Analysis of the Level of Passenger Satisfaction with the Performance of BISKITA Trans-Bekasi Patriot Service
- Savira Septiarini
- Alizar
- 301-307
- Feb 27, 2025
- Education
Analysis of the Level of Passenger Satisfaction with the Performance of BISKITA Trans-Bekasi Patriot Service
Savira Septiarini, Alizar
Civil Engineering Departement, Universitas Dian Nusantara, Jakarta, Indonesia
DOI: https://dx.doi.org/10.47772/IJRISS.2025.9020025
Received: 26 January 2025; Accepted: 30 January 2025; Published: 28 February 2025
ABSTRACT
Public transportation has a strategic role in improving the mobility of urban communities, including Bekasi City, which faces congestion challenges due to the growth of private vehicles that are not balanced with road infrastructure. The BISKITA Trans Bekasi Patriot service comes as a solution to reduce congestion and provide efficient public transportation. This study aims to analyze passenger satisfaction with the service, identify factors that affect satisfaction, and provide recommendations for improving service quality. The research method used is descriptive quantitative with a survey approach, using the SERVQUAL (Service Quality) technique to measure the gap between expectations and reality of services, as well as the Customer Satisfaction Index (CSI) to assess the overall level of satisfaction. Data was obtained through questionnaires distributed to 100 respondents with a purposive sampling technique. The results showed passenger satisfaction was in the “Satisfied” category, with a CSI value of 80.71%. The dimension with the most significant gap is Tangible (-3.78), especially in the indicators of bus stop seating comfort and bus stop cleanliness. In contrast, the reliability dimension has the smallest gap, which shows that the performance is closest to passenger expectations. The conclusion of this study confirms that although the service is quite adequate, improvements are still needed in bus stop facilities, especially cleanliness and comfort, as well as improving the quality of service of officers through training that focuses on friendliness and responsiveness. By implementing these recommendations, it is hoped that the BISKITA Trans Bekasi Patriot service can continue to increase passenger satisfaction and support the efficiency of community mobility in Bekasi City.
Keywords: public transportation, passenger satisfaction, SERVQUAL, customer satisfaction index, gap analysis
INTRODUCTION
Public transportation plays a vital role in supporting the mobility of urban communities, including Bekasi City, which faces congestion due to an increase in the number of private vehicles that are not matched by road infrastructure. As a solution, BISKITA Trans Bekasi Patriot comes through the collaboration of the Jabodetabek Transportation Management Agency (BPTJ) and the Bekasi City Government with the BTS (Buy The Service) scheme. This service is integrated with Jabodebek LRT and serves the Summarecon Bekasi – Vida Bantar Gebang route. BISKITA is designed to provide safety and convenience through a cashless payment system and government standard-based services.
In the last six months, the number of BISKITA passengers has increased significantly, from an average of 32.116 daily passengers in April 2024 to 70.061 in October 2024. This shows the public’s positive response to a service that is considered affordable and convenient. However, challenges in the form of traffic congestion along the route often cause delays, which affect passenger confidence. According to Nasution (2004), punctuality is an important dimension of public transportation, which, if not met, can reduce passenger satisfaction.
Research on the level of passenger satisfaction of BISKITA Trans Bekasi Patriot using the SERVQUAL model (physical evidence, reliability, responsiveness, assurance, empathy) aims to evaluate service performance from the user’s perspective. This analysis is essential to find out aspects that need improvement to improve service quality. The research results are expected to be the basis for public transportation managers and local governments in formulating policies to improve service efficiency and effectiveness while encouraging people to switch from private vehicles to public transportation to reduce congestion and realize a sustainable transportation system in Bekasi City.
RESEARCH METHOD
This study uses a quantitative approach with a survey method to measure the level of satisfaction of BISKITA Trans Bekasi Patriot passengers. The population in this study were all passengers who used the service, with the research sample determined using purposive sampling based on the criteria of passengers who had used the service at least three times. The number of samples taken was 100 people to ensure the research results were representative. The research was conducted from October to December 2024 in the BISKITA Trans Bekasi Patriot operational area.
The research instrument was a questionnaire based on the SERVQUAL method, covering five primary dimensions: tangibles, reliability, responsiveness, assurance, and empathy. The questionnaire was tested for validity and reliability using Statistical Package for the Social Sciences (SPSS) software before use. Data was collected by distributing questionnaires directly to respondents at selected bus stops during operating hours. The collected data were analyzed using the Customer Satisfaction Index (CSI) method to measure the level of passenger satisfaction and SERVQUAL analysis to identify the gap between passengers’ expectations and perceptions of the services provided. Data analysis was carried out with the help of Microsoft Excel 2019 and SPSS version 27.
RESULT AND DISCUSSION
Validity and Reliability Test
Before conducting the Customer Satisfaction Index (CSI) and Servqual analysis, validity, and reliability tests were performed to ensure that the research instruments could be used properly. The validity test assesses whether the statement items in the questionnaire can measure the intended construct, while reliability determines the consistency of measurement.
Table 1. Expectation validity test results
Statement | rcount | rtable | Sig. (2-tailed) | Description |
X1 | 0.39 | 0.195 | <.001 | Valid |
X2 | 0.50 | 0.195 | <.001 | Valid |
X3 | 0.53 | 0.195 | <.001 | Valid |
X4 | 0.50 | 0.195 | <.001 | Valid |
X5 | 0.51 | 0.195 | <.001 | Valid |
X6 | 0.28 | 0.195 | <.001 | Valid |
X7 | 0.47 | 0.195 | <.001 | Valid |
X8 | 0.50 | 0.195 | <.001 | Valid |
X9 | 0.59 | 0.195 | <.001 | Valid |
X10 | 0.51 | 0.195 | <.001 | Valid |
X11 | 0.64 | 0.195 | <.001 | Valid |
X12 | 0.57 | 0.195 | <.001 | Valid |
X13 | 0.52 | 0.195 | <.001 | Valid |
X14 | 0.62 | 0.195 | <.001 | Valid |
X15 | 0.54 | 0.195 | <.001 | Valid |
X16 | 0.52 | 0.195 | <.001 | Valid |
X17 | 0.45 | 0.195 | <.001 | Valid |
X18 | 0.60 | 0.195 | <.001 | Valid |
X19 | 0.64 | 0.195 | <.001 | Valid |
X20 | 0.54 | 0.195 | <.001 | Valid |
X21 | 0.62 | 0.195 | <.001 | Valid |
X22 | 0.52 | 0.195 | <.001 | Valid |
X23 | 0.63 | 0.195 | <.001 | Valid |
X24 | 0.54 | 0.195 | <.001 | Valid |
X25 | 0.44 | 0.195 | <.001 | Valid |
X26 | 0.42 | 0.195 | <.001 | Valid |
X27 | 0.60 | 0.195 | <.001 | Valid |
X28 | 0.66 | 0.195 | <.001 | Valid |
X29 | 0.50 | 0.195 | <.001 | Valid |
X30 | 0.57 | 0.195 | <.001 | Valid |
X31 | 0.58 | 0.195 | <.001 | Valid |
X32 | 0.44 | 0.195 | <.001 | Valid |
Source: Researcher, 2025
Based on the validity test results, all statements on variable X have a correlation value rcount more significant than the rtable value of 0.195, so they are declared valid. Thus, all statements on variable X can be used to measure the intended construct accurately.
Table 2. Satisfaction validity test results
Statement | rcount | rtable | Sig. (2-tailed) | Description |
Y1 | 0.58 | 0.195 | <.001 | Valid |
Y2 | 0.28 | 0.195 | 0.005 | Valid |
Y3 | 0.38 | 0.195 | <.001 | Valid |
Y4 | 0.34 | 0.195 | <.001 | Valid |
Y5 | 0.54 | 0.195 | <.001 | Valid |
Y6 | 0.43 | 0.195 | <.001 | Valid |
Y7 | 0.30 | 0.195 | 0.003 | Valid |
Y8 | 0.42 | 0.195 | <.001 | Valid |
Y9 | 0.44 | 0.195 | <.001 | Valid |
Y10 | 0.44 | 0.195 | <.001 | Valid |
Y11 | 0.50 | 0.195 | <.001 | Valid |
Y12 | 0.63 | 0.195 | <.001 | Valid |
Y13 | 0.50 | 0.195 | <.001 | Valid |
Y14 | 0.47 | 0.195 | <.001 | Valid |
Y15 | 0.45 | 0.195 | <.001 | Valid |
Y16 | 0.52 | 0.195 | <.001 | Valid |
Y17 | 0.43 | 0.195 | <.001 | Valid |
Y18 | 0.54 | 0.195 | <.001 | Valid |
Y19 | 0.62 | 0.195 | <.001 | Valid |
Y20 | 0.47 | 0.195 | <.001 | Valid |
Y21 | 0.50 | 0.195 | <.001 | Valid |
Y22 | 0.56 | 0.195 | <.001 | Valid |
Y23 | 0.54 | 0.195 | <.001 | Valid |
Y24 | 0.50 | 0.195 | <.001 | Valid |
Y25 | 0.46 | 0.195 | <.001 | Valid |
Y26 | 0.44 | 0.195 | <.001 | Valid |
Y27 | 0.45 | 0.195 | <.001 | Valid |
Y28 | 0.49 | 0.195 | <.001 | Valid |
Y29 | 0.41 | 0.195 | <.001 | Valid |
Y30 | 0.57 | 0.195 | <.001 | Valid |
Y31 | 0.56 | 0.195 | <.001 | Valid |
Y32 | 0.54 | 0.195 | <.001 | Valid |
Source: Researcher, 2025
Based on the validity test results, all statements on variable Y have a correlation value rcount more significant than the rtable value of 0.195, so they are declared valid. Thus, all statements on variable Y can be used to measure the intended construct accurately.
Table 3. Reliability test results
Variable | Cronbach’s Alpha (α) Hit | Cronbach’s Alpha (α) Table | Total Items | Description |
Expectation (X) | 0.917 | 0.60 | 32 | Reliable |
Satisfaction (Y) | 0.887 | 0.60 | 32 | Reliable |
Source: Researcher, 2025
The reliability test results show a Cronbach’s Alpha (α) value of 0.917 for the Expectation variable (X) and 0.887 for the Satisfaction variable (Y). Because this value is more significant than 0.60, all instruments are declared reliable and can be used for research data collection.
After ensuring that all research instruments have met the validity and reliability requirements, the next step is to analyze the data to calculate the level of customer satisfaction using the Customer Satisfaction Index (CSI) and SERVQUAL methods. The CSI method measures the overall level of satisfaction, while SERVQUAL analysis aims to evaluate the gap between expectations and reality of service in each dimension of service quality. The results of the CSI and SERVQUAL calculations will be the basis for identifying aspects that require service development or improvement.
Customer Satisfaction Index (CSI) Results
The stages of calculating the customer satisfaction index using the Customer Satisfaction Index (CSI) method include several steps, namely calculating the average value of the importance score (Mean Importance Score/MIS), the average satisfaction score (Mean Satisfaction Score/MSS), the weight factor (Weight Factor/WF), the weight score (Weight Score/WS), and the percentage of the overall customer satisfaction index (Customer Satisfaction Index/CSI). In this study, the calculation was carried out with the help of Microsoft Excel 2019 software, and the results are presented in Table 4.
Table 4. Customer Satisfaction Index (CSI) Results
Attribute No. | Yi Total Value | MIS Value | Xi Total Value | MSS Value | WF Value (%) | WS Value |
1 | 455 | 4.55 | 413 | 4.13 | 3.21 | 13.24 |
2 | 417 | 4.17 | 328 | 3.28 | 2.94 | 9.64 |
3 | 435 | 4.35 | 416 | 4.16 | 3.07 | 12.75 |
4 | 445 | 4.45 | 405 | 4.05 | 3.14 | 12.7 |
5 | 437 | 4.37 | 415 | 4.15 | 3.08 | 12.78 |
6 | 442 | 4.42 | 328 | 3.28 | 3.11 | 10.22 |
7 | 402 | 4.02 | 350 | 3.5 | 2.83 | 9.91 |
8 | 451 | 4.51 | 405 | 4.05 | 3.18 | 12.87 |
9 | 452 | 4.52 | 407 | 4.07 | 3.18 | 12.96 |
10 | 442 | 4.42 | 411 | 4.11 | 3.11 | 12.8 |
11 | 432 | 4.32 | 402 | 4.02 | 3.04 | 12.24 |
12 | 445 | 4.45 | 398 | 3.98 | 3.14 | 12.48 |
13 | 447 | 4.47 | 402 | 4.02 | 3.15 | 12.66 |
14 | 441 | 4.41 | 411 | 4.11 | 3.11 | 12.77 |
15 | 444 | 4.44 | 401 | 4.01 | 3.13 | 12.55 |
16 | 448 | 4.48 | 410 | 4.1 | 3.16 | 12.94 |
17 | 441 | 4.41 | 397 | 3.97 | 3.11 | 12.34 |
18 | 449 | 4.49 | 427 | 4.27 | 3.16 | 13.51 |
19 | 444 | 4.44 | 409 | 4.09 | 3.13 | 12.8 |
20 | 449 | 4.49 | 408 | 4.08 | 3.16 | 12.91 |
21 | 447 | 4.47 | 419 | 4.19 | 3.15 | 13.2 |
22 | 445 | 4.45 | 393 | 3.93 | 3.14 | 12.32 |
23 | 442 | 4.42 | 411 | 4.11 | 3.11 | 12.8 |
24 | 448 | 4.48 | 415 | 4.15 | 3.16 | 13.1 |
25 | 465 | 4.65 | 436 | 4.36 | 3.28 | 14.29 |
26 | 452 | 4.52 | 418 | 4.18 | 3.18 | 13.31 |
27 | 456 | 4.56 | 410 | 4.1 | 3.21 | 13.17 |
28 | 439 | 4.39 | 417 | 4.17 | 3.09 | 12.9 |
29 | 435 | 4.35 | 394 | 3.94 | 3.07 | 12.08 |
30 | 443 | 4.43 | 415 | 4.15 | 3.12 | 12.95 |
31 | 449 | 4.49 | 411 | 4.11 | 3.16 | 13 |
32 | 453 | 4.53 | 419 | 4.19 | 3.19 | 13.37 |
TOTAL | 141.9 | 129 | 100% | 403.56 |
Source: Researcher, 2025
The CSI percentage value is calculated by dividing the weighted score by the maximum scale used, so the calculation is as follows:
The results of the CSI calculation show that the total CSI value is 80.71%, which is in the “Satisfied” category. Thus, it can be concluded that most users of the BISKITA Trans Bekasi Patriot service are satisfied with the quality of service provided.
Servqual Value Calculation Results
This study used SERVQUAL analysis to evaluate the gap between passengers’ expectations and perceptions of the BISKITA Trans Bekasi Patriot service. This method measures five dimensions of service quality: Tangible, Reliability, Responsiveness, Assurance, and Empathy. The gap value is calculated based on the difference between the perception (Y) and expectation (X) scores on each dimension, with positive results indicating service advantages and negative results indicating service deficiencies.
Furthermore, the results of the SERVQUAL calculation are presented in tabular form to illustrate the performance of each service dimension and indicator. These results provide a comprehensive picture of aspects that require improvement and strengths that can be maintained.
Table 5. The results of the calculation of the Servqual value of each dimension
Dimensions | Average | gap | Rank | |
Xi | Yi | |||
Tangible | 30,33 | 26,55 | -3,78 | 5 |
Reliability | 22,22 | 20,23 | -1,99 | 1 |
Responsiveness | 31,14 | 28,57 | -2,57 | 4 |
Empathy | 31,48 | 29 | -2,48 | 3 |
Assurance | 26,75 | 24,66 | -2,09 | 2 |
Source: Researcher, 2025
Based on Table 5’s gap analysis of each dimension, to improve the quality of BISKITA Trans Bekasi Patriot services, improvements need to be focused on the Tangible dimension. This dimension has the highest gap between expectations and satisfaction of -3.78, indicating the need for more attention to improving the quality of aspects related to physical facilities. Meanwhile, the Reliability dimension has the smallest gap of -1.99 and is ranked first, indicating that this aspect performs closely to passenger expectations.
CONCLUSION
Based on the results of data analysis, this study found that passenger satisfaction is in the “Satisfied” category, with a Customer Satisfaction Index (CSI) value of 80.71%. The findings also show that the Reliability dimension performs better than other dimensions. However, some aspects of service require attention, especially bus stop facilities, including cleanliness and comfort of seats, as well as the quality of service of officers in handling passenger complaints. As a contribution to the development of public transportation services, the focus of improvement and development should be directed at improving bus stop facilities, such as cleanliness and comfort, and training officers to enhance alertness and friendliness in serving passengers. These findings provide recommendations for service managers to improve operational quality that impacts the satisfaction of public transportation users. From an economic perspective, improving the quality of public transportation services such as BISKITA Trans Bekasi Patriot can positively impact managers and the community. Higher user satisfaction has the potential to increase customer loyalty, which in turn will increase the number of passengers and operating income. In addition, quality public transportation can reduce people’s dependence on private vehicles, thereby reducing individual transportation costs and increasing society’s overall economic efficiency.
REFERENCE
- Aritonang, K. T., 2005, Kepuasan Pelanggan: Sebuah Kerangka Konseptual dan Praktis untuk Pengukuran dan Implementasi dalam Bisnis. Jakarta: Grasindo.
- Badan Pusat Statistik (BPS)., 2023, Laporan Kependudukan dan Urbanisasi Wilayah Kota Bekasi.
- Baiq Ira Dwi Safitri, Eti Kurniati, 2023, “Analisis Tingkat Kepuasan Pengguna Jasa Transportasi Bus
- Damri Terhadap Kinerja Pelayanan Angkutan Umum (Trayek Sumbawa– Mataram)” Jurnal Informasi, Sains, dan Teknologi, Vol. 6, No.2 Desember 2023, Hal 15 – 29
- Bertilla Vanessa Kusuma Prabantari, 2020, “Analisis Hubungan Kualitas Pelayanan Terhadap Tingkat Kepuasan Pelanggan Transportasi Transjakarta,” Jurnal Transaksi, Vol. 12, No. 1
- Creswell, J.W., 2015, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Thousand Oaks, CA: Sage.
- Ghozali, I., 2018, Aplikasi Analisis Multivariate dengan Program IBM SPSS. Semarang: Badan Penerbit Universitas Diponegoro.
- Hada Mahdani Azhar, 2018, “Analisis Pengukuran Tingkat Kepuasan Penumpang Pada Trayek Bus Yogyakarta – Denpasar Mengguakan Metode Service Quality (Servqual) dan Importance Performance Analysis (Ipa) (Studi Kasus Pada Bus Malam PO Safari Dharma Raya”, Laporan Penelitian Tugas Akhir Universitas Islam Indonesia, Yogyakarta
- Husein Umar, 2013, Metode Penelitian untuk Skripsi dan Tesis Bisnis. Jakarta: RajaGrafindo Persada
- Kamilia Ginting, 2022, “Analisis Tingkat Kepuasan Penumpang Terhadap Pelayanan Bus Trans Metro Deli Rute Medan Tuntungan – Lapangan Merdeka”, Laporan Penelitian Universitas Medan Area, Medan
- Kementerian Perhubungan Republik Indonesia., 2005, Tentang Sistem Transportasi Nasional. Peraturan Menteri Perhubungan No. 25 Tahun 2005.
- Kotler, P., & Keller, K. L., 2016, Marketing Management. Pearson Education.
- Munawar, A., 2007, Manajemen Transportasi Publik. Bandung: ITB Press.
- Nasution, M.N., 2000, Manajemen Transportasi. Jakarta: Ghalia Indonesia.
- Parasuraman, A., Zeithaml, V.A., & Berry, L.L., 1988, SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64(1), 12-40.
- Sugiyono, 2020, Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta.
- Sugiyono, 2017, Statistika untuk Penelitian. Bandung: Alfabeta.
- Tamin, O.Z., 2000, Transportasi di Perkotaan. Bandung: ITB Press.
- Tjiptono, F., 2015, Strategi Pemasaran. Edisi ke-4. Yogyakarta: Andi.