AIR POLLUTION PREDICTION MODELS DUE TO TRAFFIC VOLUME AND GREEN OPEN SPACE AVAILABILITY

As the population grows, the development of the city increases, as a result the movement of transportation also increases. The development of the city can also affect a decrease in green open space. Increased vehicle traffic affects the increase in air pollution. Hence, there is very little research that mathematically connects the influence of traffic volume (passenger car units) and green open space with the level of air pollution. Green open space and the level of air pollution are directly measured on the field. Subsequently, the measurement is calculated by using the regression analysis to obtain a model of the relationship between green open space and traffic volume with the level of air pollution. The research was directly conducted at 3 locations, 2 locations in Jakarta (Semanggi and Tanah Kusir) and 1 location in South Tangerang. This model can be applied to predict that air pollution will occur as a result of traffic volume and the availability of green open space. Keyword: Air pollution, prediction, green open space, traffic volume.


INTRODUCTION
Increased population in various cities will escalate traffic among locations in a city and among cities in a country. Increased traffic followed by an increase in reducing air quality (increasing air pollution) due to motor vehicle pollution.
The growth of population will decrease the availability of green open space which entails to the increase of air quality pollution.
DKI Jakarta ranks second as the worst air polluted city in the world which is classified as unhealthy city. The city has merely had 9.98% of green open space than it should have been 30% (Nugradi D.N.A., 2009), compare to its neighboring city, South Tangerang which has 20% of green open space (Prakoso P.;Herdiyansyah H, 2019). There is a connection among air quality, vehicle traffic volume, and green open space. Various studies have been carried out, among others: the effect of volume and speed of vehicles on noise (Sufanir A.M.S., 2017;Setiawan A., 2014;Maulana A.Z., 2012;Nugradi D.N.A., 2009;Syaiful & Ngadimo., 2014). However, it is hardly found studies alike which connect traffic volume (passenger car units) and green open spaces with air quality (air pollution)

Research Objectives
This research aims to find the mathematical relationship of the influence of traffic volume (passenger car units) and green open spaces simultaneously on air pollution.

Research Innovation
The novelty of this study is the breakthrough of a mathematical relationship on the influence of traffic volume (passenger car units) that

METHODS
The study was conducted in the following order: 1) Direct observations by measuring vehicle volume, area of green open space and air quality. Measurement of air quality use the Air Quality Meter tool, and the vehicle volume measurement tool using the Counter tool.
2) Secondary data obtained through the South Jakarta Transportation Department data and South Tangerang  Department  of  Transportation  and  various  literatures 3) Data processing is done by linear regression analysis and multiple linear regression methods to determine the pattern of relationships between the variables involved such as vehicle volume, green open space, and air quality. From the results of the analysis it will get a graph and a significant level of related variables based on the results of the regression carried out.
Research data in the form of traffic volume from various types of motor vehicles, noise and air quality are measured directly in 3 locations namely in Jakarta (location: Sequis Center and Tanah Kusir) and in South Tangerang (location: BSD -Green Park Office), while Green Open Space (GOS) is calculated from secondary data. .

DISCUSSION
Based on the calculated data, it can be described various relationships between green open space and vehicle volume with noise and air pollution. There was a drastic increase from 08:00 to 16:00 in BSD due to the large number of heavy vehicles passing by. This indicates that heavy vehicles are the major contributor to air pollution.
Based on the analysis of data collected related to air pollution and green space, the results obtained are as shown in Table 3.  The results of the analysis of the effect of X1 (vehicle volume) with Y (noise) using the SPSS program produces a sig value of 0.102> 0.05 and a value of 1264 <T table (2,080) concluded that the volume of the vehicle has no effect on noise (the first hypothesis). Analysis of the data for the second hypothesis (H2) the sig value for the effect of X2 on Y was 0.220> 0.05 and the value of 1264 <2.080 be concluded that green open space has no effect on noise. The effect of vehicle volume and green open space on noise from the analysis conducted has not yet been proven, meaning that it is assumed that there are many other factors that influence noise, not only in macro terms of vehicle volume but the composition of the types of vehicles passing through might also be impacted. Noise prediction due to traffic has been included in the Traffic Prediction Handbook (Departemen PUPR, 2004), so the purpose of simplifying noise prediction in this study has not yet been recognized.

CONCLUSION
Based on the data analysis, the following can be drawn as a conclusion: (1)