ABSTRAK
Telah menjadi fenomena dewasa ini bahwa perusahaan otomotif dituntut untuk tetap bisa menekan biaya investasi inventori sekecil mungkin agar tetap bisa bersaing. Kondisi pasar sulit diprediksi, bila penjualan menurun kebijakan produksi dan metode peramalan juga kurang tepat, mengakibatkan begitu banyak mobil yang tidak terjual dan terjebak di gudang bahkan terjebak dalam waktu yang sangat lama Deadstock , akibatnya biaya inventasi inventori besar. Ditahun 2015 saja ada sekitar 600 sampai 1500 unit deadstock yang tersimpan di gudang PT.X per bulannya, itu menelan sekitar 194 juta biaya persediaan. Jika dihitung beserta kehilangan keuntungan kesempatan maka PT.X mengalami kerugian sebesar 1,86 triliun. Penelitian ini fokus kepada mobil dengan penjualan tertinggi saja.Dalam penelitian ini digunakan metode regresi simultan gauss-seidell yang disimulasikan untuk usulan pemecahan masalah deadstock yang sedang terjadi. Persamaan regresi simultan tersebut dibentuk dari berbagai macam faktor yang mempengaruhi jumlah deadstock yaitu Faktor eksternal seperti jumlah permintaan, diskon, brand images, kualitas design, kompetitor, inflasi, suku bunga dan faktor internal seperti jumlah defect, kecepatan produksi, loss time, kehadiran operator, Proses delivery dan sbg. Dihasilkan bahwa dengan kebijakan menaikkan jumlah diskon 60 dan 100 , menambah kualitas design dan launching model baru berturut-turut dapat menurangi jumlah deadstock 20.9 s.d 50.47 .

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ABSTRACT
It has become a phenomenon today that automotive companies are required to keep the cost of inventory as small as possible in order to remain competitive. Market conditions are difficult to predict. When sales do not go smoothly, production policies and forecasting methods are also less precise, resulting in so many unsold cars and trapped in the warehouse, even stuck in a very long time Deadstock , resulting in large inventory inventory costs and lost profit opportunities. In 2015 alone there were about 600 to 1500 deadstock units stored in the PT.X warehouse per month, it consumed about 194 million inventory costs. If calculated along with a loss of profit opportunity then PT.X suffered a loss of 1.86 trillion. This study focuses on the car with the highest sales only.In this study used simultaneous equations regression method gauss seidell that simulated to proposed such problem solving deadstock that occured. Simultaneous regressions are formed from various factors that affect to number of deadstock. External factors such as the number of demand, discounts, brand images, design quality, competitors, inflation, interest rates and internal factors such as number of defects, production speed, loss time, operator presence, delivery process and ect. It was found that with the policy of increasing the discount amount of 60 and 100 , enhance quality design and launching new model consecutively can reduce the number of deadstock 20.9 up to 50.47 .