Purabaya Terminal – Blunder Terminal

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Plans for Switching Motorcycle Users to BTS Buses for Porong Terminal – Larangan Terminal –

Purabaya Terminal – Blunder Terminal

Ahmad Zaky Sujono Putra

Department of Civil Engineering, Faculty of Engineering Narotama University Surabaya [email protected]

Abstract

The high number of motorcycle causes traffic problems. Therefore, it is necessary to study the possibility of switching from private transportation to public transportation for the Sidoarjo - Surabaya - Gresik trip by analyzing the probability of motorbike users going to the BTS Bus. Identification of respondents will be divided based on social, economic and travel characteristics. Ability To Pay (ATP) is the ability to pay for services and Willingness To Pay (WTP) is the willingness to pay for services. The probability of motorcycle users who want to switch to public transportation is strongly influenced by income. The research method used a questionnaire on time and tariffs that was submitted to 100 respondents. The time and cost offered to respondents varied. And the implementation of the Logistics Regression Model aims to determine the percentage of passengers who are willing to change modes. The results showed that the majority were dominated by respondents with an income of 2,000,000 – 4,000,000 million by 76% and an income of 4,000,000 – 6,000,000 million by 24% of the total respondents. The comparison of ATP and WTP at the purabaya terminal - porong terminal is 4,638 and 3,260, at the Purabaya terminal - Larangan terminal is 4,638 and 1,565, for the Bunder-Purabaya terminal is 4,638 and 4530, for the Bunder - Porong terminal is 4638 and 3665, for the Bunder terminal – Prohibition of 4638 and 2590, for Porong-Larangan terminal of 4638 and 4555. The probability of motorcycle users who will switch to the BTS bus shows that if it is operated it will take 135 minutes and the fare is Rp. 5,000.00 as much as 18.29%, while the BTS bus which is operated with a time of 120 minutes and a fare of Rp. 10,000.00 as much as 0.047 %.

Keywords:

Descriptive Statistical Analysis, Logistic Regression Model, Probability, Public Transportation

1. Introduction

The rise of the number of motorbikes does not deny that this is due to one of the factors, namely the lack of public transportation in the Porong terminal to the Bunder terminal, so that many people who have high mobility between the 3 cities are more comfortable using motorbikes with private facilities due to inadequate public facilities. Traffic problems or congestion cause huge losses for road users, especially in terms of time wastage, waste of fuel, waste of energy and low traffic comfort as well as increasing noise and air pollution.

So, it is necessary to optimize the use of public transportation by diverting perpetrators from using private transportation to switch to using public transportation, one of which is the BTS Bus (Buy the Service). The BTS (Buy the Service) bus is a bus that has the advantage of subsidizing facilities launched by the government by reducing costs with the operator, compared to existing commercial buses, in addition to security facilities such as CCTV and supervisors to maintain the security of each passenger. Facilities that can be used by existing passengers, especially the Porong-Purabaya - Bunder department which is the center of inter-city bus activities throughout East Java.

Therefore, it is necessary to study the possibility of a transition from private transportation to public transportation for the Sidoarjo - Surabaya - Gresik trip. This study is needed to determine the high and low probability of the transition that occurs and what factors can influence the occurrence of the transition. This characteristic research is very useful for anticipating and reducing global warming by minimizing the use of motorized vehicles in certain areas. So, it takes analysis and research on the probability of motorcycle users who will switch to the BTS bus.

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2. Literature Review

2.1. Regression Analysis

The analysis used in Trip Generation is linear regression analysis. Linear regression analysis is a statistical method used to predict a dependent variable (Y) based on the independent variable (X) in a linear equation. The formula for the linear equation is expressed in the following equation:

Y = a + bX Where:

Y = variable dependent X = variable independent a = regression constant b = regression coefficient

If the above equation is to be used to estimate the magnitude of the zone-based movement generation, all variables are identified with a tick i, if the Y=A+Bx equation is defined as a zone-based movement pull, it is identified with a d column. (Tamin, 2000). Parameter values A and B can be obtained from the following equation:

𝐵 = 𝑁 Σ𝑖 (𝑋𝑖 𝑌𝑖) − Σ𝑖 (𝑋𝑖)Σ𝑖(𝑌𝑖) 𝑁 Σ𝑖 (𝑋𝑖²) − ((Σ𝑖(𝑋𝑖))²

𝐴 = 𝑌 − 𝐵𝑥 Where:

Y and X are the average values of Yi and Xi. Multiple linear regression is a further development concept from the linear regression above, were in linear regression

This multiple has many variables. The general form of the equation of this method is:

𝑌 = 𝐴 + 𝐵₁. 𝑋₁+ 𝐵₂. 𝑋₂+ 𝐵₃. 𝑋₃+ ⋯ + 𝐵_𝑧. 𝑋_𝑧 Where:

Y = dependent variable A = regression constant B1, B2, B3, Bz = regression coefficient X1, X2, X3, Xz = independent variable

There are several assumptions that need to be considered in the use of multiple linear regression analysis, namely:

1. The value of the independent variable has a certain value or is the value obtained from the survey results without significant errors.

2. Must have a linear correlation with the independent variable (X) and the dependent variable (Y).

3. The effect of the independent variable (X) on the dependent variable (Y) is the sum and there must be no strong correlation between the independent variables.

4. The variance of the value of the dependent variable on the regression line must be the same for all values of the independent variable.

5. The value of the dependent variable must be distributed normally or nominally close to normal (Tamin).

2.2. Split Capital

Split Capital is one part of the Travel Demand Modeling process which plays an important role of public transport in transportation policy. This is related to the provision of transportation facilities and also road infrastructure needed for the movement process to occur with the availability of existing modes.

(Tamin) Split Capital can be defined as the division of trips made by travelers into available modes with various influencing factors.

2.3. Logistics Regression

Logistic regression is a statistical method that is applied to model categorical response variables (nominal/ordinal scale) based on one or more predictor modifiers which can be either categorical or continuous variables (interval or ratio scale). If the response modifier consists of only two categories, the logistic regression method that can be used is binary logistic regression. Logistic regression is a part of regression analysis that can be used if the dependent variable (response) is a dichotomous variable. Dichotomous variables usually only consist of two values, which represent the occurrence or absence of an event which is usually assigned a number 0 or 1 (Nirwana et al., 2016).

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19 2.4. Logistics Regression Model

Logistic regression analysis is an analysis used to see the relationship between the response variables in the form of qualitative data and explanatory variables, namely qualitative and quantitative data. Response modifiers in logistic regression form columns (binary) or polychotomes (ordinal or nominal). Logistic regression model is a statistical modeling that is applied to model the response variables that are categon based on one or more covariates (explanatory variables). Logistic regression models are often used in epidemiology, namely the study of the pattern of disease occurrence and the factors that influence it (Akbar, 2011). The following is a logistic regression probability model contained in the equation:

𝜋(𝑋₁) = exp (𝛽₀+ 𝛽₁𝑋₁) 1 + exp (𝛽₀+ 𝛽₁𝑋₁)

2.5. Binary Logistics Regression Model

The Binary Logistics Regression Model is a modeling procedure that is applied to model the categorical response variable (Y) based on one or more predictor variables (X) either categorical or continuous. if the response variable consists of 2 categories, namely Y=1 (success) and Y=0 (failure), then the regression method that can be applied is binary logistic regression. For one research object, the conditions with these 2 categories result in Y having a Bernoulli distribution (Masmuda, 2011). The logistic regression model with predictor variables is expressed in the equation:

𝜋(𝑋) = 𝑒𝑥𝑝^(𝛽⁰^+𝛽¹^𝑋¹^+⋯+𝛽^𝑝^𝑋^𝑝⁾ 1 + exp (𝛽₀+ 𝛽₁𝑋₁+ ⋯ + 𝛽_𝑝𝑋_𝑝))

Or

𝜋(𝑋) = exp (𝛽₀+ 𝛽₁𝑋₁… + 𝛽_𝑝𝑋_𝑝) 1 + exp (𝛽₀+ 𝛽₁𝑋₁+ ⋯ + 𝛽_𝑝𝑋_𝑝) 2.6. Conjoint Analysis

Conjoint Rating, in this method questionnaires are distributed to respondents to provide an assessment of the alternatives offered by using a rating scale (eg choosing a scale between 1 to 10). Similar to Choose Modeling (CM), this method uses various attributes that have been considered beforehand. The difference with CM is that respondents do not need to make comparisons between several alternatives to choose the preferred alternative. In this method, respondents examine the alternatives offered.

Conjoint Ranking, the difference between this method and Conjoint Rating is that respondents are given 3 or more alternatives in one question and are expected to make a ranking or order of these alternatives (from preferred to disliked or vice versa).

This method is no longer widely used because of difficulties in processing the data obtained. Paited Comparison, through this method respondents are expected to choose between two alternatives where an alternative situation exists at that time and another alternative indicates a change. Respondents are expected to provide an assessment in the form of a scale such as the Conjoint Rating. This method is used more often than the three types of Conjoint Analysis that exist.

3. Methodology

3.1. Data collection

Data collection was obtained from field survey data at Sudirman Bus Terminal, Sukabumi, which was carried out by distributing questionnaires to respondents who were motorbike users. Contains questions in the form of respondent's personal data, including name, age, gender, occupation, purpose of travel from departure, destination of travel, costs incurred for each trip, time required each time to travel, expected ticket costs from the BTS Bus, travel time What is expected when using BTS Bus, BTS Bus departure time, BTS Bus arrival frequency every day and willingness to change modes.

3.2. Determination Number of Samples

To determine the number of samples with unknown data sources using a non-probability technique, namely the incidental sampling technique , which is a sampling technique based on chance, that is, anyone who coincidentally/ incidentally meets the researcher can be used as a sample, if it is deemed that the person who happened to be met is suitable. as a data source. The number of samples taken in this study using the Lemeshow formula, this is because the total population is unknown or infinite.

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20 𝑛 =𝑍₁−𝛼

2 𝑃(1 − 𝑃) 𝑑² Where:

n = sample

Z = z score at 95% confidence = 1.96 p = maximum estimate = 0.5

d = Alpha (0,10) or sampling error = 10.

3.3. Application of Descriptive Statistics and Logistics Regression Model

In the formation of a logistic regression model, the first step is to determine the dependent variable and the independent variable. In accordance with the research objectives, the dependent variable is the respondent's answer about the willingness to change modes with two categories, namely:

Category 1: Yes (willing to move) Category 2: No (not willing to move)

For the dependent variable in the binary logit regression model, there are 9 variables, namely gender, age, occupation, purpose of travel, frequency of travel, origin of departure, destination of travel, costs incurred each time you travel, and time required each time you travel with use minibuses.

3.4. Questionnaire Form

Questionnaire form the probability model of motorcycle users who will switch to the BTS Bus.

Table 1. Questionnaire form Scenario Bus BTS Porong – Purabaya – Bunder Gresik

Yes No

Time (second) Cost (Rp)

1 130 6..000

2 135 5.000

3 120 10.000

4 125 9.000

5 130 7.000

6 120 9.000

7 125 8.000

8 135 6.000

Assumption of Travel Time and Fare for BTS Porong – Purabaya – Bunder Gresik Travel time ranges from 120 to 135 minutes

Distance between 70 km – 75 km

1 liter = 40 km, if 75 km means that it takes 1.875 liters = 1.875 x Rp. 7650 = Rp. 14500 for 1 time of departure, so the cost is around 10,000 – Rp. 15.000, -.

4. Result and Discussion

4.1. Description of Survey Results

The questionnaire that was distributed consisted of three parts, namely the general characteristics of the respondents, the characteristics of the respondents' trips, and the mode selection form. And the general characteristics of the respondents consist of age, gender, occupation, last education, transportation expenses, and income. While the characteristics of the trip consist of travel time, frequency of travel, travel costs, number of people who go together, access vehicles. And the selection of modes consisting of changes in ticket prices, travel time, ability to pay, and willingness to pay.

4.1.1. Category Age and Gender

The following are the results of a survey that has been conducted based on the age distribution, which can be seen in the diagram below:

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Figure 1. Age Category Diagram

From the table it can be seen that the gender category is male with a percentage of 76% while female with 24% with the largest age range of motorcycle passengers being 21-25 years old with a percentage of 23%, then 26-30 years old with a percentage of 15%, 36-40 years with a percentage of 14%. Then followed by the age category 31 -35 with a percentage of 12% and after that it was dominated by the age category 15-20 by 12%. And the rest are in the range below 10%, with ages 41-60.

Figure 2. Gender Category Diagram

From the tab el it can be seen that the age of motorcycle passengers who are mostly in the gender category is male with a percentage of 76% while female with a percentage of 24% . This is because men's mobility is higher, and jobs that require road conditions are predominantly dominated by men so that the percentage of male respondents is greater than female.

4.1.2. Category Type of Work and Total Income

The following are the results of a survey that has been carried out by type of work , the distribution can be seen in the diagram below :

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Figure 3. Type of Work Diagram

The sample was taken randomly, but from the sample taken, it turns out that many motorcycle users are among employees with 71% of the total respondents, with 71 respondents, then followed by Entrepreneurs at 19% with 19 respondents, followed by students with 9% of the total respondents, and civil servants with 1% of the total respondents.

Figure 4. Total Income Diagram

Based on the results of the survey conducted, it can be seen that the majority are dominated by respondents with an income of 2,000,000 – 4,000,000 million with a frequency of 76 respondents or 76%

of the total respondents, followed by respondents with an income of 4,000,000 – 6,000,000 million per year.

month with a frequency of 24%.

4.1.2. Category of Travel Destination and Frequency of Using Motorcycle

The following are the results of a survey that has been conducted based on Travel Destinations, the distribution of which can be seen in the diagram below:

Figure 5. Travel Destination Category Diagram

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Based on the results of the survey conducted, it can be seen that the survey results are dominated by respondents with 1 travel destination with 74% of the total respondents or filled by 74 respondents. Then proceed with 2 objectives, which on average have an entrepreneurial background with 17 respondents or 17% of the total respondents. Then 3 goals with 6% and 4 goals with 3%.

Figure 6. Frequency of Using Motorcycle Diagram

Based on the results of the survey conducted, it can be seen that the average motorbike user carries out driving activities and the use of this mode is dominated by daily activities (7 days a week) with a frequency of or 89% of the total respondents, while respondents with a frequency of use of 1 to 5 days by 11%.

4.1.3. Cost Category a. Travel expense

This trip cost is related to the location and purpose of each motorbike mode user so that a varied value is obtained. The following are the results of a survey that has been conducted based on Travel Costs (BBM /Day), the distribution of which can be seen in the diagram below :

Figure 7. Fuel Cost Diagram

Based on the results of the survey conducted, it can be seen that the average motorcycle user spends in the range of 5000 to more than 30,000 rupiah per day, with 80 respondents answering the expense ranging from 5,000 – 10,000 rupiah per day and 80% of respondents say that, then followed by 7 respondents, each of which is in the range of 11,000 – 15,000 and 16,000 – 20,000 with each obtaining 7% of the respondents from the total respondents. For 21,000 – 25,000 the fuel expenditure range gets 1% of the total respondents, while the 26,000 – 30,000 range gets 2% while spending more than 30,000 is 3% of the total respondents.

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24 b. Motorcycle Maintenance Cost

Figure 8. Motorcycle Maintenance Cost Diagram

Based on the results of the survey conducted, it can be seen that the average motorcycle user pays a fairly large maintenance fee, only 2% spends less than 50,000 rupiah, while the average respondent is dominated by the range of motorcycle maintenance costs ranging from 76,000 to 100,000 with 44 % of total respondents or 44 respondents from 100 respondents.

c. Parking Cost

Figure 9. Parking Cost Diagram

Based on the results of the survey conducted, it can be seen that the average motorcycle user spends parking fees and is dominated by parking financing activities with a frequency of 72% of the total respondents, while respondents with a frequency of no parking financing are 28%.

4.2. Mode Selection

The following table shows some questions to respondents regarding the selection of BTS Bus modes from respondents who use motorcycles. Respondents just have to choose a yes or no answer by ticking several fare options and BTS Bus travel times. The results of the respondents' choices will be processed to obtain a logistic regression equation for the selection of BTS Bus transportation modes. The following are the results of the processed answers of respondents who use motorcycles which can be seen in the following table:

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25 Table 3.

B S.E. Wald df Sig.

90% C.I.for EXP(B) Exp(B) Lower Upper

Step 1 WT -0,076 0,039 3,709 1 0,054 0,927 0,869 0,989

TARIF -0,001 0 14,976 1 0,000 0,999 0,999 1

Constant 13,763 5,97 5,314 1 0,021 948943,5

a. Variable(s) entered on step 1: time, rate. The initial model of the logistic regression equation is:

𝑃 = ^𝑒^{(𝛽0+𝛽1+𝑋𝑖)}

1+ 𝑒^{(𝛽0+𝛽1+𝑋𝑖)}………(1)

From the table above, the equation of the logistic regression model can be formulated as follows:

𝑃 =

^𝑒(13,763−0,076 𝑥 𝑡𝑖𝑚𝑒𝑠−0,001 𝑥 𝑇𝑎𝑟𝑖𝑓)

1+ 𝑒(𝛽0+𝛽1+𝑋𝑖)(13,763−0,076 𝑥 𝑡𝑖𝑚𝑒𝑠−0,001 𝑥 𝑇𝑎𝑟𝑖𝑓)…..…………(2)

The interpretation of the results of the table and the logistic regression equation above, the equations that have been obtained will be entered into several scenarios of questions posed to respondents using motorcycles, the results of which can be seen in the following table:

Table 4. The interpretation of the results of the table Scenario Bus BTS Porong – Purabaya – Bunder Gresik

Yes No

Time (menit) Cost (Rp)

1 130 6..000 0,1075 0,89254

2 135 5.000 0,1829 0,81713

3 120 10.000 0,0047 0,99531

4 125 9.000 0,0087 0,99131

5 130 7.000 0,0424 0,95759

6 120 9.000 0,0127 0,98735

7 125 8.000 0,0233 0,97673

8 135 6.000 0,0761 0,92393

The table above shows that the probability of motorcycle users who will switch to BTS buses is that the BTS buses are operated with a travel time of 135 minutes and a fare of Rp. 5,000.00 as much as 18.29%, while the BTS bus which is operated with a time of 120 minutes and a fare of Rp. 10,000.00 as much as 0.047 %.

4.3. Ability To Pay Analysis

ATP analysis is the ability to pay respondents to use mode facilities in accordance with the ratio of their income so that the average ATP value obtained is:

𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑇𝑜𝑡𝑎𝑙 𝐴𝑇𝑃 𝑉𝑎𝑙𝑢𝑒 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑅𝑒𝑠𝑝𝑜𝑛𝑑𝑒𝑛𝑡𝑠 𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 = 463.813

100 = 𝑅𝑝 4.638

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So that the average ATP value of respondents is Rp. 4,638, which is obtained from the division of the total number of Ability to Pay values divided by the Total Respondents, from the total Ability to Pay value, it is obtained 463,813 divided by 100 Respondents, it is Rp. 4,638 Rupiah.

4.4. Willingness to Pay Analysis

The average value of willingness to pay is obtained from:

𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑉𝑎𝑙𝑢𝑒 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑅𝑒𝑠𝑝𝑜𝑛𝑑𝑒𝑛𝑡𝑠 𝑀𝑎𝑥𝑖𝑚𝑢𝑚 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑉𝑎𝑙𝑢𝑒

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑅𝑒𝑠𝑝𝑜𝑛𝑑𝑒𝑛𝑡𝑠

𝑊𝑇𝑃 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑀𝑖𝑛. 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐶𝑜𝑠𝑡 + 𝑀𝑎𝑥. 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐶𝑜𝑠𝑡 2

So it was found that the comparison of ATP and WTP is a comparison between the ability to pay of the respondents and the need or desire to pay due to the need for these modes in fulfilling daily activities. It can be seen that at the purabaya terminal - porong terminal / vice versa, the ratio of ATP and WTP is 4,638 and 3,260, at Purabaya terminal - Larangan terminal / vice versa it is 4,638 and 1,565, for the roundabout- purabaya terminal / vice versa it is 4,638 and 4530, for the roundabout - porong terminal / on the other hand, it is 4638 and 3537. For the Bunder - Lamongan terminal / vice versa it is 4638 and 3900, for the Porong - Larangan terminal / vice versa it is 1735. The comparison graph of ATP and WTP can be seen in the image below:

Figure 9. Comparison of ATP and WTP Values

5. Conclusion

The conclusions that can be drawn from this final project are:

4. Characteristics of motorcycle users in the Terminal-Porong - Terminal Bunder department, namely the age category from the age of 15-60 years. by married as much as 65%, the last education category is dominated by high school graduates with a percentage of 60% because the majority are employees, and income is dominated by respondents with an income of 1.5 million to 3 million, and the purpose of the trip is dominated by 1 travel destination.

5. The comparison of ATP and WTP between the respondents' ability to pay and their need or desire to pay. It can be seen that at the Purabaya terminal - Porong terminal / vice versa, the ratio of ATP and WTP is 4,638 and 3,260, at Purabaya terminal - Larangan Terminal / vice versa it is 4,638 and 1,565,

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for the Bunder-Purabaya terminal / vice versa, 4,638 and 4530, for the Bunder - Porong terminal / on the other hand it is 4638 and 3665. For the roundabout terminal – prohibition/conversely it is 4638 and 2590, for the porong-banan terminal/otherwise it is 4638 and 4555.

6. The probability that motorcycle users will switch to the BTS bus shows that the BTS bus is operated with a travel time of 135 minutes and a fare of Rp. 5,000.00 as much as 18.29%, while the BTS bus which is operated with a time of 120 minutes and a fare of Rp. 10,000.00 as much as 0.047 %.

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