TRANSAKSI AFILIASI DAN CAPITAL INTENSITY MEMPENGARUHI EMITEN DALAM MENGHINDARI PAJAK

Abstract- Target of tax for several last year show increase positive as need of fund on State Budget. But on the other hand of emiten which listing in stock exchange Indonesia always comply to efisiensy of tax as tax planning. That is way by this research expected to find solution about what was variable effect to emiten comply tax efisiensy. Target of population were emiten which stock exchange for 3 year periode 2015 until 2017. Purposive sampling was choose to find out research data. The research selected 54 emiten as sample for representative of emitens. Tax avoidance was measured by proxy effective tax rates; affiliated transaction was measured by liabilities transaction affiliated. Hyphotesis was examined by multiple regression dan decision that: 1) Transaction affiliated affect emiten Industry manufacturing sector listed in Indonesia Stock Exchange during period in 2015-2017 for comply tax avoidance. Emitens have indication often make transaction with group (affiliated) for tax avoidance; 2) Capital intensity not affect emiten manufacturing sector listed in Indonesia Stock Exchange during period in 2015-2017 for comply tax avoidance. Emitens listed in Bursa Efek Indonesia higest invested on fixed asset not objective for tax avoidance but to support operating activity inclined rise. Keywords: Affiliated Transaction, Capital Intensity, Tax Avoidance,

ATTENet: Detecting and Explaining Suspicious Tax Evasion Groups

In this demonstration, we present ATTENet, a novel visual analytic system for detecting and explaining suspicious affiliated-transaction-based tax evasion (ATTE) groups. First, the system constructs a taxpayer interest interacted network, which contains economic behaviors and social relationships between taxpayers. Then, the system combines basic features and structure features of each group in the network with network embedding method structure2Vec, and then detects suspicious ATTE groups with random forest algorithm. Last, to explore and explain the detection results, the system provides an ATTENet visualization with three coordinated views and interactive tools. We demonstrate ATTENet on a non-confidential dataset which contains two years of real tax data obtained by our cooperative tax authorities to verify the usefulness of our system.