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Penelitian ini bertujuan untuk mengeksplorasi faktor makroekonomi yang mempengaruhi ekspor di Indonesia. Data yang digunakan dalam penelitian ini adalah data sekunder yaitu data ekspor, inflasi, suku bunga, dan nilai tukar pada periode 1998-2022 yang dipublikasikan oleh Badan Pusat Statistik dan Bank Indonesia. Penelitian ini menggunakan pendekatan kuantitatif. Metode analisis data yang digunakan dalam penelitian ini adalah model Vector Error Correction Model (VECM) dengan data time series, data diolah dengan menggunakan program eviews 10. Hasil pengujian VECM dalam jangka panjang inflasi berpengaruh positif dan signifikan terhadap ekspor, suku bunga berpengaruh negatif dan signifikan terhadap ekspor. Untuk jangka pendek inflasi berpengaruh negatif dan signifikan terhadap ekspor, suku bunga berpengaruh positif dan signifikan terhadap ekspor, dan nilai tukar pada jangka panjang dan pendek berpengaruh negatif dan tidak signifikan terhadap ekspor.

Damage that occurs to manufactured goods can occur due to several things, such as in the manufacturing process, in the packaging process or during the delivery process. To find out where when the goods were damaged and the factors causing the damage to the goods as well as the efforts made to reduce the damage to the goods, an investigation was carried out at the time of unloading the goods, to find out where the damage to the goods occurred so as not to harm the recipient of the goods if they received the goods in damage condition.Based on multiple linear regression analysis, the results obtained are Y = 3.133 + 0.044 X1, + 0.402 X2 + 0.299 X3 + . Partial test results of machine (X1), material (X2), man power (X3) have a positive and significant effect on damage goods. It is proven by the results of the comparison of the value of t count with t table and with a significant level comparison of 5% (0.05) where the machine variable t count (0.413) < t table (1.98609), material variable t count (3.142) > t table (1.98609), variable man power t count (2.990) > t table (1.98609). The R2 test of machines, materials and man power gave a significant effect on damage goods by 43.6%, while the remaining 56.4% was explained by other causes outside the model variables that were not examined.