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A Comparison of Hand Grip Strength Among Healthy Young Adult Malaysian and Thai Women Isa Halim; Radin Zaid Radin Umar; Zulkeflee Abdullah; Muhammad Syafiq Syed Mohamed; Seri Rahayu Kamat; Mohd Shukor Salleh; Dujdow Buranapanichkit; Kunlapat Thongkaew; Ezrin Hani Sukadarin; Denni Kurniawan; Adi Saptari
Jurnal Optimasi Sistem Industri Vol. 25 No. 1 (2026): Published in June 2026
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v25.n1.p42-62.2026

Abstract

Hand grip strength (HGS) is a well-known parameter of physical capability, clinical health status, and functional work performance. However, the scarcity of standardized, region-specific HGS data for Southeast Asian populations restricts the accuracy of health screening practices and the development of ergonomics and occupational safety guidelines. The aim of this study was to measure the dominant-hand HGS for healthy young adult women of Malaysia and Thailand, to compare the HGS of these two groups of women, and to investigate the relationship between age and anthropometric variables and the HGS. Researchers conducted a cross-sectional study involving 166 healthy women aged 20 to 39 years. This study recruited 92 participants from Malaysia and 74 from Thailand, primarily from university students and staff populations. Dominant-hand HGS was measured using a Jamar dynamometer (Sammons Preston, USA) while participants adopted a standardized standing position with the forearm in a neutral posture. Thai women demonstrated significantly greater mean HGS than Malaysian women (27.31 ± 6.96 kg vs. 23.64 ± 4.67 kg; p < 0.001), corresponding to an approximately 16% difference and a medium-to-large effect size (Cohen’s d = 0.63). Among Thai participants, HGS was significantly associated with palm circumference (r = 0.544), height, weight, and age. These variables collectively explained 44.8% of the variation in HGS. In contrast, only height showed a modest association with HGS among Malaysian participants. Meanwhile, the corresponding regression model demonstrated limited explanatory capability. These findings reveal population-specific differences in both HGS and its anthropometric correlates when assessed under standardized testing conditions. The study provides protocol-specific, preliminary reference data for healthy young adult Malaysian and Thai women, which may inform future development of validated, population-specific reference standards. By generating population-specific reference data, this study contributes to improving the accuracy and equity of health monitoring practices, in line with the objectives of United Nations SDG 3 (Good Health and Well-being).
Prediction of Ground Vibration due to Blasting Activities of Coal Open Pit Mine Near Village Residents Using Multivariate Logarithmic Regression Alloysius Vendhi Prasmoro; Nurhadi Siswanto; Budi Santosa; Giri Waluyo Nugraha; Mohd Shukor Salleh
Advance Sustainable Science Engineering and Technology Vol. 8 No. 3 (2026): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i3.3616

Abstract

Blasting activities are among the most important in mining and can have a negative impact on the environment and surrounding communities, causing disruption and even damaging nearby buildings and infrastructure. If the community protests and demonstrates, mining operations may be shut down, which would be very detrimental to the company. Studies are needed on effective planning to reduce the negative impacts. Ground vibrations measured by Peak Particle Velocity (PPV) are subject to thresholds set by each region's standards; in this research area, the maximum threshold is 3 mm/s to avoid damage to nearby buildings or settlements. The important variables are the explosive charge per delay and the distance, along with other blasting geometry variables such as spacing, burden, stemming, powder factor, and number of blast holes. Several previous researchers have used methods to predict PPV, with detonation parameters as the independent variables. This research uses general empirical methods and multivariate logarithmic regression (MLR). Prediction using MLR is better than general empirical methods; with R2 = 0.925, RMSE = 0.247, MAE = 0.548, MAPE = 0.218, and VAF = 96.66%, indicating near-perfect prediction. The MLR model produces a reference maximum explosive charge per delay of 59.09 kg.