                      b.  Food Commodities:
                             1)  Volatile: chicken  beef,  egg, onion, chili, low quality rice, and
                                premium quality rice.
                             2)  Non-volatile:  mackerel,  long  bean,  instant  dry  noodles,
                                peanuts, and vegetable tomatoes.
                      c.  This study is taking place at Lombok Island, during March until July
                         2015.



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