FORECASTING ANALYSIS MUATAN KENDARAAN DAN ALAT BERAT PADA KAPAL RO – RO RUTE JAKARTA - MAKASSAR (STUDI KASUS : KALLA TRANSPORT & LOGISTICS)

MARINI ANDRIYANI PUTRI, . (2026) FORECASTING ANALYSIS MUATAN KENDARAAN DAN ALAT BERAT PADA KAPAL RO – RO RUTE JAKARTA - MAKASSAR (STUDI KASUS : KALLA TRANSPORT & LOGISTICS). Sarjana thesis, UNIVERSITAS NEGERI JAKARTA.

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Abstract

Muatan kendaraan dan alat berat kapal Ro–Ro PT Kalla Transport dan Logistics rute Jakarta–Makassar berfluktuasi, namun selama ini hanya diproyeksikan dengan rata-rata statis metode Single Moving Average yang belum mempertimbangkan pola tren dan musiman, sehingga berisiko menimbulkan ketidaksesuaian kapasitas kapal. Penelitian ini menganalisis dan memprediksi muatan empat kategori (Roda 2, Roda 4, Roda 6, dan Alat Berat) menggunakan metode Single Moving Average (SMA) dan Holt-Winters Exponential Smoothing model Additive, lalu membandingkan akurasinya untuk menentukan metode terbaik. Pendekatan kuantitatif deskriptif - komparatif diterapkan pada data time series bulanan Januari 2023–Desember 2025, diolah dengan Microsoft Excel (SMA) dan IBM SPSS Statistics (Holt-Winters), dengan akurasi diukur melalui MAPE, RMSE, dan MAE. Hasil menunjukkan Holt-Winters Additive lebih akurat untuk Roda 2 MAPE (42,5%) karena menangkap pola musiman yang dominan, sedangkan SMA-3 lebih akurat untuk Roda 4 MAPE (9,7%), Roda 6 (31,1%), dan Alat Berat (60,5%) karena data yang lebih stabil. Secara keseluruhan, SMA-3 ditetapkan sebagai metode terbaik karena unggul pada tiga dari empat kategori, sehingga pemilihan metode Forecasting perlu disesuaikan dengan karakteristik data masing-masing kategori sebagai dasar perencanaan kapasitas kapal Ro–Ro Jakarta–Makassar. Kata Kunci: Akurasi Prediksi, Forecasting, Holt-Winters Exponential Smoothing, Kapal Ro–Ro, Single Moving Average. / ***** Vehicle and heavy-equipment cargo carried by PT Kalla Transport and Logistics' Ro–Ro vessels on the Jakarta–Makassar route fluctuates, yet has so far only been projected using a static average from the Moving Average method, which does not account for trend and seasonal patterns, creating a risk of mismatch in vessel capacity. This study analyzes and forecasts cargo volume across four categories (two-wheel, four-wheel, and six-wheel vehicles, and heavy equipment) using the Single Moving Average (SMA) and additive Holt-Winters Exponential Smoothing methods, then compares their accuracy to determine the best method. A quantitative descriptive-comparative approach was applied to monthly time-series data from January 2023 to December 2025, processed with Microsoft Excel (SMA) and IBM SPSS Statistics (Holt-Winters), with accuracy measured through MAPE, RMSE, and MAE. The results show that the additive Holt-Winters model is more accurate for two-wheel vehicles (MAPE of 42.5%) because it captures the dominant seasonal pattern, while SMA-3 is more accurate for four-wheel vehicles MAPE (9.7%), six-wheel vehicles (31.1%), and heavy equipment (60.5%) due to their more stable data. Overall, SMA-3 is identified as the best method, outperforming in three of the four categories, indicating that the choice of Forecasting method should be tailored to the data characteristics of each category as a basis for Ro–Ro vessel capacity planning on the Jakarta–Makassar route. Keywords: Forecasting, Forecast accuracy, Holt-Winters Exponential Smoothing, Ro–Ro vessel, Single Moving Average.

Item Type:	Thesis (Sarjana)
Additional Information:	1) Prof. Dr. Henita Rahmayanti, M.Si. 2) Kencana Verawati, S.S.T., M.M.Tr.
Subjects:	Ilmu Sosial > Transportasi Sains > Matematika
Divisions:	FT > D IV Manajemen Pelabuhan dan Logistik Maritim
Depositing User:	Marini Andriyani Putri .
Date Deposited:	05 Aug 2026 04:48
Last Modified:	05 Aug 2026 04:48
URI:	http://repository.unj.ac.id/id/eprint/68508

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