Korea has been rapidly developing and accordingly cities have been also developing remarkably. However, as cities develop, various problems such as facility safety, environmental problems, and construction problems are occurring. Although local governments have proposed various policies and solutions to these problems within the city, citizens still feel uncomfortable and complain to local governments. Local governments have received citizens'' complaints to solve the complaints of citizens, but the fundamental causes of the problems have not been solved yet and only partial solutions have been made. For this reason, citizens'' complaints tend to increase year after year. With the recent rise of Social Network Service(SNS), the Big data era, in which data has grown exponentially, comes to us, and most complaints are received under the electronic civil service online rather than offline.
In this regard, this study acquired the electronic civil petitions data, collected from 2005 to 2015 targeting 16 administrative districts where the population and floating population was the highest in Jinju-si, which is the small local city and conducted a Spatial pattern analysis according to the causes for civil petitions after classifying causes for civil petitions and extracting location data. In addition, it conducted a time-series analysis for the complaints related to the illegal parking crackdown and identified the past pattern of civil complaints to suggest ways to improvement by predicting the occurrence pattern of civil complaints at a future point.
The study results of classifying the causes of civil complaints demonstrate that civil complaints related to parking, dust, noise, odors and pests in the middle classification have steadily occurred for 11 years, and complaints related to garbage such as illegal garbage dumping have decreased and have continued to increase again. In addition, civil complaints related to the illegal parking crackdown and noise related complaints among the small classification appeared to steadily increase every year. The study results of analyzing spatial distribution patterns according to the causes of civil complaints, complaints related to noise, road rehabilitation, and water and sewage maintenance formed hot spots in areas where industrial and residential facilities are mixed. Complaints related to odors were concentrated in residential areas. Civil complaints related to the illegal parking crackdown appeared to form a big hot spot every year in central commercial areas. In the case of the civil complaint related to illegal parking, which is one of the most frequent causes of civil complaints, the seasonal model ARIMA was applied to estimate the amount of future generations for two years. It is estimated that the ARIMA(0,1,1)(0,1,2)12 model is the most appropriate. Like the past pattern, this model showed a seasonal pattern, which occurred the most in summer. It was estimated that civil complaint related to illegal parking slightly increased year after year. Finally, as a result of investigating and analyzing the cause of the hotspot area where civil complaints for the illegal parking crackdown occurred the most, complaints about the imposition of the fine for parking within a short time (within 5 minutes) were the majority. This indicates that a variety of improvements such as parking facilities, fare rate improvement, and efficient parking system are needed because it is judged that civil complaints increase because the fare rate for the short time parking and the goals and directions of transportation maintenance are not established. Therefore, it is judged that this study will be utilized to set the urban planning and the direction of urban management as well as establishing measures for civic complaints in cities and systematic management by analyzing civil complaints, raised in local governments.