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ANALYSIS OF THE EFFECTIVENESS OF RAILWAY SERVICE IN LAMPUNG ON THE TANJUNG KARANG STATION – KOTABUMI STATION ROUTE

This study aims to analyze the effectiveness of railway services in Lampung on the Tanjung Karang–Kotabumi route from the users’ perspective using a quantitative survey-based approach. The research focuses on Rajabasa (economy class) and Kuala Stabas (premium class) train services. Data were collected through Likert-scale questionnaires and secondary sources using an  accidental simple random sampling  technique. The variables include traveler characteristics, travel characteristics, and transportation system facilities. Data validity and reliability were tested before being analyzed using the  Classification and Regression Tree (CART) method. The results indicate that service effectiveness is strongly influenced by the quality of interaction between staff and passengers as well as the condition of physical carriage facilities. Staff attributes emerge as the most dominant factor with the highest satisfaction scores, while management aspects remain the primary weakness. Differences in facility quality between premium and economy classes and accessibility issues in premium services were also identified. The CART model reveals that integrated operational and service quality is the key determinant, with staff attributes as the strongest predictor. The optimal model was obtained at a 1.5 threshold with high accuracy.

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This study aims to analyze the effectiveness of railway services in Lampung on the Tanjung Karang–Kotabumi route from the users’ perspective using a quantitative survey-based approach. The research focuses on Rajabasa (economy class) and Kuala Stabas (premium class) train services. Data were collected through Likert-scale questionnaires and secondary sources using an  accidental simple random sampling  technique. The variables include traveler characteristics, travel characteristics, and transportation system facilities. Data validity and reliability were tested before being analyzed using the  Classification and Regression Tree (CART) method. The results indicate that service effectiveness is strongly influenced by the quality of interaction between staff and passengers as well as the condition of physical carriage facilities. Staff attributes emerge as the most dominant factor with the highest satisfaction scores, while management aspects remain the primary weakness. Differences in facility quality between premium and economy classes and accessibility issues in premium services were also identified. The CART model reveals that integrated operational and service quality is the key determinant, with staff attributes as the strongest predictor. The optimal model was obtained at a 1.5 threshold with high accuracy.

聚变人工智能代理模型智能控制Service Effectiveness, Railway, CART, Passenger Satisfaction, Transportation
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适用任务状态重建、快速预测、代理计算、参数扫描与设计优化
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核验重点超出训练分布或用于关键工程判断时,应由高保真模型或实验数据复核
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