Febri Hadi’s research while affiliated with Universitas Putra Indonesia "YPTK" and other places

The development of technology today has a great influence in various fields. One of the fields that requires information technology data processing is the business field. Information technology data processing is very necessary to analyze data in the business world. Data analysis is needed to understand customers and group customers. One of the data analysis methods used for customer grouping is the K-Means algorithm. This method also helps companies analyze customer loyalty in sales transactions. The purpose of the study is to group customers as an analysis of a business. Data grouping in this study is grouped into 2, namely loyal and less loyal customers. The data in this study is 20 data samples taken from sales transaction data. The results of this study produce information about loyal customers and less loyal customers so that from this information the company can make decisions to improve relationships with customers in making sales transactions

span>Malnutrition is a problem that is often faced by every country around the world. Various facts show that malnutrition is of particular concern to many researchers. To can overcome this problem, every effort has been made such as developing analytical models in identification, classification, and prediction. This study aims to determine the nutritional status of children using the machine learning (ML) classification analysis approach. The methods used in the ML analysis process consist of cluster K-Means, artificial neural network (ANN), sum square error (SSE), pearson correlation (PC), and decision tree (DT). The dataset for this study uses data on child nutrition cases that occurred in the previous and was sourced from the provincial general hospital (RSUP) M. Djamil, Padang, West Sumatera. Based on the research presented, ML performance in the nutritional status classification analysis gave maximum results. These results are reported based on the level of precision with an accuracy of 99.23%. The results of the analysis can also present a knowledge-based nutritional status classification. This research can contribute to and update the analytical model in determining nutritional status. The results of this study can also provide benefits in handling nutritional status problems that occur in children.</span

Malnutrition is one of the problems that occurs in children due to a lack of nutritional intake. Indonesia contributed 36%, making it the fifth country with the largest cases of malnutrition in the world. On this basis, a solution is needed to reduce the growth rate of malnutrition cases. This research aims to carry out classification analysis to determine nutritional status by optimizing machine learning (ML) performance. The ML classification analysis process will later utilize the performance of the artificial neural network (ANN) method with the Multilayer Perceptron (MLP) algorithm. ML performance can be optimized using the Pearson’s correlation (PC) method to produce optimal classification analysis patterns. This research data set uses child nutrition case data from 576 patients sourced from the M. Djamil Padang Province Regional General Hospital (RSUP). The data set is divided into 417 training data and 159 test data. On the basis of the tests that have been carried out, the performance of the PC method can provide precise and accurate analysis patterns. This analysis pattern has also been able to provide a fairly good level of accuracy, namely 95%. Not only that, this research is also able to present analysis patterns with the best ANN architectural model in classifying nutritional status. Based on the overall results, this research can be used as an alternative solution to the treatment of nutritional problems in children.

Imagery on edge detection is a process that will display the edges of an image. Basically, edge detection is one of the techniques for the analysis of image quality in the spatial domain and is also one of the initial process in digital image processing. Edge detection serves to detect the border line of an object contained in the image. This study aims to identify and recognize face pattern objects in the capture zoom image. To perform face identification begins with collecting image data, image processing, image edge detection, thinning of the image, and identification process using the template matching method. The method used in edge detection uses 3 methods, namely Sobel, Roberts and Prewitt which are gradient operators to detect edges in facial images. The dataset used is image capture zoom. The trial was carried out in two stages, namely the identification of the face shape and the identification of the edges of the face. The conclusion of the study is that the Roberts operator is the operator that finds the least edge patterns in facial images than the other two operators, namely Prewitt and Sobel. Meanwhile, the Sobel operator produces edge patterns that are better in quality and quantity than using the Roberts and Prewitt operators.

Infectious diseases are common diseases and are caused by microorganisms such as viruses, bacteria, and parasites. Indicators of the spread of this disease can be seen based on the population level and the number of confirmed cases. This study aims to develop a machine learning (ML) analysis model using the K-means cluster, artificial neural network (ANN), and decision tree (DT) methods. The dataset used in this study was obtained based on the number of confirmed patients and the distribution of the population. The analysis process is divided into two stages, namely preprocessing and the classification process. The pre-processing stage aims to produce a classification pattern that can describe the level of distribution status. The classification pattern will be continued at the classification analysis stage using ANN and DT. Classification analysis gave significant results with an accuracy rate of 99.77%. The results of the classification analysis can also describe the level of knowledge distribution based on the decision tree. Overall, the contribution of this research is to develop a classification analysis model that presents the latest information and knowledge. The results of the research presented also have an impact on the control process in environmental management and public health.

The city of Padang has many tourist attractions so that the city of Padang is one of the tourist destinations. Tourists who come not only from within the country but also from abroad. For that we need a technology that can promote tourist objects to visiting tourists. The technology that is currently becoming popular is augmented reality. Augmented reality can provide more innovative information so that tourists are interested in visiting the objects they are visiting. This augmented reality technology will be applied to Android-based smartphones and use 3D objects. This augmented reality application uses the point of interest method, where tourists use a smartphone camera to recognize a map image of the city of Padang and send the results of capturing these images to be processed and display visually according to predetermined points.

This study aims to determine the marketing channels of mushrooms, to know the internal and external factors of the mushroom marketing business, to know the marketing strategies of mushrooms. From the results of the SWOT analysis, it is known that the internal factors (strengths and weaknesses) and external factors (opportunities and threats) of the mushroom business in sweet limes. Its strengths are: Good mushroom quality, Affordable amount of capital, Competitive pricing, Retaining customers. Weaknesses are: There is still a lack of promotional activities, Lack of a marketing system, The production process still uses simple technology. The opportunities are: The market share of oyster mushrooms is still wide, Mushrooms can be processed into derivative products, Government intervention. The threats are: There is competition between mushroom cultivators, the effect of changing seasons/weather, the marketing strategy that can be done by mushroom farmers is aggressive growth (growth oriented strategy), namely by expanding the share, and through increasing added value by processing products from these mushrooms.

Strategi pembelajaran adalah cara-cara yang akan dipilih dan digunakan oleh seorang pengajar untuk menyampaikan materi pembelajaran. Tujuan strategi pembelajaran adalah untuk memudahkan anak menerima dan memahami materi pembelajaran, yang pada akhirnya anak-anak dapat menguasai materi pembelajaran. Tujuan kegiatan Pengabdian kepada Masyarakat (PkM) ini adalah untuk menelaah penggunaan teknologi informasi dan komputer (TIK) pada anak-anak pada masa Covid-19. Kegiatan ini melibatkan anak-anak panti asuh rumah yatim Nagari Maimbau Pauh V Padang. Kegiatan pengabdian masyarakat ini memberikan edukasi kepada anak-anak yang ada di panti dalam penggunaan teknologi informasi dan komputer yang tepat dan bermanfaat bagi penunjang pembelajaran. Hasil dari kegiatan pengabdian masyarakat diperoleh hampir 85% anak-anak sudah dapat menggunakan teknologi informasi secara tepat dan bijaksana.

Garbage is leftover material that is no longer used from daily human activities. The Garbage Bank system is currently still manual in nature such as buying and selling waste from the Bengkalis community, waste price lists, types of waste and grouping waste categories. As a solution to these problems, the author builds a Software Design to digitize the previous system which was done manually. In this study the research methodology used is the Kanban method. In making this application the programming language used is PHP Framework Codeigniter, and MYSQL as a data storage area. With this application, it can help the Waste Bank to buy waste easily, safely and more efficiently.