Model Hubungan Antara Volume Lalulintas Dengan Tarif Jalan Tol

Indonesia has experienced increasing economic growth every year. This recent trend needs to be supported by adequate transportation infrastructures, especially roads. Since there is limited budget for infrastructure development, the government has invited private investors for toll road construction. Toll tariff and traffic volume are two main factors that affect toll road income and investment. A method based on financial approach needs to be developed to enhance the benefit cost analysis of toll road construction and furthermore to determine the toll tariff. Factors that affect toll tariff were analyzed based on vehicle number and vehicle growth rate. The elasticity theory was applied in this case study to identify the effects of toll tariff on traffic volume. A model of critical traffic volume was created based on the analysis of several factors such as construction cost, operation and maintenance cost, payback period, and internal rate of return. The results from Jia method and the Present Worth Factor (PWF) method show that the relationship between traffic volume and toll tariff is very sensitive, indicated by the elasticity value equal to 1. The difference between the two method is about 27% and is caused by the double counting on taxes on Jia method

Location of discriminating peak masses shared between the spectra acquired from <i>Rickettsia</i>-infected specimens and the corresponding <i>Rickettsia</i> strain using Flex analysis software 3.3.

<p>The alignment spectra comparing the infected specimen and the corresponding strain spectra are shown in detail. (A) <i>R. conorii conorii</i> shared discriminating peak masses located on the MS profile of <i>Rh. sanguineus</i> infected by <i>R. conorii conorii</i>. (B) <i>R. slovaca</i> shared discriminating peak masses located on the MS profile of <i>D. marginatus</i> infected by <i>R. slovaca</i>.</p

Peak masses distinguishing uninfected and filariae-infected <i>Aedes aegypti</i> mosquitoes according the compartment, based on the Genetic Algorithm model analysis of ClinProTools.

<p>Peak masses distinguishing uninfected and filariae-infected <i>Aedes aegypti</i> mosquitoes according the compartment, based on the Genetic Algorithm model analysis of ClinProTools.</p

Peak masses distinguishing uninfected and <i>R.slovaca</i>-infected D. marginatus Ticks and the determination of the peak masses shared with a purified R. slovaca strain based on statistical analysis with ClinProTools.

<p>Peak masses distinguishing uninfected and <i>R.slovaca</i>-infected D. marginatus Ticks and the determination of the peak masses shared with a purified R. slovaca strain based on statistical analysis with ClinProTools.</p

Comparison of MALDI-TOF MS profiles of Ticks infected or not by <i>Rickettsia</i> spp.

<p>Representative spectra from biological replicates of <i>Rh. sanguineus</i> (A, B), <i>Rh. sanguineus</i> infected by <i>R. conorii conorii</i> (C, D), <i>D. marginatus</i> (E, F) and <i>D. marginatus</i> infected by <i>R. slovaca</i> (G, H) were aligned using Flex analysis 3.3 software. a.u., arbitrary units; m/z, mass-to-charge ratio.</p

Peak masses distinguishing uninfected and <i>R. c conorii</i>-infected <i>Rh. sanguineus</i> Ticks and the determination of the peak masses shared with a purified <i>R. c. conorii</i> strain based on statistical analysis with ClinProTools.

<p>Peak masses distinguishing uninfected and <i>R. c conorii</i>-infected <i>Rh. sanguineus</i> Ticks and the determination of the peak masses shared with a purified <i>R. c. conorii</i> strain based on statistical analysis with ClinProTools.</p

Result of the blind tests against the MALDI-TOF MS reference database according the compartment and infectious status of mosquitoes.

<p>Result of the blind tests against the MALDI-TOF MS reference database according the compartment and infectious status of mosquitoes.</p

Comparison of MALDI-TOF MS spectra from heads of <i>Aedes aegypti</i> infected or not by filariae.

<p>Spectra of control uninfected <i>Ae</i>. <i>aegypti</i> (A, B); infected with <i>B</i>. <i>malayi</i> (C, D) or <i>B</i>. <i>pahangi</i> (E, F). Some distinct protein masses generated with ClinProTools are represented (I, J and K). a.u., arbitrary units; m/z, mass-to-charge ratio.</p

Classification of samples submitted to MALDI-TOF MS and real-time PCR results.

<p>Classification of samples submitted to MALDI-TOF MS and real-time PCR results.</p

Comparison of MALDI-TOF MS spectra from thorax-head of <i>Aedes aegypti</i> infected or not by filariae.

<p>Spectra of control uninfected <i>Ae</i>. <i>aegypti</i> (A, B); infected with <i>D</i>. <i>immitis</i> (C, D) or <i>B</i>. <i>malayi</i> (E, F) or <i>B</i>. <i>pahangi</i> (G, H). Somme distinct protein masses generated with ClinProTools are represented (I, J, K, and L). a.u., arbitrary units; m/z, mass-to-charge ratio.</p