K-nearest neighborhood Research Papers - Academia.edu (original) (raw)

Logical analysis shows the attributes of an individual decision making, problem solving and verbal ability. Furthermore, it provides significant information to schools and companies to strategically develop relevant interventions towards the improvement of individual logical capability skills. This is the reason why logical test is given, basically to measure the thinking level of an individual. However, experts in this field make tedious process in generating the result thus consuming time and effort. With this current situation, the study aims to develop an online logical test to automatically generate score and skills analysis results in real-time. The study used descriptive method to understand the process and interpretation of skills to ensure its accuracy and the Rapid Application Development model was adopted to accomplish the technical requirement of the application. And this application was evaluated by the experts in terms of functionality, reliability, usability, and efficiency with the overall weighted mean result of 4.29 " Very Satisfactorily ". I. INTRODUCTION Logical thinking is a process of problem solving, decision making, verbal reasoning, metacognitive process, and adaptation ability and purely needed in science and mathematics. [42][22] [10] [30] [46]. In the information technology it is one of the foundational skill of an ITE students [34].

The suspended sediment load (SSL) is one of the major hydrological processes affecting the sustainability of river planning and management. Moreover, sediments have a significant impact on dam operation and reservoir capacity. To this end, reliable and applicable models are required to compute and classify the SSL in rivers. The application of machine learning models has become common to solve complex problems such as SSL modeling. The present research investigated the ability of several models to classify the SSL data. This investigation aims to explore a new version of machine learning classifiers for SSL classification at Johor River, Malaysia. Extreme gradient boosting, random forest, support vector machine, multi-layer perceptron and k-nearest neighbors classifiers have been used to classify the SSL data. The sediment values are divided into multiple discrete ranges, where each range can be considered as one category or class. This study illustrates two different scenarios related to the number of categories, which are five and 10 categories, with two time scales, daily and weekly. The performance of the proposed models was evaluated by several statistical indicators. Overall, the proposed models achieved excellent classification of the SSL data under various scenarios.

- by K.W. Chau
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- Malaysia, Support Vector Machines, Random Forest, K-nearest neighborhood

Posyandu is an activity to record the health condition of children under five that is done regularly and continuously every month. Recording health of children under five is done to monitor the growth of children under five (growth monitoring), both weight and height growth of children under five. Weighing weight and height measurement of babies at posyandu is the effort of society in monitoring growth of baby and toddler growth. Although the weight and height of the toddler have been recorded in the KMS, parents still need to do the calculations to find out if their toddlers have normal weight or not, besides the parents also want to know if their toddler weight will increase in the coming months based on the baby's weight in previous months. We propose a nearest neighbour using Euclidean distance to determine if the weight of a toddler is normal, less normal or abnormal based on the WHO table. Furthermore, to predict the weight of infants in the coming months we propose k-nearest neighbour based on the previous baby's weight. The experimental results show that k-nearest neighbour can classify normal, abnormal, and abnormal growths of the baby and k-nearest neighbour can predict the baby's weight in the following month. Keywords— Classification of baby growth; baby weight prediction; K-Nearest Neighbor; I. INTRODUCTION Posyandu is an activity to record the health condition of children under five that is done regularly and continuously every month. Recording health of children under five is done to monitor the growth of toddlers, both weight and height growth of children under five. Weighing weight and height measurement of babies at posyandu is the effort of society in monitoring growth of baby and toddler growth. Monitoring the growth of toddlers is very important to be done to determine early growth failure (growth faltering). Currently, health education is conducted by health workers by providing counselling directly. Results of counselling, weight and height of children under five are recorded in KMS every month. Recording in the KMS is done to monitor the growth of infants and toddlers. Although the weight and height of the toddler have been recorded in the KMS, the mothers still need to do the calculations to find out their toddler has an ideal weight or not. This shows that in fact people still lay for information covering about the growth of children's health and toddlers.(Munawaroh,2014).