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.

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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.

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

Aktivitas pemeriksaan persediaan atau Stock-taking merupakan aktivitas pemeriksaan barang manual oleh petugas gudang yang dilakukan secara rutin pada aktivitas pergudangan. Aktivitas ini berfungsi untuk menentukan akurasi persediaan dan mengetahui kondisi persediaan sehingga dapat mengurangi resiko kehilangan, kerusakan, dan keausan persediaan. Aktivitas pemeriksaan persediaan termasuk aktivitas yang memerlukan biaya dan waktu yang besar. Selain itu, aktivitas ini juga tak luput dari kesalahan manusia karena aktivitas pengecekan merupakan aktivitas yang membutuhkan ketelitian tinggi. Penelitian ini bertujuan untuk melakukan identifikasi objek atau produk yang bertujuan untuk menggantikan pemeriksaan manual manusia sehingga proses pemeriksaan jenis dan jumlah barang dapat dilakukan secara otomatis dan presisi. Pengolahan citra digital berbentuk Object Recognition digunakan pada penelitian ini untuk menentukan jenis objek dan jumlah objek. Hasil penelitian menunjukan tingkat deteksi produk tunggal mencapai 90% yang dipengaruhi oleh sudut pengambilan gambar dan tingkat deteksi jumlah objek tunggal mencapai > 81% dengan tingkat pencahayaan yang normal dan sudut pengambilan gambar yang ideal. Diharapkan dengan adanya sistem ini, biaya untuk aktivitas pemeriksaan persediaan dan aktivitas pergudangan secara umum dapat ditekan sehingga efisiensi dan efektivitas dapat dicapai.

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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.

XYZ company produce the various shape of motor spare parts product. The company has three identical parallel spot welding machines that use a random method of production scheduling, based on machine capacity without any sequence of jobs, and only use daily production targets given to operators. Based on the data, the actual scheduling of the machines has a very large completion time difference between each machine, or the machine loading is uneven. As a result, the makespan becomes longer with a value of 440000 seconds (26 days). This research aims to minimize the existing makespan by giving proposed scheduling, using the suggested algorithm method, which has a small number of iterations and has an optimal result. The method begins with the longest processing time sequence rule which is used as the upper bound for the first iteration, then continued to calculate the lower bound and machine workload. The calculation stops at the 15th iteration because the completion time value exceeds the lower and upper bound so that the optimal scheduling taken is scheduled in the 14th iteration with a makespan value of 914412 seconds (16 days). The proposed scheduling can minimize the makespan from the actual schedule by 38%.