Intermodal Passenger Transport Planning in Yogyakarta International Airport, Indonesia

2.1 Intermodal passenger transport

The movements of passengers or freight from an origin to a destination rely on several modes of transportation [10]. Based on the Regulation of the Minister of Transportation of the Republic of Indonesia, intermodal passenger transport refers to a transportation of inter-route network and inter-province city. The transport with the origin, destination and transit terminals are in the form of terminals or other transportation modes, including airports, ports and train stations connected as route networks and or strategic areas or other areas that have the potential for trip generation and travel attraction between cities and between provinces [11]. Transport operations is expected to provide a cost-effective operation following travel requests that are timely and reliable by customer needs and target operators [12, 13]. Therefore, the origin and destination terminals of each route were determined by considering that: (a) estimated transportation needs to and from the node to the city outside the rural location of the node is at least 5 years; (b) the transportation node is part of the national node.

Intermodal passenger transport service organized with the following characteristics: (a) explicitly transporting passenger movement from one mode to another; (b) scheduled; (c) using a bus car.

2.2 Transportation network system

This transportation network system includes: (a) transportation services consisting of several modes of transportation, including the ways of roads, railways and air modes; (b) the transportation network system under study specifically for the road network; (c) the loading of the leading road network used to predict future traffic loads.

Accessibility analysis in the preparation of a study on the operation of intermodal passenger transport includes road network accessibility and road network mobility.

Connected vehicles on the mode choice and mobility of transportation network demands were modified based on the travel time between each origin-destination (OD) pair caused by the connected car [14].

The analysis of land use patterns can affect the determination of the operation of intermodal passenger transport, which is used to determine the location of the route to get to the airport. Therefore, it is necessary to analyse the following aspects: (a) locations of potential passengers such as residential centres, trade and service centres and others requiring intermodal passenger transport; (b) land use patterns that will help determine the route or location of the supporting facilities for the operation of intermodal passenger transport.

Intermodal passenger transport involves several categories, namely facility network, route network, organization network and demand network [15-17].

2.3 Determination of the zone system and network system

The zoning study area is one of the most widely studied transport planning as the first and the most critical steps [18]. The transportation system for the study area consists of two elements: the zone system and the road network system. The zone system divides the study area into several sections as the minor aggregation level of generating and towing trips. Generally, the zone is the centre of the location or centroid, which is assumed to be the starting or ending point of the journey. A road network consists of roads or links which generally give the attributes of length, capacity and speed of operation. The intersection between streets is called a node which can be in the form of a crossroads (with or without traffic lights), while for the study of regional transportation networks between cities, the node can be a city. In the study of node-point transportation, terminals (buses, trains, airports, ports) can be the beginning and end of a trip using public or non-road-based transportation. Zone system based on the city centre and administrative area boundaries, such as regency/city and provincial borders, consists of internal and external zones [19].

4.1 Yogyakarta International Airport service area coverage

The coverage of the YIA Service Area, as shown in Figure 2, was calculated based on the distance of the district/city road network to the surrounding airports.

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Figure 2. Yogyakarta International Airport coverage service area

4.2 Origin-destination survey

Stated preference [21-23] is a data collection technique based on the approach to the opinion of respondents in dealing with various choices. This technique uses an experimental design to create alternative imaginary situations. The step taken was to indicate the respondents’ responds of the real ideal problems. It was aimed at enabling the researchers to exercise control over all factors in the choices offered.

An excellent public transport system was designed and funded to meet potential demand [24]. Plan for intermodal passenger transport planning activities at YIA will involve the participation of stakeholders, including the community (participatory planning), in the overall activity process.

The OD survey is a part of the activities carried out to obtain data on the amount of travel/ movement from the original location to the destination location within the scope of the study area [25, 26].

The OD matrix process was carried out based on the input in passenger travel data. The OD matrices in the analysis was used for the following reasons:

(a) Destination–origin matrix is the most basic information for all existing transportation problem-solving techniques. Various planning policies in the transportation sector were determined at the national and regional scope through the various efforts in developing methods to obtain the destination-origin matrix [27, 28]. The inexpensive way is more beneficial. In this study, the method of establishing the destination–origin. This study used the matrix of the conventional method by distributing questionnaires, and the primary input data in the form of trip OD passenger data. The conventional OD matrices formation method has many advantages from various sides, especially in terms of less time consumption and cost savings.

(b) The main criteria for determining the zone system in this study were the homogeneity and availability of data from the study area. The data were the transportation data (number of vehicles, bus lines, passengers), demographic data, urbanization data and economic data [29]. Therefore, the application in the study area on zone boundaries was based on the administrative boundaries of the district/municipality.

(c) One thing that affected the accuracy of the OD matrices was the amount of data and the location of the survey [30].

4.3 Primary data questionnaire collection

The data from PT Angkasa Pura I (Persero) Yogyakarta indicated the number of passengers departing and arriving in 2008–2019 (Table 1). Using the time series method with a polynomial graph and coefficient of determination of R squared (R2)=0.9534, it resulted in a perfect approximation (Figure 3). The prediction of the number of passenger movements until 2023 (2025) can be seen in Table 1.

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Figure 3. Trendline function number of passengers

Table 1. Number of passengers and projections at Yogyakarta Adisutjipto International Airport

Several factors were considered in determining the size of the sample. To determine the number of samples, the following is required:

(a) Determination of the population as the object of observation (per day);

(b) Total number of passengers per airport per day (if the object of observation is per day);

(c) Random sampling throughout the day (all hours of service).

The number of respondents were determined on a daily passenger basis of 19,572 (2019) people based on the following Slovin formula [31, 32]:

$n=\frac{N}{1+n \cdot e^2}$     (1)

where, n=number of samples; N=total population; e=margin of error.

The survey on 1,000 airport passengers who used Yogyakarta’s Adisutjipto International Airport asked respondents’ willingness to use transportation to and from YIA in Kulon Progo during operation. Table 2 presents the results of the choice of transportation modes used to and from YIA in 2019.

Out of 1,000 number of respondents, there were 3.08% margins of error.

$e=\sqrt{\frac{\frac{N}{\frac{1000}{N}-1}}{N}}=\sqrt{\frac{\frac{19572}{\frac{1000}{}-1}}{19572}}=0.0308$

Table 2. Selection of transportation modes

Table 3. Origin and destination of the respondents

Table 4. Potential service routes of intermodal passenger transport

Table 3 presents the respondents’ origin and destination and the estimation of potential intermodal passenger transport based on estimates made in 2021 in Table 1.

Passengers in 2021 (2023) are estimated to be 8,688,766 or 23,805 per day, so the potential annual need for intermodal passenger modes is 21.30%×8,688,766=1,850,707 or 5,070 per day.

Determining intermodal passenger transport stops can adjust to the potential centre of activity or other strategic locations (terminals, stations, hotels, shopping centres, tourist sites). Several possible alternative areas for route development exist based on passenger movement data, service area coverage and the criteria mentioned above. Table 4 and Figure 4 recommend potential routes for intermodal passenger transportation based on the demand for passenger movement.

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Figure 4. Map route of intermodal passenger transport

Travel time with vehicle speed is an average of 60 km per hour with a time deviation of 10% of travel time. The following formula calculates travel time:

$T T_{A B}=\left(A T_{A B}\right)+\left(\sigma_{A B}\right)+\left(D T_{A B}\right)$     (2)

where, TT_AB=travel time from A to B; AT_AB=average travel time from A to B with a speed of 60 km/h; σ_AB=deviation of travel time from A to B (10% from AT); DT_AB=vehicle downtime at the terminal between AB (5% from AT).

From Table 4 presents the recommendations for potential routes for intermodal passenger transportation, and thus the travel time can be calculated and presented in Table 5.

Routes 1 to 5 covers the destination of Yogyakarta, Sleman and Bantul agglomeration areas, so that potential passengers were counted into one with the following formula:

$P P_i=\left[\frac{F i}{\sum F}\right] * B$     (3)

The calculation obtained the following number of passengers:

route 1=(49.68/356.62)×257=35.80;

route 2=(56.12/356.62)×257=40.44;

route 3=(60.61/356.62)×257=43.68;

route 4=(91.66/356.62)×257=66.05;

route 5=(98.56/356.62)×257=71.03.

Table 5. Traveling time per route

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Figure 5. Intermodal passenger transport bus and seat configuration

Table 6. Estimation of bus needs per route

Table 7. Estimation of bus needs per route

Table 8. Existing intermodal passenger transport routes

Table 6 calculates the need for buses by considering the number of prospective passengers and the distance of departure time (headway). Forty-two buses are ready to operate, with a reserve of 10% or four buses. Thus, the total demand for all buses is 46 buses. The maximum number of passengers per bus is 11.84≈12, so the intermodal passenger bus plan with a medium bus capacity is 15 seats. Figure 5 shows a proposed Hino Dutro 130 MDBL luxury medium bus (minibus) with 15 passenger seats with vehicle dimensions having an overall height approx. ±2,709 mm, length of 7,673 mm and width of 2,135 mm.

4.4 The operating costs and tariff determination

Table 7 presents the calculation of the operating costs of each route with different amounts and distances using the Hino Dutro 130 MDBL vehicle.

Existing intermodal passenger transport services at Yogyakarta Adisutjipto International Airport and current rates these presented in Table 8. It can be seen in Table 8 that the tariff rates vary and range from IDR 545.45 up to IDR 1,470.59 per km.

The fare per kilometre currently has an interval of 925.13 (calculated based on the difference between the highest and the lowest). Users’ willingness to rate the service they receive (willingness to pay/WTP) is considered to be on average (997.20). The base rate per km was=997.20, based on which the travel costs and potential income were determined and presented in Table 9.

4.5 Financial feasibility analysis

The basis of investment decisions is the rate of return on investment/investment costs from the number of benefits calculated during the planning period. The feasibility analysis determine the appropriateness of the planned intermodal passenger transport operation.

Standard economic indicators commonly used in financial evaluation include the net present value (NPV), financial internal rate of return (FIRR) and benefit-cost ratio (BCR) [33, 34]. In general, all indicators will provide a scale that compares the value of each proposed alternative’s benefits and costs, but specifically, each indicator has different characteristics.

Table 9. The travel costs and potential income

Table 10. The benefit-cost ratio (BCR)

The NPV approach assesses alternative planning’s financial performance by calculating the difference in the benefits and the cost value of each alternative throughout the planning period. The difference in value is then estimated in its present value (the base year of the project) by reducing its value due to an interest rate (discount rate), which is expected to occur throughout the planning period. This NPV indicator can provide information on the amount of the difference (benefit-cost) in each review year and the current value of money. If the NPV value is >0, the alternative planning is financially feasible [35].

Economic growth and inflation in Indonesia in 2019 was 8.15%, so the discount factor is set with a security of 10%.

Table 11. Cumulative present value

FIRR is a value of the interest rate (discount rate) when the present value of the investment benefit is equal to the current value of the investment cost or the amount of the interest rate at a time when the NPV value is 0. If the FIRR value > actual discount rate has expected to occur throughout the planning period, the alternative is feasible [36].

The calculation in Table 10 indicates that the price of the Hino Dutro 130 MDBL vehicle is IDR 850,000,000 per unit, with operation time of 5 years, so its NPV net benefit is=128.397,296,609; BCR is=1.4625; FIRR is=0.9114 for 5 years, which is equivalent to 18.23% per year. With the predicted bank’s interest of 7.0%, the FIRR is > the bank’s interest. Table 11 shows the cumulative present value, which states that the value of cost < revenue or pay back period=1.99 years=2 years. According to Tables 10 and 11, BCR is > 1; NPV net benefit is >0 and FIRR is >bank interest, and thus the proposed vehicle is feasible to implement.