Meidiani, Siti Astrid (2017) Minimasi Total Biaya Persediaan Komponen Hardware Menggunakan Metode Lot Sizing dan Integer Programming. Sarjana thesis, Universitas Brawijaya.
Abstract
Dalam membuat suatu produk furniture, selain bahan baku utama kayu terdapat komponen hardware yang menjadi salah satu hal yang penting untuk diperhatikan. Terdapat 207 komponen hardware yang digunakan untuk membuat keseluruhan produk. Peneliti menemukan pada komponen hardware sering terjadi penumpukan komponen di gudang dikarenakan kurang tepatnya peramalan oleh perusahaannya. Selain itu tidak terdapat evaluasi internal bidang PPIC dalam merencanakan tingkat persediaan yang menyebabkan tingginya biaya yang dikeluarkan oleh perusahaan. Tujuan dari penelitian ini adalah untuk meminimasi total biaya persediaan komponen hardware dengan memilih komponen hardware yang membutuhkan fokus penganganan kemudian dilakukan peramalan terhadap komponen terpilih. Setelah itu dilakukan perhitungan biaya persediaan dengan mempertimbangkan pemasok komponen agar perusahaan dapat melakukan penghematan terhadap biaya persediaan komponen. Untuk mengatasi permasalahan tersebut, komponen hardware diklasifikasikan dengan metode Always Better Control (ABC) Analysis kemudian komponen terpilih diramalkan permintaannya dengan metode Decomposition, Holt Winter’s Method, Trend Analysis dan Double Exponential Smoothing sesuai dengan pola data. Setelah itu dilakukan perencanaan persediaan hardware dengan metode lot size untuk pemasok yang memasok hanya satu komponen dan integer programming untuk pemasok yang memasok lebih dari satu komponen berdasarkan data historis komponen. Kemudian dibandingkan biayanya dengan existing perusahaan untuk mengetahui metode terbaik yang akan digunakan. Tahap terakhir yaitu dibuat perencanaan persediaan hardware sesuai metode yang terpilih berdasarkan hasil peramalan permintaan komponen hardware. Dari hasil klasifikasi dengan ABC Analysis terdapat lima komponen yang termasuk kategori A yaitu Insert DO 311 M6 x 10mm x 12mm, Metal Extension Rail 37 x 400mm Non Bracket, Metal Extension Rail 37 x 400mm, Knob Metal Townsend+Jp, dan Paku Antique. Peramalan yang dipilih melihat nilai MSD terendah. Untuk komponen Knob Metal Townsend+Jp hasil peramalan menggunakan metode Decomposition multiplicative, nilai koefisien variabilitas < 0,101, menggunakan lot sizing metode Economic Order Quantity (EOQ). Untuk komponen Paku Antique hasil peramalan menggunakan metode Trend Analysis model tipe Quadratic, nilai koefisien variabilitas 0,251, menggunakan lot sizing metode Silver Meal dan Algoritma Wagner Within. Untuk komponen Insert DO 311 M6 x 10mm x 12mm, Metal Extension Rail 37 x 400mm Non Bracket, dan Metal Extension Rail 37 x 400mm hasil peramalan berturut-turut menggunakan metode Decomposition additive, Decomposition additive, Decomposition multiplicative, nilai koefisien variabilitas 0,251; 0,128; 0,354, menggunakan metode integer programming. Perhitungan total biaya persediaan komponen dengan metode terpilih dapat dilakukan penghematan sebesar Rp 536.044.061,86 atau 1,65 %, sehingga metode terpilih dapat digunakan untuk merencanakan persediaan komponen kedepan.
English Abstract
In a process of making a furniture product, beside woods as the raw materials, there is also the hardware component that be the important material to be considered. There are 207 hardware components are used to make a product. The researcher found there are some components that often being overstocked in the warehouse. It is happened because there are some miscalculations by the company on their components’ forecast. Moreover, there is no internal evaluation by PPIC Department on the planning of inventory level and it effects to the high costs that the company has to pay. The purpose of this research is to minimize the total inventory cost of the hardware components by choosing which hardware component that is need to be focused on. After that the forecast is being done on the chosen component. The last step is to calculate the inventory cost by considering the component suppliers so the company could do some savings on the component inventory costs. To resolve the problem, hardware components will be classified by Always Better Control (ABC) Analysis method, then the demand for chosen component will be forecasted by using Decomposition, Holt Winter’s Method, Trend Analysis and Double Exponential Smoothing method, based on their data pattern. Next, the hardware component inventory was calculated by using lot size method, for suppliers which only supplies one component, and integer porgramming method, for supplier which supplies more than one component. The calculation was according to the component’s historical data. The next step was to compare the cost that company had to pay with the existing data to find the best method. The last step was planning the hardware component inventory by using the chosen method based on the result of hardware component’s demand forecast. Based on the classification result by ABC analysis, there are five components that is included in the A category. They are Insert DO 311 M6 x 10mm x 12mm, Metal Extension Rail 37 x 400mm Non-Bracket, Metal Extension Rail 37 x 400mm, Knob Metal Townsend+Jp, and Antique Nail. The forecast that is chosen is based on the lowest MSD. For the Knob Metal Townsend+Jp component, the forecast was calculated by using Decomposition multiplicative method, with variability coefficient < 0,101, and lot sizing using Economic Order Quantity (EOQ) method. For Antique nail component, the forecast was calculated by using Trend Analysis model Quadratic type, with variability coefficient < 0,251, lot sizing using Silver Meal and Algoritma Wagner Within method. For Insert DO 311 M6 x 10mm x 12mm, Metal Extension Rail 37 x 400mm Non Bracket, dan Metal Extension Rail 37 x 400mm components, the forecast was calculated, accordingly, by using Decomposition additive, Decomposition additive, Decomposition multiplicative method, with their variability coefficient 0,251; 0,128; 0,354, using integer programming method. This calculation of total inventory cost, using the chosen methods, could save up to Rp 536.044.061,86 or 1,65 %. In conclusion, the chosen method could be used to plan the future component’s inventory.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FT/2017/385/051704626 |
| Uncontrolled Keywords: | pengendalian persediaan, Analisis ABC, Peramalan, EOQ, Silver Meal, Algoritma Wagner Within, Integer Programming. |
| Subjects: | 600 Technology (Applied sciences) > 621 Applied physics > 621.3 Electrical, magnetic, optical, communications, computer engineering; electronics, lighting > 621.39 Computer engineering |
| Divisions: | Fakultas Teknik > Teknik Industri |
| Depositing User: | Budi Wahyono Wahyono |
| Date Deposited: | 07 Sep 2017 02:27 |
| Last Modified: | 11 Nov 2020 01:36 |
| URI: | http://repository.ub.ac.id/id/eprint/2192 |
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