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"Biaya transportasi adalah salah satu komponen untuk mendapatkan keuntungan maksimal, tetapi sekarang tingkat emisi yang dihasilkan dari kegiatan transportasi juga menjadi perhatian di dunia industri. Model optimal komponen biaya dan emisi diperlukan untuk mendapatkan skenario terbaik yang memiliki biaya dan emisi rendah untuk mendukung komitmen industri ramah lingkungan. Untuk mencapai model yang dapat menyerupai kondisi asli di tempat tertentu kita akan menggunakan metode classifier Naïve Bayes. Model ini akan mengklasifikasikan tingkat keramahan lingkungan dan efisiensi biaya berdasarkan pengukuran berat dan volume menggunakan database yang diperoleh dari area tertentu, pada riset ini periset menggunakan beberapa skenario transportasi dari zona industri yang memiliki aktivitas melalui pelabuhan Tanjung Priok. Sebagai hasil dari pengklasifikasi alat yang dapat mengklasifikasikan tingkat hijau, tingkat biaya dan karakteristik barang yang sesuai (apakah itu cenderung memenuhi berat atau volume) berdasarkan metode pengklasifikasi Naïve Bayes.

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Transportation costs are one of the components to get the maximum profit, but now the level of emissions resulting from transportation activities also becomes a concern in the industry. Optimum models of cost and emissions components required to get the best scenario that has low costs and emissions to support green industrial commitment. To achieve a model that can resemble the original conditions on the specific place we will use the Naïve Bayes classifier method. This model will classify the environmental friendliness and cost efficiency incurred with weight and volume measurement based on existing databases acquired from specific areas, at this study researcher using multiple transportation scenarios from industrial zones that had activity through the Tanjung Priok port. As a result of a classifier of tools that can classify green levels, cost levels and suitable characteristics of goods (whether it tends to meet weight or volume) based on Naïve Bayes classifier methods."

"stakeholders in Bali have highlighted the need to investigate and better understand road user behavior as a means of reducing the high proportion of crashes in goods and freight distribution sector. This study aimed to analyze the relationship between self-reported driver behaviors and traffic crashes reported by drivers transporting goods and freight in Denpasar, Bali. A driving safety survey was distributed to 350 goods and freight transport drivers to obtaine a range of demographic information, self-reported crash and offence data, along with psychosocial factors data associated with driving safety. Factor analysis identified a four factor solution with distinctions between di?erent driving practices within the sample consisting of aggresive driving behaviors, driving errors, traffic code violations and normlessness. The results of this study demonstrated that normlessness consisting of behaviors such as taking a slight risk when overtaking and ignoring speed limits were the most common form of unsafe behaviors reported by the goods vehicle transport drivers. The study indicated that speeding behaviors influenced more self-reported driving errors, aggresive behaviors and traffic rule violations and traffic crashes. In addition, drink driving was found to be positively related to traffic crashes. The implications of these results are discussed."