TY - GEN
T1 - Online Transportation Order Matching Considering Passenger Priority Using Recency Frequency Monetary Method
AU - Handojo, Andreas
AU - Pujawan, Nyoman
AU - Santosa, Budi
AU - Singgih, Moses Laksono
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.
PY - 2023
Y1 - 2023
N2 - With the development of transportation technology, online transportation is one of the choices of public transportation which is currently growing rapidly. Passengers can book transportation services through the app. The application will appoint a driver to fulfill the order. It takes a system that can prioritize service to loyal customers, to get priority to be served first. This is important in retaining loyal customers. In this research, the Recency Frequency Monetary (RFM) method was used to classify loyal customers. Based on this classification, drivers are appointed to fulfill orders from passengers (order matching). The method used to pair drivers and passengers is the Hungarian method. The simulation of this system will be tested using the Google Maps API. Based on the tests carried out, the results obtained that the system made was able to prioritize the fulfillment of orders from passengers based on its Recency Frequency Monetary value.
AB - With the development of transportation technology, online transportation is one of the choices of public transportation which is currently growing rapidly. Passengers can book transportation services through the app. The application will appoint a driver to fulfill the order. It takes a system that can prioritize service to loyal customers, to get priority to be served first. This is important in retaining loyal customers. In this research, the Recency Frequency Monetary (RFM) method was used to classify loyal customers. Based on this classification, drivers are appointed to fulfill orders from passengers (order matching). The method used to pair drivers and passengers is the Hungarian method. The simulation of this system will be tested using the Google Maps API. Based on the tests carried out, the results obtained that the system made was able to prioritize the fulfillment of orders from passengers based on its Recency Frequency Monetary value.
KW - Customer segmentation
KW - Hungarian
KW - Online transportation
KW - Recency frequency monetary
UR - http://www.scopus.com/inward/record.url?scp=85174711999&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-1245-2_31
DO - 10.1007/978-981-99-1245-2_31
M3 - Conference contribution
AN - SCOPUS:85174711999
SN - 9789819912445
T3 - Lecture Notes in Mechanical Engineering
SP - 331
EP - 338
BT - Proceedings of the 6th Asia Pacific Conference on Manufacturing Systems and 5th International Manufacturing Engineering Conference - APCOMS-IMEC 2022
A2 - Rosyidi, Cucuk Nur
A2 - Laksono, Pringgo Widyo
A2 - Jauhari, Wakhid Ahmad
A2 - Hisjam, Muhammad
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th Asia Pacific Conference on Manufacturing System and the 5th International Manufacturing Engineering Conference, APCOMS-IMEC 2022
Y2 - 27 October 2022 through 28 October 2022
ER -
