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"Penelitian ini bertujuan untuk mengetahui dampak penerapan kebijakan Electronic Road Pricing (ERP) yang diberlakukan di Jakarta. Kebijakan ERP yang diberlakukan menggunakan sistem zonasi kawasan. Metode analisis dalam penelitian ini berbasis pada model pemilihan diskrit logit binomial. Untuk menggunakan model logit binomial perlu dibangun fungsi utilitas dengan menggunakan pendekatan regresi logistik. Model regresi dari fungsi utilitas dibangun dari data hasil survei Stated Preference dan Revealed Preference. Proses pembangunan model regresi logistik diawali dengan uji korelasi menggunakan metode uji spearman, lalu uji kelayakan model menggunakan metode uji hosmer lemmeshow dan omnibus, uji validasi menggunakan metode uji RMSE (Root Mean Square Error), analisis pemilihan model dengan syarat lolos uji kelayakan dan uji validasi serta uji komparasi, uji sensitifitas, dan analisis potensi perpindahan moda. Hasil uji korelasi menunjukkan variabel bebas yang siginifikan pada penelitian ini yaitu tarif ERP. Dari hasil analisis hubungan Willingness To Pay (WTP) dengan Willingness To Shift (WTS) dibangun 6 fungsi utilitas yang didasarkan atas perpindahan zona karena terdapat pola preferensi yang cenderung sama antar perpindahan zona lainnya tetapi memiliki tingkat persentase WTP dan WTS yang berbeda antar perpindahan zona lainnya. Hasil dari uji kelayakan model menunjukkan keenam fungsi utilitas lolos uji kelayakan. Selanjutnya, hasil uji validasi menunjukan 2 model fungsi utilitas dengan nilai RMSE < 10% dan 4 model fungsi utilitas dengan nilai RMSE > 10%. Hasil uji komparasi didalam proses pemilihan menunjukkan keenam model tetap merupakan model yang berbeda. Hasil pembuatan fungsi utilitas digunakan untuk menganalisis persentase perpindahan menggunakan angkutan umum di tiap pengenaan tarif . Terdapat kecenderungan bahwa semakin mahal tarif ERP maka akan semakin tinggi tingkat perpindahan pengendara mobil ke angkutan umum dan kesediaan pengendara mobil untuk menaiki angkutan umum di daerah pusat kota lebih kecil dibandingkan di daerah pinggir kota. Selain itu, didapatkan kesimpulan bahwa pengendara mobil bersedia membayar ERP dengan tarif termahal yaitu sebesar Rp 10.000 untuk pola perjalanan 1 dengan rata – rata persentase perpindahan menggunakan angkutan umum sebesar 68% , Rp 20.000 untuk pola perjalanan 2 dengan rata – rata persentase perpindahan menggunakan angkutan umum sebesar 60,5%, dan Rp 30.000 untuk pola perjalanan 3 dengan rata – rata persentase perpindahan menggunakan angkutan umum sebesar 15%.

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This study aims to determine the impact of the implementation of the Electronic Road Pricing (ERP) policy that was implemented in Jakarta. The ERP policy is implemented using a regional zoning system. The analytical method in this research is based on the discrete binomial logit selection model. To use the binomial logit model a utility function needs to be built using a logistic regression approach. Regression models of utility functions are built from Stated Preference and Revealed Preference survey results. The process of building a logistic regression model begins with the correlation test using the Spearman test method, then the feasibility test of the model using the Lemmeshow and Omnibus hosmer test methods, the validation test uses the RMSE (Root Mean Square Error) method, the analysis of the model selection with the requirements of passing the feasibility test and validation test and comparative test, sensitivity test, and modal shift potential analysis. Correlation test results showed a significant independent variable in this study, namely ERP rates. From the results of the analysis of the relationship between Willingness To Pay (WTP) and Willingness To Shift (WTS), 6 utility functions are based on zone displacement because there is a preference pattern that tends to be the same between other zone transfers but has different percentages of WTP and WTS among other zone movements . The results of the model feasibility test show that all six utility functions passed the feasibility test. Furthermore, the validation test results showed 2 utility function models with RMSE values ​​<10% and 4 utility function models with RMSE values> 10%. Comparative test results in the selection process show the six models remain different models. The results of the creation of the utility function are used to analyze the percentage of movement using public transportation at each rate. There is a tendency that the more expensive ERP rates, the higher the rate of movement of car to public transport and the willingness of car to ride public transportation in downtown areas is smaller than in suburban areas. In addition, it was concluded that car are willing to pay ERP with the most expensive tariff of Rp 10.000 for travel pattern 1 with an average percentage of transfers using public transportation of 68%, Rp 10.000 for travel pattern 2 with an average percentage of transfers using public transportation by 60.5%, and Rp 30.000 for travel pattern 3 with an average percentage of transfers using public transportation by 15%."

"Summary:Demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. This title provides an approach to identify opportunities, extract requirements, design variables and build and test models"