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Jambi Province is one of the largest natural rubber producing regions in Indonesia; however, rubber factories under GAPKINDO Jambi still face productivity issues, particularly the gap between production capacity and actual output, and productivity assessment that is still conducted manually by GAPKINDO Jambi. This study employs Decision Tree, Random Forest, KNN, and SVM algorithms within a structured pipeline involving preprocessing, feature selection, standardization, data balancing using SMOTE, and hyperparameter tuning. The proposed solution applies productivity level classification both individually and through paired combinations (ensemble voting). The results show that the Decision Tree + Random Forest model achieves the best performance with an accuracy of 0.84 and an F1-score of 0.83, confirming the effectiveness of ensemble methods in supporting productivity improvement decisions.

Porous asphalt is an open graded hot mix asphalt with a small percentage of fine aggregate and a large percentage of coarse aggregate. Porous asphalt is an asphalt mixture that is being developed for wearing course construction. The aim of this research is to analyze the effect of adding rubber tire powder on the performance of the Asphalt Porous-Wearing Course. In this research two standard gradations for porous asphalt were used, namely Australian gradation (AAPA) and California gradation (CalTrans) with the addition 0%, 2%, 4%, and 6% of rubber tire powder. Based on the research carried out, it can be seen that the addition of rubber tire powder to a mixture with AAPA gradation is better in terms of its ability to accept loads without experiencing deformation (stability) and the possibility of the mixture being able to withstand maximum loads to prevent traction failure (ITS). Meanwhile, mixtures with Caltrans gradations are better in terms of resistance to wear (CL), homogeneous mixing of asphalt and aggregate (AFD), and ability to resist cracking (TSR). The addition of rubber tire powder was not able to improve the strength due to immersion at extreme temperatures (IRS) in a mixture of both gradation specifications.  

Utilization of new technologies in asphalt mixture production includes soaking technologies that can enhance mechanical properties of the mixture. This research aims to evaluate pavement vulnerability to water and the environmental quality impact due to waste from used rubber tires as an effort to strengthen pavements by substituting asphalt. The variables studied are variations of used rubber tire waste at 0%, 2%, 3%, and 4% replacing asphalt content in AC-BC mixtures. Testing was conducted using the Marshall method by soaking the mixtures in water for normal duration, 30 minutes, 24 hours, and 72 hours. The test results indicate that higher percentages of used rubber tire waste and longer soaking durations lead to a decrease in AC-BC mixture characteristics. The Marshall value of the AC-BC mixture with 2% used rubber tire waste was found to be superior compared to mixtures with 0%, 3%, and 4%. From the data analysis conducted, it can be concluded that water has a negative influence on the Marshall value reduction of mixtures containing used rubber tire waste, correlating with increased soaking duration.