[ABSTRAK
Bea masuk sebagai salah satu sumber pendapatan negara merupakan bagian dari penerimaan perpajakan pada subpos penerimaan pajak perdagangan internasional, yang perlu diperkirakan target pencapaiannya sesuai dengan proyeksi kondisi perekonomian di masa yang akan datang. Untuk itu diperlukan suatu model proyeksi penerimaan bea masuk yang akurat agar perencanaan pemerintah yang telah dibuat dapat direalisasikan secara optimal. Penelitian ini bertujuan untuk menganalisis faktor apa saja yang dapat mempengaruhi penerimaan bea masuk, terutama yang terkait dengan faktor makro ekonomi serta sektor industri sesuai jenis lapangan usaha yang ada di dalam perekonomian, untuk kemudian disusun suatu model proyeksi berdasarkan teori ekonomi. Penyusunan model proyeksi penerimaan bea masuk dilakukan secara agregat dan secara sektoral. Secara agreragat yakni penyusunan model menggunakan data komoditi impor yang nilainya bersifat akumulatif, yang telah dikelompokkan sesuai jenis lapangan usaha pada PDB, dengan data tahunan mulai tahun 1982 s.d. 2013. Sedangkan secara sektoral yakni proses penyusunan model dengan menggunakan data komoditi impor yang menyumbang penerimaan bea masuk dalam satu tahun, yang dikelompokkan sesuai HS 4 digit, dengan periode penelitian tahun 2004 s.d. 2013. Teknik penyusunan model menggunakan regresi linier berganda dengan software STATA 12.0 sebagai alat olah data. Hasil penelitian menunjukkan bahwa model proyeksi penerimaan bea masuk yang paling akurat adalah model proyeksi secara agregat, dengan variabel bebas berupa total nilai impor komoditi subsektor pertanian, total nilai impor komoditi subsektor industri non migas, rasio pertumbuhan ekonomi, nilai tukar kurs rupiah terhadap dolar Amerika Serikat serta variebel dummy kebijakan perdagangan bebas;

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ABSTRACT
Import duties as one of state?s income revenue are part of the international trade tax revenue subheading, which the target purpose need to be estimated in accordance with economic condition in the future. This requires a proper model of import duty revenue projection so that the government plans existed can be optimally realized. This study aims to analyze the factors that may affect the import duty revenue, especially those related to macroeconomic factors and industry sectors according to the type of business fields that existed in economic, and then formulate a projection model based on economic theory. Modelling projection of import duty revenue performed in the aggregate and sectoral. In agreragat means that the preparation of the model using data imported commodities whose value is accumulative, which have been grouped according to the type of business field in GDP, with annual data began in 1982 - 2013. Sectoral means that the process of data modelling using annual data imported commodity with largest contribution to import duty revenue, which are grouped according to the HS 4-digit, with a study period of 2004 - 2013. Modelling technique using multiple linear regression with STATA 12.0 software as a data processing tool. The results showed that the model of import duty revenue projections are most accurate in the aggregate projection model, with the independent variables such as the total value of imports of commodity subsectors of agriculture, the total value of imports of non-oil commodity sub-sectors, the economic growth rate, the exchange rate of the rupiah against the U.S. dollar and dummy variable free trade policies.;Import duties as one of state?s income revenue are part of the international trade tax revenue subheading, which the target purpose need to be estimated in accordance with economic condition in the future. This requires a proper model of import duty revenue projection so that the government plans existed can be optimally realized. This study aims to analyze the factors that may affect the import duty revenue, especially those related to macroeconomic factors and industry sectors according to the type of business fields that existed in economic, and then formulate a projection model based on economic theory. Modelling projection of import duty revenue performed in the aggregate and sectoral. In agreragat means that the preparation of the model using data imported commodities whose value is accumulative, which have been grouped according to the type of business field in GDP, with annual data began in 1982 - 2013. Sectoral means that the process of data modelling using annual data imported commodity with largest contribution to import duty revenue, which are grouped according to the HS 4-digit, with a study period of 2004 - 2013. Modelling technique using multiple linear regression with STATA 12.0 software as a data processing tool. The results showed that the model of import duty revenue projections are most accurate in the aggregate projection model, with the independent variables such as the total value of imports of commodity subsectors of agriculture, the total value of imports of non-oil commodity sub-sectors, the economic growth rate, the exchange rate of the rupiah against the U.S. dollar and dummy variable free trade policies.;Import duties as one of state’s income revenue are part of the international trade tax revenue subheading, which the target purpose need to be estimated in accordance with economic condition in the future. This requires a proper model of import duty revenue projection so that the government plans existed can be optimally realized. This study aims to analyze the factors that may affect the import duty revenue, especially those related to macroeconomic factors and industry sectors according to the type of business fields that existed in economic, and then formulate a projection model based on economic theory. Modelling projection of import duty revenue performed in the aggregate and sectoral. In agreragat means that the preparation of the model using data imported commodities whose value is accumulative, which have been grouped according to the type of business field in GDP, with annual data began in 1982 - 2013. Sectoral means that the process of data modelling using annual data imported commodity with largest contribution to import duty revenue, which are grouped according to the HS 4-digit, with a study period of 2004 - 2013. Modelling technique using multiple linear regression with STATA 12.0 software as a data processing tool. The results showed that the model of import duty revenue projections are most accurate in the aggregate projection model, with the independent variables such as the total value of imports of commodity subsectors of agriculture, the total value of imports of non-oil commodity sub-sectors, the economic growth rate, the exchange rate of the rupiah against the U.S. dollar and dummy variable free trade policies., Import duties as one of state’s income revenue are part of the international trade tax revenue subheading, which the target purpose need to be estimated in accordance with economic condition in the future. This requires a proper model of import duty revenue projection so that the government plans existed can be optimally realized. This study aims to analyze the factors that may affect the import duty revenue, especially those related to macroeconomic factors and industry sectors according to the type of business fields that existed in economic, and then formulate a projection model based on economic theory. Modelling projection of import duty revenue performed in the aggregate and sectoral. In agreragat means that the preparation of the model using data imported commodities whose value is accumulative, which have been grouped according to the type of business field in GDP, with annual data began in 1982 - 2013. Sectoral means that the process of data modelling using annual data imported commodity with largest contribution to import duty revenue, which are grouped according to the HS 4-digit, with a study period of 2004 - 2013. Modelling technique using multiple linear regression with STATA 12.0 software as a data processing tool. The results showed that the model of import duty revenue projections are most accurate in the aggregate projection model, with the independent variables such as the total value of imports of commodity subsectors of agriculture, the total value of imports of non-oil commodity sub-sectors, the economic growth rate, the exchange rate of the rupiah against the U.S. dollar and dummy variable free trade policies.]