## 5 Description of the Study Area
### Data Collection  
In order to execute the transit network problem, four important datasets must be available, namely the list of all nodes (_i.e._, bus stops and rail stations), the network available connectivity list, the transit demand matrix and the cost parameters. A total of 54 nodes is defined to describe the service area and associated network connectivity. The list of locations associated with these 54 nodes is tabulated in Tables 3 and 4.  
Network connectivity is generated from street links that connect these 54 nodes, and these are suitable for bus operations. The generation of the demand matrix is based on a questionnaire survey data collection. The demand matrix was determined by extracting the abstained results from the survey.  
The questionnaire is designed to collect a respondent's origin and destination. Targeted respondents are LRT passengers that queue up at bus stops and LRT stations in different locations in the study area. Generally, larger sample sizes provide more accurate survey results. Nonetheless, due to the constraints of limited resources and time, the sample size for transit service is confined to 20 percent of passengers counted in each LRT station using public buses.  
The random sampling technique is employed in this survey to make sure that each member of the population has an equal chance of being selected as a respondent. The locations of LRT stations in the PJ area used for conducting the questionnaires, which widely covers the study area, are shown in Table 5.  
The data for normal weekdays were applied in the research. The survey time slot was for the three-hour morning peak period from 6:30 a.m. to 9:30 a.m. and was designed to capture the feeder bus passengers of morning peak times.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Rail Station No.** & **X-Coordinate (km)** & **Y-Coordinate (km)** \\ \hline
51 & 7.06 & 3.43 \\
52 & 6.19 & 3.52 \\
53 & 4.57 & 3.48 \\
54 & 3.42 & 4.17 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Rail station locations.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Bus Stop No.** & **X-Coordinate (km)** & **Y-Coordinate (km)** & **Bus Stop No.** & **X-Coordinate (km)** & **Y-Coordinate (km)** \\ \hline
1 & 6.71 & 6.17 & 26 & 5.11 & 2.30 \\
2 & 5.97 & 6.15 & 27 & 4.31 & 1.67 \\
3 & 5.79 & 5.59 & 28 & 4.30 & 2.14 \\
4 & 6.26 & 5  
To determine some of the data and the value of parameters in the proposed mathematical model, the observation method was used in this research. In this section, the design and procedures employed for conducting the observation in train stations and bus stops are presented. Observations are conducted based on the LRT stations and existing feeder bus routes. Observations are categorized into two types of questions. The first question was about the time spent boarding and alighting at the LRT station and bus stops based on time per passenger. The second question was about the average feeder bus speed in existing routes. The cost parameters are based on data collection for the current study, as well as ridership and financial reports publicized by Barton and Valley Metro Barton and Valley (1993); Barton and Valley (1993).