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Otto Sandjoko
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Transportation

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APPLICATION OF ARTIFICIAL INTELLIGENCE IN TRANSPORTATION DEMAND MANAGEMENT: DEVELOPMENT AND IMPLEMENTATION OF E-SUTRA ., Resdiansyah; ., Ircham; Sandjoko, Otto
Jurnal Transportasi Vol 13, No 3 (2013)
Publisher : Jurnal Transportasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1409.682 KB)

Abstract

Allowing traffic to grow to a level at which there is extensive and regular congestion is economically inefficient. Although the construction of additional roads can alleviate some of the effects of congestion, the benefits may be counterbalanced unless the growth in traffic volumes can be restrained. Therefore, another alternative is by implementing Transportation Demand Management (TDM), which means people still travel but at the same time the private car usage is reduced. This paper presents the development of an expert system for sustainable transportation (E-SUTRA) through implementation of TDM. The overall result of 69% accuracy indicates the high possibility of the E-SUTRA system to be used as an advisory tool for sustainable transportation through TDM.
APPLICATION OF ARTIFICIAL INTELLIGENCE IN TRANSPORTATION DEMAND MANAGEMENT: DEVELOPMENT AND IMPLEMENTATION OF E-SUTRA ., Resdiansyah; ., Ircham; Sandjoko, Otto
Jurnal Transportasi Vol 13, No 3 (2013)
Publisher : Jurnal Transportasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1409.682 KB) | DOI: 10.26593/jt.v13i3.1346.%p

Abstract

Allowing traffic to grow to a level at which there is extensive and regular congestion is economically inefficient. Although the construction of additional roads can alleviate some of the effects of congestion, the benefits may be counterbalanced unless the growth in traffic volumes can be restrained. Therefore, another alternative is by implementing Transportation Demand Management (TDM), which means people still travel but at the same time the private car usage is reduced. This paper presents the development of an expert system for sustainable transportation (E-SUTRA) through implementation of TDM. The overall result of 69% accuracy indicates the high possibility of the E-SUTRA system to be used as an advisory tool for sustainable transportation through TDM.
APPLICATION OF ARTIFICIAL INTELLIGENCE IN TRANSPORTATION DEMAND MANAGEMENT: DEVELOPMENT AND IMPLEMENTATION OF E-SUTRA Resdiansyah .; Ircham .; Otto Sandjoko
Jurnal Transportasi Vol. 13 No. 3 (2013)
Publisher : Forum Studi Transportasi antar Perguruan Tinggi (FSTPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1409.682 KB) | DOI: 10.26593/jtrans.v13i3.1346.%p

Abstract

Allowing traffic to grow to a level at which there is extensive and regular congestion is economically inefficient. Although the construction of additional roads can alleviate some of the effects of congestion, the benefits may be counterbalanced unless the growth in traffic volumes can be restrained. Therefore, another alternative is by implementing Transportation Demand Management (TDM), which means people still travel but at the same time the private car usage is reduced. This paper presents the development of an expert system for sustainable transportation (E-SUTRA) through implementation of TDM. The overall result of 69% accuracy indicates the high possibility of the E-SUTRA system to be used as an advisory tool for sustainable transportation through TDM.
Co-Authors Ircham Resdiansyah .