Skripsi
KLASIFIKASI DATA KOMUTER UNTUK MENENTUKAN TINGKAT KEPUASAN HIDUP KOMUTER MENGGUNAKAN ALGORITMA C4.5
Commuters travel far from their home areas back and forth every day to work. Long trips make commuters lose a lot of time, energy, and thoughts, especially if their income is not commensurate so that it affects the quality or life satisfaction of commuters. Low life satisfaction can lead to mental health disorders. Low life satisfaction also adversely affects commuters performance in the company. Therefore, through this research commuters life satisfaction needs to be studied more deeply with the aim of knowing what factors influence it, then determining commuter life satisfaction based on these factors. Classification with the CRISP-DM method can be a solution. Classification was performed using the RapidMiner with the C4.5 algorithm. Classification was carried out on commuter life satisfaction data in Jabodetabek with 3 commuter life satisfaction classes, namely very satisfied, normal and very dissatisfied and 18 other variables. The classification produces 116 decision trees that become rules for determining commuter life satisfaction. Testing using 10-Folds Cross Validation result an accuracy of 86.44%. The analysis results can be take as a decisions for the company policy.
Inventory Code | Barcode | Call Number | Location | Status |
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2307004351 | T104783 | T1047832023 | Central Library (Reference) | Available but not for loan - Not for Loan |
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