Judul: Analisis Surface Electromyography (SEMG) Terhadap Penggunaan Exoskeleton Pada Kegiatan Panen Muat Kelapa Sawit
Abstrak: Aktivitas kerja yang dilakukan di perkebunan kelapa sawit sampai saat ini masih mengandalkan tenaga manusia. Gangguan otot rangka atau musculoskeletal disorders (MSDs) cukup umum dialami oleh para pemanen, maka dari itu pemanen membutuhkan alat bantu yang dapat mengurangi resiko kerja mereka. Penelitian ini bertujuan mengetahui pengaruh exoskeleton terhadap kerja otot pemanen saat melakukan kegiatan panen muat kelapa sawit. Hasil penelitian diharapkan dapat membantu pemanen mengurangi resiko keselamatan kerja mereka serta memberikan alat bantu untuk mengurangi resiko cedera. Otot yang diteliti pada penelitian ini adalah otot deltoid dan otot trapezius atas. Sensor electromyography (EMG) digunakan untuk mendapatkan data aktivitas kerja otot. Analisis data menggunakan analysis of variance (ANOVA) menggunakan SPSS 27.0. Uji shapiro wilk digunakan untuk mengetahui data yang terdistribusi secara normal, data dianggap normal jika p>0.05, jika data terdistribusi normal maka dilanjutkan dengan paired T-test sedangkan yang terdistribusi tidak normal dilanjutkan dengan wilcoxon signed rank test. Perbedaan beban kerja yang signifikan didapatkan di proses panen pada otot deltoid yaitu sebesar 19±9%MVE sebelum menggunakan exoskeleton dan 16±8%MVE setelah menggunakan exoskeleton. Pada proses muat tidak terlalu banyak perbedaan dikarenakan cara pemanen melakukan kegiatan muat berbeda-beda. Hal tersebut menunjukkan bahwa exoskeleton dapat mengurangi beban kerja pemanen terutama pada saat melakukan kegiatan panen., Work activities carried out in oil palm plantations until now still rely on human labor. Skeletal muscle disorders or musculoskeletal disorders (MSDs) are quite common among harvesters, therefore harvesters need tools that can reduce their work risks. This study aims to determine the influence of the exoskeleton on the work of harvester muscles when harvesting oil palm loading. The results of the study are expected to help harvesters reduce their occupational safety risks and provide tools to reduce the risk of injury. The muscles studied in this study were the deltoid muscle and the upper trapezius muscle. Electromyography (EMG) sensors are used to obtain data on muscle work activity. Data analysis using analysis of variance (ANOVA) using SPSS 27.0. The shapiro wilk test is used to determine normally distributed data, the data is considered normal if p>0.05, if the data is normally distributed then continued with the paired T-test while the abnormally distributed is continued with the Wilcoxon signed rank test. A significant difference in workload was obtained in the harvesting process in deltoid muscles, which was 19±9% MVE before using the exoskeleton and 16±8% MVE after using the exoskeleton. In the loading process, there is not too much difference because the way harvesters carry out loading activities is different. This shows that the exoskeleton can reduce the workload of harvesters, especially when harvesting.
Keyword: pemanenan kelapa sawit, musculoskeletal disorders (MSDs), exoskeleton

Judul: Precision Motion Analysis Using Motion Capture (Noitom) in Oil Palm Harvestin
Abstrak: Kegiatan pemanenan kelapa sawit di Indonesia masih dilakukan secara manual dengan menggunakan tenaga manusia. Aktivitas yang dilakukan secara manual ini sangat berisiko dalam menyebabkan gangguan otot rangka atau Musculoskeletal Disorders (MSDs). Penelitian ini bertujuan untuk memetakan tingkat risiko kerja berdasarkan postur pemanen dengan menggunakan analisis Range of Motion (ROM) dan Rapid Entire Body Assessment (REBA) untuk menjadi rekomendasi perbaikan postur kerja yang aman bagi pemanen kelapa sawit. Penelitian ini juga bertujuan untuk mengetahui korelasi antara ekstensi pada leher dengan tinggi badan, fleksi pada bahu dengan fleksi pada lengan bawah, dan fleksi pada pangkal paha dengan fleksi pada lutut pada pemanenan kelapa sawit, serta mengetahui gerakan yang besarnya dipengaruhi oleh letak bagian tubuh pada pemanenan kelapa sawit. Data pada penelitian ini diambil menggunakan metode motion capture lalu kemudian diolah dengan menggunakan software Axis Neuron dan Biomechanics of Bodies. Hasil analisis ROM menunjukkan tubuh bagian atas memiliki risiko lebih tinggi mengalami MSDs dengan leher, bahu, dan lengan bawah menjadi bagian tubuh yang paling banyak berada dalam zona bahaya. Kegiatan pemanenan kelapa sawit mendapat skor 12-14 pada penilaian REBA yang berarti perlu segera dilakukan intervensi ergonomika untuk memperbaiki metode ataupun prosedur kerja agar risiko dapat dimitigasi ataupun diminimalisir., Oil palm harvesting activities in Indonesia are still carried out manually using human labor. This manual activity is very risky to cause Musculoskeletal Disorders (MSDs). This study aims to map the level of work risk based on the posture of harvesters using Range of Motion (ROM) analysis and Rapid Entire Body Assessment (REBA) to be a recommendation for improving safe work postures for oil palm harvesters. This study also aims to determine the correlation between neck extension with height, shoulder flexion with elbow flexion, and hip flexion with knee flexion in oil palm harvesting, and determine the movements that are most influenced by the location of body parts in oil palm harvesting. The data were taken using the motion capture method and then processed using Axis Neuron and Biomechanics of Bodies. The ROM analysis results show that the upper body has a higher risk of MSDs with the neck, shoulders, and forearms as the body parts that are most in the danger zone. Oil palm harvesting activities received a score of 12-14 on the REBA assessment which means ergonomic interventions need to be carried out immediately to improve work methods or procedures so that risks can be mitigated or minimized.
Keyword: oil palm harvesting, ergonomy, motion analysis, ROM, REBA

Judul: Construction of Strongly Optimal Binary Linear Code with Minimum Distance 9 and 11
Abstrak: A binary linear code of length n over q F is a subspace of n q F . A code has three parameters that attached to it, namely length, dimension, and minimum distance. A code with length n, dimension k and minimum distance d is often called [n, k, d ]-code. Usually, when two parameters are given, then we want to find a code that has the best value for the last parameter. Based on Gilbert- Varshamov bound, if a [n, k, d ]-code exists and can not be expanded, we call it a strongly optimal code. In this paper, we construct strongly optimal code with minimum distance 9 and 11. In constructing the code, we created a theorem and algorithm based on Gilbert-Varshamov bound before we implement the algorithm to MAPLE programming language. Because of computational limitations, the program can only construct up to k = 10 for d = 9 and k = 12 for d = 11.
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