The COVID-19 virus has infected many people, resulting in death tolls around the world. So, it is necessary to adopt a clean and healthy lifestyle and implement health protocols such as using masks, washing hands and maintaining distance. This community service activity aims to provide education and assistance to community representatives in Desa Bojongsoang, Bandung, to always implement a healthy and clean lifestyle and health protocols. Educational activities are carried out by providing counseling with the methods of lectures, discussions, and questions and answers. Material delivery is also conveyed through the media of posters, so that the posters can be affi xed to strategic areas so that it can be seen and read eff ectively. In this activity, an evaluation of the level of community compliance in implementing health protocols while outside the home was also carried out, by distributing questionnaires before the activity took place. As a result, in general the community is disciplined in applying health protocols while outside the home. Several fi ndings were also obtained in this simple survey, so that these fi ndings can be used as initial data/information for local stakeholders to streamline education and socialization in eff orts to prevent the massif transmission of the COVID-19 virus.

The Indonesian roof tile manufacturing industry relies heavily on manual operations, specifically in transportation and inspection processes, which creates multiple issues, such as fatigue, injuries, human error, and reduced productivity. Various industries in the Indonesian industrial landscape have begun embracing a problem-solving approach known as the theory of inventive problem-solving (TRIZ) to mine solutions for industrial issues. Nevertheless, its application in the Indonesian roof tile manufacturing industry remains unaddressed. The study aims to solve manual handling issues in the roof tile manufacturing industry using TRIZ. Three observations were outlined from manual roof tile transportation and inspection, followed by the formulation of engineering contradictions (ECs). The ECs were linked with system parameters, which were used as indicators within the contradiction matrix to extract inventive principles as solution models for conceptual development. The concept included an automated system with a conveyor belt (#15: dynamics) for effective transportation, automated image capture (#28: mechanics substitution) for effective inspection, and a flipping conveyor (#25: self-service) to eliminate manual contact. Although the study addressed several issues stemming from manual operations, mechanical analysis, prototyping, and usability testing still require improvements.

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Clothing, food, and shelter are three basic types of needs in our lives. If one of the basic needs is not met then there can be an imbalance in our lives. One of the basic needs is to build a house. House needs a tile or roof to cover of a building that can protect all weather influences. One company in Majalengka only uses fleeting vision in inspection process. This can result in a decrease in work productivity. This paper proposed an approach machine learning model for classification of defects was carried out in the inspection process. Feature extraction was performed using the Local Binary Pattern (LBP) method to obtain training features. The next stage is training (training) to the characteristics of training that has been obtained. Furthermore, the database obtained from the training results will be used to classify tile image test data using the Support Vector Machine (SVM) method. From the test results, the system is made capable of classifying defects of a maximum accuracy value of 63.21%. The results obtained are the best accuracy value generated is 76.67% with LBP parameters used are 256 × 256 cell size and radius 2. While for SVM parameters use Polynomial kernel type or RBF with OAA multiclass

The strength of the company's competitiveness is needed because the current industrial development is very rapid. It is necessary to maintain the quality and quantity of the products produced according to company standards.  One of the companies that must maintain the quality and quantity is PT. XYZ is a clay tile company. The classification of products used by this company to maintain good quality is three classes: good tile, white stone tile, and cracked tile. However, quality control based on classification still uses the traditional way by relying on sight.  It can increase errors and slow down the process. It can be overcome with artificial visual detectors. It is a result of the rapid development of automation. So to detect defects, this research can use image preprocessing, supervised learning algorithms, and measurement methods.  Support Vector Machine (SVM) is used in this study to perform classification, while feature extraction on clay tiles used the Local Binary Pattern (LBP) method. The algorithm is made using python, while for image retrieval, raspberry pi is used. The linear kernel on the SVM algorithm is used in this study. The conclusion in this study obtained 86.95% is the highest accuracy with a linear kernel. It takes 10.625 seconds to classify.