Abstract. Two things that are very influential on the growth of Chrysanthemum are moisture and lighting. This research aims to make the system of watering and lighting control, and monitoring of soil moisture on the cultivation of Chrysanthemum in IoT-based Greenhouse. This research combines the concept of the Internet of Things and control system. The temporary results of this research are the application of lamp control and website-based pumps that are compatible on Android at least version 4.2, iOS, and windows also various browsers. The WEMOS D1 mini ESP8266 module is used as a controller and webserver of this Chrysanthemum irrigation and lighting system. The system is tested with wireless connections within a limited range, with an average response time of 0.5 seconds and an average connection speed of 58 Mbps.
The number of verses of the Quran contained in the Qur'an, encouraging people to look for a way to get the exact clause in a short time. The science is an important knowledge, as Muslims we are obliged to study it with the Al-Quran as a guide. So that's how we get the verse about the science of the Quran with a quick, efficient and practical with a mobile application. Decision tree is a predictive model using a tree or hierarchical structure, this method can support mobile applications to be created. Because based decision very complex and global in the Quran, can be transformed into more simple and specific. C4.5 algorithm is a decision tree induction algorithm and is suitable to perform the classification process. The results of the percentage of successful applications created by using a decision tree that is 75.73%. From these results is known that the algorithm C4.5 and decision tree reasonably is well used in the classification process.
Diplomatic relations between countries increasingly show how important the meaning of relations between these countries. Representatives are needed in order to establish cooperative relationships in several fields such as culture, politics, and education. The Ministry of Foreign Affairs is expected to recommend objective representatives to be placed as foreign diplomats. Finding suitable representatives and the number of representatives to be dispatched in accordance with the criteria and rules that apply in the foreign ministry becomes complicated. With this objective and value-weighted recommendation made, it is easier for superiors in the ministry to make representative selection. The method used is the Multi Attribute Utility Method (MAUT) which can make effective and specific selections. Based on the results of testing of 50 sample data to calculate the selection of foreign diplomats using the MAUT method the results were 94%.
The ability of students to determine their chosen field of expertise is still subjective, many students choose the field of expertise because their classmates choose the field of expertise not by considering their abilities and interests. This research uses the KNN classification method to determine areas of expertise that are in accordance with student expertise. The KNN method was chosen because it is a method that uses supervised algorithms where the results of new query instances are classified based on the majority of the categories in the KNN whose purpose is to classify test data based on training data. This system was tested using the confusion matrix method and the results were 98.30% of the total student data sample of 30 people.
Brown sugar is the result of processing the coconut juice with a distinctive taste, so that its use cannot be replaced by other types of sugar. The purpose of this research is to design of Decision Support System (DSS) using a Multi Attribute Decision Making (MADM) model by applying Weighted Product (WP) method to determine the quality of brown sugar. WP method was chosen because the problem in this research is a ranking problem. The WP method is able to select the best alternative from a number of alternatives and its superiority in weighting technique. This system is designed by using PHP and MySQL as the database programming language. This system can rank the brown sugar by calculating the criteria weight. The weight value is searched for each attribute, then conduct the ranking process to determine the optimal alternative, which is the best brown sugar and decent in terms of ranking. Based on the tests performed, a system capable to produce the best ranking in accordance with the calculations used, so that the system this can be speed up the selection of brown sugar.
Characteristic extraction in face recognition is a step to get characteristic information from the image. The characteristic extraction algorithm is tested against several scenarios of different sunlight and lights, objects facing the camera and not facing the camera. The sample test data were performed on 4 people using a video file or frame numbering 70 for recognizable faces using Principal Component Analysis (PCA) and Local Binary Pattern (LBP) algorithms. The result of the research shows that Local Binary Pattern (LBP) algorithm in object scenario facing camera with sunlighting in room has accuracy of 98.59%, recognition time of 812,817 milliseconds, FAR of 1,41% and FRR of 0%, while at Principal Component Analysis (PCA) 98.59% accuracy, recognition time of 1275,761 milliseconds, FAR of 1.41% and FRR of 0%. Based on these results, the Local Binary Pattern (LBP) algorithm is more efficient than Principal Component Analysis (PCA) for face recognition of the scenarios to be implemented in real-time video.
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