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Perpetrators ) /K [6] /P 25 0 R /Pg 5 0 R >> endobj 29 0 obj << /S /Span /Type /StructElem /ActualText (are often aware of the presence of CCTV and use face coverings and cover license plates to ) /K [7] /P 25 0 R /Pg 5 0 R >> endobj 30 0 obj << /S /Span /Type /StructElem /ActualText (avoid recording. However, CCTV has a limited viewing angle, which is) /K [8] /P 25 0 R /Pg 5 0 R >> endobj 31 0 obj << /S /Span /Type /StructElem /ActualText ( ) /K [9] /P 25 0 R /Pg 5 0 R >> endobj 32 0 obj << /S /Span /Type /StructElem /ActualText (not able to monitor a ) /K [10] /P 25 0 R /Pg 5 0 R >> endobj 33 0 obj << /S /Span /Type /StructElem /ActualText (large area. This makes the community restless and feel disadvantaged by the actions of these ) /K [11] /P 25 0 R /Pg 5 0 R >> endobj 34 0 obj << /S /Span /Type /StructElem /ActualText (individuals. Motorcycle theft cases are increasing in various parts of Indonesia. Ironically, ) /K [12] /P 25 0 R /Pg 5 0 R >> endobj 35 0 obj << /S /Span /Type /StructElem /ActualText (perpetrators often use stolen motorbikes when ) /K [13] /P 25 0 R /Pg 5 0 R >> endobj 36 0 obj << /S /Span /Type /StructElem /ActualText (committing theft in groups or pairs. This ) /K [14] /P 25 0 R /Pg 5 0 R >> endobj 37 0 obj << /S /Span /Type /StructElem /ActualText (makes it difficult for the authorities to identify the perpetrators. Law enforcement officers ) /K [15] /P 25 0 R /Pg 5 0 R >> endobj 38 0 obj << /S /Span /Type /StructElem /ActualText (need sound recordings from two) /K [16] /P 25 0 R /Pg 5 0 R >> endobj 39 0 obj << /S /Span /Type /StructElem /ActualText (-) /K [17] /P 25 0 R /Pg 5 0 R >> endobj 40 0 obj << /S /Span /Type /StructElem /ActualText (wheeled vehicles used by perpetrators in the form of 2) /K [18] /P 25 0 R /Pg 5 0 R >> endobj 41 0 obj << /S /Span /Type /StructElem /ActualText (-) /K [19] /P 25 0 R /Pg 5 0 R >> endobj 42 0 obj << /S /Span /Type /StructElem /ActualText (stroke and 4) /K [20] /P 25 0 R /Pg 5 0 R >> endobj 43 0 obj << /S /Span /Type /StructElem /ActualText (-) /K [21] /P 25 0 R /Pg 5 0 R >> endobj 44 0 obj << /S /Span /Type /StructElem /ActualText (stroke engines to fac) /K [22] /P 25 0 R /Pg 5 0 R >> endobj 45 0 obj << /S /Span /Type /StructElem /ActualText (ilitate identification.) /K [23] /P 25 0 R /Pg 5 0 R >> endobj 46 0 obj << /S /Span /Type /StructElem /ActualText ( ) /K [24] /P 25 0 R /Pg 5 0 R >> endobj 25 0 obj << /S /P /Type /StructElem /K [24 0 R 26 0 R 27 0 R 28 0 R 29 0 R 30 0 R 31 0 R 32 0 R 33 0 R 34 0 R 35 0 R 36 0 R 37 0 R 38 0 R 39 0 R 40 0 R 41 0 R 42 0 R 43 0 R 44 0 R 45 0 R 46 0 R] /P 20 0 R >> endobj 47 0 obj << /S /Span /Type /StructElem /ActualText ( ) /K [25] /P 48 0 R /Pg 5 0 R >> endobj 49 0 obj << /S /Span /Type /StructElem /ActualText (In detecting 2) /K [26] /P 48 0 R /Pg 5 0 R >> endobj 50 0 obj << /S /Span /Type /StructElem /ActualText (-) /K [27] /P 48 0 R /Pg 5 0 R >> endobj 51 0 obj << /S /Span /Type /StructElem /ActualText (stroke and 4) /K [28] /P 48 0 R /Pg 5 0 R >> endobj 52 0 obj << /S /Span /Type /StructElem /ActualText (-) /K [29] /P 48 0 R /Pg 5 0 R >> endobj 53 0 obj << /S /Span /Type /StructElem /ActualText (stroke engine vehicles can be done through the sound ) /K [30] /P 48 0 R /Pg 5 0 R >> endobj 54 0 obj << /S /Span /Type /StructElem /ActualText /K [31] /P 48 0 R /Pg 5 0 R >> endobj 55 0 obj << /S /Span /Type /StructElem /ActualText (method plays a role in extracting data characteristics. Furthe) /K [32] /P 48 0 R /Pg 5 0 R >> endobj 56 0 obj << /S /Span /Type /StructElem /ActualText (rmore, the data characteristics ) /K [33] /P 48 0 R /Pg 5 0 R >> endobj 57 0 obj << /S /Span /Type /StructElem /ActualText (will be classified using the K) /K [34] /P 48 0 R /Pg 5 0 R >> endobj 58 0 obj << /S /Span /Type /StructElem /ActualText (-) /K [35] /P 48 0 R /Pg 5 0 R >> endobj 59 0 obj << /S /Span /Type /StructElem /ActualText (Nearest Neighbor \(KNN\) algorithm. The input training data is ) /K [36] /P 48 0 R /Pg 5 0 R >> endobj 60 0 obj << /S /Span /Type /StructElem /ActualText (then extracted in MFCC. The voice data characteristics will be stored in the database file ) /K [37] /P 48 0 R /Pg 5 0 R >> endobj 61 0 obj << /S /Span /Type /StructElem /ActualText (and will be used for further processing. ) /K [38] /P 48 0 R /Pg 5 0 R >> endobj 62 0 obj << /S /Span /Type /StructElem /ActualText (After completing the input in the feature extraction ) /K [39] /P 48 0 R /Pg 5 0 R >> endobj 63 0 obj << /S /Span /Type /StructElem /ActualText (process, the voice data will be classified by KNN using the data characteristics that have ) /K [40] /P 48 0 R /Pg 5 0 R >> endobj 64 0 obj << /S /Span /Type /StructElem /ActualText (been stored. The result of this system is to bring up the accuracy value and computation time.) /K [41] /P 48 0 R /Pg 5 0 R >> endobj 65 0 obj << /S /Span /Type /StructElem /ActualText ( ) /K [42] /P 48 0 R /Pg 5 0 R >> endobj 48 0 obj << /S /P /Type /StructElem /K [47 0 R 49 0 R 50 0 R 51 0 R 52 0 R 53 0 R 54 0 R 55 0 R 56 0 R 57 0 R 58 0 R 59 0 R 60 0 R 61 0 R 62 0 R 63 0 R 64 0 R 65 0 R] /P 20 0 R >> endobj 66 0 obj << /S /Span /Type /StructElem /ActualText ( ) /K [43] /P 67 0 R /Pg 5 0 R >> endobj 68 0 obj << /S /Span /Type /StructElem /ActualText (This research wi) /K [44] /P 67 0 R /Pg 5 0 R >> endobj 69 0 obj << /S /Span /Type /StructElem /ActualText (ll process voice recording data using the Matlab application. Matlab ) /K [45] /P 67 0 R /Pg 5 0 R >> endobj 70 0 obj << /S /Span /Type /StructElem /ActualText (is used to find feature extraction using MFCC and find classification using KNN. Then enter ) /K [46] /P 67 0 R /Pg 5 0 R >> endobj 71 0 obj << /S /Span /Type /StructElem /ActualText (the data processing process as much as 71 training data and 20 test data as a calculation ) /K [47] /P 67 0 R /Pg 5 0 R >> endobj 72 0 obj << /S /Span /Type /StructElem /ActualText (and s) /K [48] /P 67 0 R /Pg 5 0 R >> endobj 73 0 obj << /S /Span /Type /StructElem /ActualText (imulation process. The result of the accuracy value obtained from the identification of ) /K [49] /P 67 0 R /Pg 5 0 R >> endobj 74 0 obj << /S /Span /Type /StructElem /ActualText (motorcycle types based on characteristics with the MFCC and KNN methods is 95.00%. 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