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All Journal Jurnal Industrial Galuh eProceedings of Engineering Sainteks: Jurnal Sain dan Teknik
Nisa Noviani Sudarman
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Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Penentuan Jumlah Perencanaan Permintaan Pelumas Untuk Meminimasi Tingkat Kesalahan Peramalan Berdasarkan Peramalan Permintaan Pelumas Pada Pt. Nyz Nisa Noviani Sudarman; Luciana Andrawina; Rio Aurachman
eProceedings of Engineering Vol 3, No 2 (2016): Agustus, 2016
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

PT NYZ merupakan perusahaan divisi pelumas dari perusahaan minyak nasional PT ABC (Persero) yang berbentuk perseroan terbatas (PT). PT NYZ ini mempunyai akurasi peramalan yang rendah sehingga menyebabkan terjadinya overstock. Hal ini terjadi diakibatkan karena PT NYZ tidak melakukan peramalan permintaan berdasarkan kriteria yang dimiliki oleh PT NYZ, perusahaan hanya melihat berdasarkan data historis. Oleh karena itu, untuk mengatasi permasalahan tersebut maka perlu adanya peramalan permintaan dengan metode yang sesuai. Dalam penelitian ini, metode yang digunakan adalah metode naïve approach, moving average, exponential smoothing, regresi linear, dan konstan dikarenakan pola data permintaan yang terbentuk memiliki pola trend, musiman, dan siklis. Berdasarkan hasil perhitungan peramalan permintaan yang dilakukan, metode yang terpilih adalah metode regresi linear untuk 46 jenis pelumas dan metode konstan untuk 3 jenis pelumas lainnya. Metode ini terpilih karena memliki nilai kesalahan peramalan terendah. Nilai kesalahan peramalan diolah dengan melakukan perhitungan mean square error (MSE). Dengan terpilihnya kedua metode tersebut maka kesalahan peramalan yang terjadi menjadi turun sebesar 30839278.56 atau sama dengan 84.92% dari kesalahan peramalan kondisi awal dan overstock yang terjadi dapat menurun sebesar 88.34%. Dari hasil tersebut maka diperlukan penerapan peramalan permintaan pelumas di PT NYZ dengan metode yang sudah terpilih dan mengaplikasikannya dalam sebuah aplikasi yang mendukung. Kata Kunci : Peramalan, Overstock, Regresi Linear, Konstan, Mean Square Error (MSE)
Batch Scheduling Model For a Flow Shop Two Stage to Minimize Total Actual Flow Time Sudarman, Nisa Noviani
Sainteks: Jurnal Sain dan Teknik Vol 6 No 2 (2024): September
Publisher : Universitas Insan Cendekia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37577/sainteks.v6i02.646

Abstract

This research concerns a batch scheduling problem with the process time used in the existing batch scheduling research can vary. One of the factors influencing processing time is machine deterioration and learning-forgetting process. The effect of the deterioration can results in a longer process time due to decreased machine capability, as well as an increase in service life or usage. The effect of the learning process can result in a faster product processing time due to an increase in operator experience in processing the product. Meanwhile, the effect of the forgetting process can result in slower product processing times due to the lag time between processing of the same product. This research proposes a batch scheduling model for a flow shop with a processing tow-item with considering of the deterioration process in Stage One and learning-forgetting process in Stage Two. The objectives is to minimize total actual flow time. The decision variables in this research are number of batch (?), batch size (Qi), and batch processing sequence. The problem-solving method was developed by proposed heuristic algorithms.The proposed algorithm is consist of batching sub algorithm, and sequence sub algorithm. Numerical testing shows that the proposed algorithm is able to solve the problem of a batch scheduling for a flow shop to minimize total actual flow time and the solution obtained by the algorithm is a feasible solution.
ANALISIS PERBANDINGAN METODE FORECASTING DEMAND UNTUK OPTIMASI PERSEDIAAN BAHAN BAKU DI DIETGO KITCHEN Sudarman, Nisa Noviani
Jurnal Industrial Galuh Vol. 7 No. 2 (2025): Jurnal Industrial Galuh
Publisher : Teknik Industri Fakultas Teknik UNIGAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jig.v7i2.5327

Abstract

Choosing an appropriate demand forecasting approach plays a vital role in ensuring effective management of raw material inventories. Yet, catering businesses face unpredictable and constantly evolving market conditions, which makes it extremely difficult to achieve accurate forecasts. Furthermore, no single forecasting technique can universally address raw material inventory management challenges. As such, selecting an appropriate method depends on the specific context. This study applies both the Autoregressive Integrated Moving Average (ARIMA) model and Exponential Smoothing, with their performance assessed using accuracy metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The results show that Exponential Smoothing delivers more accurate forecasts for the baked grilled chicken menu, while ARIMA performs better for other dishes including beef sei, chicken sei, beef slices, sambal bawang, and lamb sei. By implementing these tailored forecasting approaches, DietGo Kitchen can optimize supply chain operations, minimize material waste, and enhance customer service quality.
Co-Authors Luciana Andrawina Rio Aurachman