Machine learning enables machines to learn information and make inferences using the it has learned. In this article, five years of crime data were analyzed process was completed with in machine's hands. One-Hot Encoding Min-Max Normalization methods Principal Component Analysis algorithm used analysis data. The model asked predict whether criminal could be caught, security area, type committed...

In healthcare machine learning is used mainly for disease diagnosis or acute condition detection based on patient data analysis. the proposed work diabetic dataset analysis done hypoglycemia which means lowering of blood glucose level. Often in it observed that imbalanced. Therefore an Ensemble Approach using imbalanced techniques Synthetic Minority Over-sampling Technique and Adaptive oversamp...

At present, the method for fault diagnosis and maintenance of CTCS-3 (Chinese Train Control System Level 3) electronic equipment relies too heavily on expert knowledge. Moreover, use historical data is not valued. This paper proposes a sustainable model based imbalanced text mining. First, to process from field recorded in natural language, language processing technology used extract feature wo...

Chemical oxygen demand (COD) is one of the indicators used to monitor level pollution in surface water. To recycle agricultural water resources, it crucial monitor, a timely manner, whether COD exceeds control standard. A diagnostic model was developed using visible near-infrared spectroscopy (Vis-NIR) combined with partial least squares discriminant analysis (PLS–DA). total 127 samples were co...

Patchouli plants are main raw materials for essential oils in Indonesia. leaves have a very varied physical form based on the area planted, making it difficult to recognize variety. This condition makes farmers these varieties and they need experts’ advice. As there few experts this field, technology identifying types of patchouli is required. In study, identification model constructed using co...

Predicting student dropout is a challenging problem in the education sector. This due to an imbalance data, mainly because number of registered students always higher than students. Developing model without taking data issue into account may lead ungeneralized model. In this study, different balancing techniques were applied improve prediction accuracy minority class while maintaining satisfact...

In recent years, radio frequency identification (RFID) technology has been utilized to monitor product movements within a supply chain in real time. By utilizing RFID technology, the products can be tracked automatically real-time. However, cannot detect movement and direction of tag. This study investigates performance machine learning (ML) algorithms passive tags. The dataset this was created...

We investigate the use of biased sampling according to the density of the data set to speed up the operation of general data mining tasks, such as clustering and outlier detection in large multidimensional data sets. In density-biased sampling, the probability that a given point will be included in the sample depends on the local density of the data set. We propose a general technique for densi...

We investigate the use of biased sampling according to the density of the dataset, to speed up the operation of general data mining tasks, such as clustering and outlier detection in large multidimensional datasets. In densitybiased sampling, the probability that a given point will be included in the sample depends on the local density of the dataset. We propose a general technique for density-...