Pengukuran Metode Beban Kerja Mental Modified Cooper Harper (MCH) dan Manfaatnya

Mental workload is a branch of ergonomics that focuses on the psychological load that a person experiences at work. This is important to research because humans will definitely experience psychological fatigue in addition to physical fatigue. One method that can be used in examining a person's mental workload is the modified cooper harper method. The purpose of using this method is to determine the mental workload conditions of workers, especially when using tools or facilities that support their work. And the subject chosen in applying this method is a nurse. It is hoped that after knowing the workload of nurses, researchers can provide recommendations for the future

EVALUASI STASIUN KERJA CETAK DI HOME INDUSTRY MENGGUNAKAN METODE REBA DAN LINGKUNGAN KERJA FISIK

XYZ cake mould home industry is a restaurant industry located in the city of Mojokerto, East Java. It is known that there are several abnormal worker positions in the Home Industry, namely at the printing workstation. Where Musculoskeletal Disorders (MSDs) occur, complaints or pain in certain parts of the body. These factors are affected by seating, hot workplaces, noise, and poor lighting. As a result, work productivity is erratic and tends to decrease. In this study, the Rapid Entire Body Assessment (REBA) method was used as the final step to determine the score for each operator activity and determine the severity experienced by the operator. And the highest score was obtained, namely 9 (nine) or the high-level category in the activity of making sand moulds and pouring molten aluminium. The environment also affects productivity, so the researchers used the Indoor Health and Comfort (IHC) method to determine the environmental conditions at the printing station. And get data starting from lighting 60 Lux, temperature 44o C, and noise 87.8 dB. From the physical environmental factors at the printing place, it is known that the value is not average.   Keywords: Musculoskeletal Disorders (MSDs), Rapid Entire Body Assessment (REBA), Indoor Health and Comfort (IHC)Home Industry cetakan kue XYZ merupakan industri rumah makan yang terletak di kota Mojokerto Jawa Timur. Diketahui beberapa posisi pekerja yang tidak normal di Home Industry yaitu pada stasiun kerja cetak. Dimana terjadi Musculoskeletal Disorders (MSDs) keluhan atau rasa sakit dibagian tertentu pada tubuh. Faktor tersebut dipengaruhi dari tempat duduk, tempat kerja yang panas, kebisingan, dan pencahayaan yang kurang. Akibatnya produktivitas kerja tidak menentu dan cenderung menurun. Dalam penelitian ini digunakan metode Rapid Entire Body Assessment (REBA) sebagai tahap akhir untuk menentukan skoring pada setiap aktivitas operator dan mengetahui tingkat keparahan yang dialami operator. Dan didapatkan skor tertinggi yaitu 9 (sembilan) atau kategori level tinggi  pada aktivitas membuat cetakan pasir dan menuangkan aluminuim cair. Lingkungan juga mempengaruhi produktivitas oleh sebab itu peneliti juga menggunakan metode Indoor Health and Comfort (IHC) untuk mengetahui kondisi lingkungan pada stasiun cetak. Dan mendapatkan data mulai dari Pencahayaan 60 Lux,  Suhu 44o C, dan kebisingan 87,8 dB. Dari faktor lingkungan fisik pada stasiun cetak diketahui memiliki nilai yang tidak normal. Kata Kunci: Musculoskeletal Disorders (MSDs), Rapid Entire Body Assessment (REBA), Indoor Health and Comfort (IHC

PENINGKATAN SIFAT MEKANIK AL6061 MELALUI HEAT TREATMENT NATURAL-ARTIFICIAL AGING

Aluminium memiliki sifat yang ringan, ulet serta memiliki ketahanan korosi yang baik. Akan tetapi, aluminium juga memiliki kelemahan, dimana kekuatan mekaniknya relatif lebih rendah apabila dibandingkan dengan logam komersil lainnya. Aluminium 6061 adalah salah satu seri aluminium yang sangat banyak ditemukan dan diaplikasikan dalam berbagai bidang industri. Ditinjau dari jumlah penggunaan aluminium yang semakin bertambah setiap tahunnya, maka perlu dilakukan perbaikan sifat mekanik aluminium 6061. Sifat mekanik aluminium 6061 dapat ditingkatkan melalui proses aging. Penelitian ini bertujuan untuk meningkatkan sifat mekanik 6061 serta mendapatkan sifat mekanik antara aluminium 6061 yang dikeraskan dengan menggunakan metode natural aging yang dilanjutkan dengan artificial aging. Penelitian ini menggunakan metode eksperimen laboratorium. Proses natural aging dan artificial aging dilakukan dengan proses solution heat treatment pada suhu 520℃ ditahan selama 30 menit, dan quenching dilakukan dengan media campuran air dan dromus oil. Selanjutnya proses natural aging dilakukan dengan penahanan di temperatur kamar selama 7 hari, dilanjutkan proses artificial aging, pemanasan dilakukan pada temperatur 200℃ dengan variasi holding time selama 2, 4, dan 6. Hasil perlakuan panas pada aluminium 6061 akan diuji kekerasan dan struktur mikronya dimana hasil terbaik ditunjukkan pada spesimen dengan waktu penahanan artificial aging selama 4 jam

Pembinaan Manajemen Keuangan Berbasis Mobile Application Akuntansi pada Industri Rumah Tangga Kacang Telur “Al-Halwa”

The community service activities carried out by the implementing team are related to financial management based on mobile accounting applications in the AL-Halwa peanut egg home industry. The mobile application used in this community service is the “Financial Daily Notes” application. The purpose of introducing this financial application is to create awareness for home industry players or SMEs in the use of business financial management technology. So that home industry players or SMEs can manage their finances easily. This application has standard features to assist partners when recording the financial results of operations. The features in this application include recording income, recording expenses, periodic reports, features that display financial differences, displaying historical data that users input into the application, security features such as pins and passwords, to features that can export reports in word form, excel and pdf

Analisis Keluhan Karyawan dan Evaluasi Postur Tubuh dengan Metode Reba di CV.Allwooden Woodworking

CV. Allwooden Woodworking is a furniture company that has been established since November 2017, with a product ordering system, namely Make To Order (MTO). In carrying out work, many employees still complain about discomfort at work such as complaints of pain in certain body parts, this is evidenced by the Nordic Body Map (NBM) questionnaire. To solve these problems the researcher used the Rapid Entire Body Assessment (REBA) method. From the processing, it is known that the REBA score of CV employees. There are 5 Allwooden Woodworking workstations for measuring, 5 assembly workstations, 5 sanding workstations, 6 finishing workstations, and 3 cutting workstations. Recommendations for improvement offered by researchers are work desks and rest time schedule

Analisis Bullwhip Efect pada Kegiatan Supply Chain Perishable Product

UD. Sayur Mayur merupakan perusahaan distributor sayur-mayur, buah-buahan dan bahan baku makanan lainnya yang melakukan pemesanan produk kepada pemasok lalu didistribusikan ke setiap retail, dimana tujuan distribusi yang memasok bahan baku makanan dari UD. Sayur Mayur berada di wilayah Malang Raya, Yogyakarta dan Jawa Tengah. Dalam memenuhi permintaan retailer, perusahaan melebihkan jumlah pesanan kepada pemasok sebesar 9% hingga 40% terganting jenis produk untuk mengantisipasi adanya cacat/rusak karena produk bersifat perishable atau tidak tahan lama. Pertimbangan melebihkan pesanan tersebut ternyata berdampak pada timbulnya bullwhip effect atau peningkatan variabilitas permintaan. Maka dari itu, tujuan dari penelitian ini adalah untuk mengetahui nilai bullwhip effect di tingkat distributor, tingkat retailer dan tingkat retailer kategori produk, sehingga nilai bullwhip effect merupakan dasar penentuan rekomendasi perbaikan untuk mengatasi permasalahan bullwhip effect pada perusahaan. Berdasarkan hasil perhitungan, dapat diketahui bahwa terjadi bullwhip effect sebesar 81.3% di tingkat distributor, 80% di tingkat retailer, dan 66.7% di tingkat retailer kategori produk. Produk maupun kategori yang mengalami bullwhip effect dimana nilai BE lebih besar dari parameternya dipengaruhi oleh adanya selisih yang cukup signifikan antara demand dan order, sedangkan produk maupun kategori yang berada di posisi stabil dipengaruhi oleh selisih antara demand dan order yang tidak signifikan sehingga nilai BE tidak melebihi parameternya

Deep Learning to Detect and Classify the Purity Level of Luwak Coffee Green Beans

Luwak coffee (palm civet coffee) is known as one of the most expensive coffee in the world. In order to lower production costs, Indonesian producers and retailers often mix high-priced Luwak coffee with regular coffee green beans. However, the absence of tools and methods to classify Luwak coffee counterfeiting makes the sensing method’s development urgent. The research aimed to detect and classify Luwak coffee green beans purity into the following purity categories, very low (0-25%), low (25-50%), medium (50-75%), and high (75-100%). The classifying method relied on a low-cost commercial visible light camera and the deep learning model method. Then, the research also compared the performance of four pre-trained convolutional neural network (CNN) models consisting of SqueezeNet, GoogLeNet, ResNet-50, and AlexNet. At the same time, the sensitivity analysis was performed by setting the CNN parameters such as optimization technique (SGDm, Adam, RMSProp) and the initial learning rate (0.00005 and 0.0001). The training and validation result obtained the GoogLeNet as the best CNN model with optimizer type Adam and learning rate 0.0001, which resulted in 89.65% accuracy. Furthermore, the testing process using confusion matrix from different sample data obtained the best CNN model using ResNet-50 with optimizer type RMSProp and learning rate 0.0001, providing an accuracy average of up to 85.00%. Later, the CNN model can be used to establish a real-time, non-destructive, rapid, and precise purity detection system

Classification of soybean tempe quality using deep learning

Tempe is a traditional food originating from Indonesia, which is made from the fermentation process of soybean using Rhizopus mold. The purpose of this study was to classify three quality levels of soybean tempe i.e., fresh, consumable, and non-consumable using a convolutional neural network (CNN) based deep learning. Four types of pre-trained networks CNN were used in this study i.e. SqueezeNet, GoogLeNet, ResNet50, and AlexNet. The sensitivity analysis showed the highest quality classification accuracy of soybean tempe was 100% can be achieved when using AlexNet with SGDm optimizer and learning rate of 0.0001; GoogLeNet with Adam optimizer and learning rate 0.0001, GoogLeNet with RMSProp optimizer, and learning rate 0.0001, ResNet50 with Adam optimizer and learning rate 0.00005, ResNet50 with Adam optimizer and learning rate 0.0001, and SqueezeNet with RSMProp optimizer and learning rate 0.0001. In further testing using testing-set data, the classification accuracy based on the confusion matrix reached 98.33%. The combination of the CNN model and the low-cost digital commercial camera can later be used to detect the quality of soybean tempe with the advantages of being non-destructive, rapid, accurate, low-cost, and real time