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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal of Industrial Engineering Management
Ratih Rahmawati
Universitas Tanjungpura
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Energy Engineering Industrial & Manufacturing Engineering

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ENGINEERING DESIGN OF AUTOMATIC SELENOID STOVE TO REDUCE MUSCULOSKELETAL DISORDERS COMPLAINTS USING NBM AND RULA APPROACH Tri Wahyudi; Ratih Rahmawati; Silvia Uslianti
Journal of Industrial Engineering Management Special edition of Seminar Nasional Teknik dan Manajemen Industri 2020
Publisher : Center for Study and Journal Management FTI UMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33536/jiem.v0i0.772

Abstract

UKM Kenanga is a home industry producing various cassava chips based in Kubu Raya district, West Kalimantan. Complaints regarding musculoskeletal were identified in the process of frying chips. The complaints were carpal tunnel syndrome, low back pain, neck pain, as well as on the forearm and upper arm. Non-ergonomic working position contributes to these complaints. Therefore, it is necessary to perform this analysis and suggest a tool that would be helpful to reduce the worker’s complaints. Formerly, there haven’t been any early studies that cover the design of an automatic stove for the frying process based on biomechanical considerations, particularly on musculoskeletal disorder complaints.This study performs an analysis based on Nordic Body Map (NBM) and Rapid Upper Limb Assessment (RULA) concerning the process of frying the chips. Nordic Body Map analysis was used to identify body parts that were experiencing fatigue. Following the Nordic Body Map results, the automatic stove was designed to solve the employees’ complaints. RULA approach was used to analyze the condition after the employees carried out the work using the stove. The outcomes of this study are an automatic solenoid stove and a stool for the process of chips frying. RULA approach on the frying process with the manual stove and with the automatic solenoid stove resulted in L4-LV compression level reduced by 71.05%, whereas for Flex/Ext Compression was 87.97%
Antropometri Digital Suku Dayak, Melayu, dan Tionghoa Kalimantan Barat Berbasis Image Processing Yopa Eka Prawatya; Noveicalistus H Djanggu; Ratih Rahmawati; Syahmi Sajid
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 3 (2023): Volume 9 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i3.70233

Abstract

Kalimantan Barat merupakan daerah yang didiami oleh banyak suku bangsa dengan ketiga suku bangsa terbanyak adalah Dayak, Melayu, dan Tionghoa. Setiap suku bangsa memiliki dimensi tubuh yang berbeda-beda. Pengukuran dimensi tubuh atau antropometri umumnya dilakukan secara manual dengan menggunakan bantuan jangka sorong, mistar, dan pita meteran. Pengumpulan data antropometri untuk ketiga suku bangsa tersebut dari sejumlah banyak orang tentunya dapat dilakukan walaupun memerlukan waktu yang cukup lama. Pengumpulan data antropometri secara cepat serta efektif dan efisien dapat dilakukan dengan menggunakan antropometri digital berbasis image processing. Pengumpulan data antropometri menggunakan image processing dapat dilakukan dengan mengambil gambar dari objek penelitian menggunakan sebuah kamera. Gambar tersebut kemudian akan diolah menggunakan bahasa pemrograman Python dan dengan library OpenCV. Gambar terlebih dahulu akan dilabeli dengan sebuah bentuk melalui tahapan shape creation dan hasil bentuk yang dibangun kemudian dideteksi menggunakan object detection. Kemudian dilakukan perhitungan sistem dengan menggunakan koefisien pengali yang telah diperoleh melalui perhitungan titik acuan. Diperoleh akurasi program pengukuran antropometri digital adalah 98,66% dan tingkat error 0,99 cm. Berdasarkan hasil pengumpulan data diperoleh bahwa setiap suku bangsa memiliki karakteristik dimensi tubuh yang berbeda. Penggunaan antropometri digital dapat mengumpulkan data antropometri secara akurat dan cepat.
Co-Authors Noveicalistus H Djanggu Silvia Uslianti Syahmi Sajid Tri Wahyudi Yopa Eka Prawatya