Magang di PT. Samator - Jakarta

Nurmalasari, Selly (2025) Magang di PT. Samator - Jakarta. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

PT Samator merupakan perusahaan yang bergerak di bidang produksi dan distribusi gas industri, termasuk Produk A sebagai salah satu komoditas utama dalam rantai pasoknya. Dalam operasionalnya, perusahaan menghadapi tantangan berupa fluktuasi permintaan yang tidak menentu, keterbatasan kapasitas distribusi, serta kebutuhan pengelolaan armada yang efisien. Ketidaktepatan dalam memperkirakan volume pengiriman dapat menyebabkan kelebihan atau kekurangan produksi, yang berdampak pada meningkatnya biaya logistik atau tidak terpenuhinya permintaan pelanggan. Sebagai pendukung efisiensi logistik dan perencanaan distribusi, dibutuhkan suatu metode peramalan yang mampu memprediksi volume pengiriman secara akurat. Penelitian ini bertujuan untuk membangun model peramalan delivery quantity Produk A di wilayah Jawa Tengah menggunakan metode Autoregressive Integrated Moving Average (ARIMA). Data yang digunakan dalam penelitian ini merupakan data dummy dari simulasi volume pengiriman harian dari Januari hingga Juni 2025. Data kemudian dibagi menjadi data training sebesar 80% dan testing sebesar 20%. Hasil identifikasi pola menggunakan Autocorrelation Function (ACF) dan Partial Autocorrelation Function (PACF) serta estimasi parameter menunjukkan bahwa model terbaik adalah ARIMA(0,1,1). Evaluasi performa model menghasilkan nilai MAE sebesar 23,82, RMSE sebesar 662,89, dan MAPE sebesar 15,8%, yang mengindikasikan tingkat akurasi peramalan yang cukup baik. Peramalan dilakukan sebanyak 35 hari ke depan dan dibandingkan dengan data aktual.
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PT Samator is a company engaged in the production and distribution of industrial gases, including Product A as one of the main commodities in its supply chain. In its operations, the company faces challenges in the form of uncertain demand fluctuations, limited distribution capacity, and the need for efficient fleet management. Inaccuracy in estimating delivery volume can lead to overproduction or underproduction, which impacts increased logistics costs or unmet customer demand. To support logistics efficiency and distribution planning, a forecasting method is needed that can accurately predict delivery volume. This study aims to build a forecasting model for Product A delivery quantity in the Central Java region using the Autoregressive Integrated Moving Average (ARIMA) method. The data used in this study are dummy data from daily delivery volume simulations from January to June 2025. The data is then divided into training data of 80% and testing data of 20%. The results of pattern identification using the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) as well as parameter estimation indicate that the best model is ARIMA(0,1,1). The model performance evaluation yielded an MAE of 23.82, an RMSE of 662.89, and a MAPE of 15.8%, indicating a fairly good level of forecasting accuracy. Forecasts were performed 35 days in advance and compared with actual data.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	ARIMA, Delivery Quantity, Peramalan, PT Samator, Forecast
Subjects:	H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HA Statistics > HA31.38 Data envelopment analysis.
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Selly Nurmalasari
Date Deposited:	31 Jul 2025 10:26
Last Modified:	31 Jul 2025 10:26
URI:	http://repository.its.ac.id/id/eprint/125207

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