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Jurnal Manajemen Bisnis Transportasi dan Logistik
Published by Institut Transportasi dan Logistik Trisakti
ISSN : 23565519     EISSN : 2407635X     DOI : 10.54324
Core Subject : Economy, Science, Social, Engineering,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences Transportation
The Journal of Transportation and Logistics Business Management is published by the Fakultas Manajamen dan Bisnis Institut Transportasi dan Logistik Trisakti as a scientific responsibility and the embodiment of the "Tridharma" of higher education. The scope of the article includes: Digital Service Management in Transportation and Logistics Multimodal Transportation Management Logistics Management Supply Chain Management Transport and Tourism Management Transport and Environment Safety in Transportation and Logistics Transportation Management
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 1 Documents
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Search results for , issue "Vol. 11 No. 2 (2025): December" : 1 Documents clear
Seasonality and Operational Delays in Palm Kernel Trucking: Evidence from Central Kalimantan (2022–2024) Veronica, Veronica; Raga, Paulus; Fakhruddin, Muhammad; Farid, Muhamad
Jurnal Manajemen Bisnis Transportasi dan Logistik Vol. 11 No. 2 (2025): December
Publisher : Institut Transportasi dan Logistik Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54324/j.mbtl.v11i2.2546

Abstract

Timely distribution of Palm Kernel (PK) is critical for maintaining Free Fatty Acid (FFA) levels and supply chain stability, yet logistical inefficiencies persist in the Indonesian palm oil sector. This study empirically investigates the determinants of shipment delays within the trucking logistics framework of a major Palm Oil Mill in Central Kalimantan from 2022 to 2024. Utilizing a mixed-methods approach, the research integrates historical shipment data (N=119), field observations, and linear regression analysis to evaluate six potential delay factors. The findings reveal a 23.5% delay rate over the three-year period, with 'Long Holidays' (religious festivals) and 'Weather/Road Conditions' identified as the most significant predictors of lateness, particularly in 2024 where holidays showed a dominant regression coefficient (β=0.962). Unlike previous studies focusing solely on infrastructure, this research highlights a shift toward seasonal operational constraints and transporter performance. The study implies that technical fleet upgrades are insufficient without adaptive scheduling strategies. Consequently, implementing predictive logistics planning around seasonal events and real-time infrastructure monitoring is recommended to mitigate delays, offering a practical framework for enhancing supply chain resilience in the tropical agricultural industry.

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