Pemodelan Breakdown Kapal PT. ABC Menggunakan Metode Regresi Berganda dan Regresi Poisson

Pratomo, Patrick and Alta Zaidan, Muhammad Rafli (2024) Pemodelan Breakdown Kapal PT. ABC Menggunakan Metode Regresi Berganda dan Regresi Poisson. Project Report. [s.n], [s.l.]. (Unpublished)

Text 5006211004_5006211042-Project_Report.pdf - Accepted Version Restricted to Repository staff only Download (3MB) | Request a copy

Abstract

Penelitian ini menganalisis faktor-faktor yang memengaruhi terjadinya breakdown kapal suatu logistik pelayaran menggunakan data historis tahun 2023. Breakdown kapal merupakan tantangan serius dalam industri pelayaran karena dapat menyebabkan downtime operasional dan kerugian ekonomi. Dua metode pemodelan statistik, regresi linear berganda dan regresi Poisson, digunakan untuk menentukan faktor yang berpengaruh signifikan. Data yang dianalisis mencakup usia mesin, durasi operasional, kualitas kru, konsistensi perawatan, dan jenis spare part. Hasil menunjukkan bahwa regresi Poisson lebih optimal dibandingkan regresi linear berganda berdasarkan nilai AIC. Faktor-faktor seperti konsistensi perawatan dan kualitas kru ditemukan memiliki pengaruh signifikan terhadap jumlah breakdown. Penelitian ini memberikan wawasan penting untuk menyusun strategi pemeliharaan yang efektif dan meningkatkan efisiensi operasional, sehingga diharapkan dapat membantu mengurangi frekuensi breakdown pada logistik pelayaran.
============================================================================================================================
This study analyzes the factors that influence the occurrence of ship breakdown of a shipping logistics using historical data for 2023. Ship breakdown is a serious challenge in the shipping industry as it can cause operational downtime and economic losses. Two statistical modeling methods, multiple linear regression and Poisson regression, were used to determine the significant influencing factors. The data analyzed included engine age, operational duration, crew quality, maintenance consistency, and spare part type. Results showed that Poisson regression was more optimal than multiple linear regression based on the AIC value. Factors such as maintenance consistency and crew quality were found to have a significant influence on the number of breakdowns. This research provides important insights for devising effective maintenance strategies and improving operational efficiency, thus hopefully helping to reduce the frequency of breakdowns in shipping logistics.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	Breakdown Kapal, Regresi Berganda, Regresi Poisson, None Elimination, Backward Elimination
Subjects:	H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Patrick Pratomo
Date Deposited:	08 Jan 2025 07:38
Last Modified:	08 Jan 2025 07:38
URI:	http://repository.its.ac.id/id/eprint/116198

Actions (login required)

View Item