Impact of Mahalanobis-Taguchi System on health performance among academicians - Nur Aisyah Mardhiah, Halim; Mohd Yazid, Abu; Nor Suhadah, Razali; Nurul Haziyani, Aris; Emelia Sari, .; Nur Najmiyah, Jaafar; Ahmad Shahrizan, Abdul Ghani; Faizir, Ramlie; Wan Zuki Azman, Wan Muhamad; Nolia, Harudin (Faculty of Engineering, Universitas Indonesia, 2025)
Health performance generally refers to the effectiveness and efficiency of individual or population health outcomes and behaviors. It comprises various aspects, such as physical health, specifically how well an individual manages disease and engages in preventive measures, as well as mental health. Non-communicable diseases affect individuals across diverse backgrounds and regions globally. Therefore, this study aimed to investigate the impact of Mahalanobis-Taguchi System (MTS) on health performance among academicians. Data were collected from health center that served all academic faculties at a local university, focusing on the years 2022 and 2023. To achieve the objective, a total of 17 parameters were considered. The robust Taguchi (RT) Method was used for classification, while the Taguchi (T) Method was used for optimization. In 2022, Mahalanobis distance for abnormal cases ranged between a minimum of 0.0130 and a maximum of 49.9425. For normal cases, the distance ranged between 0.0176 and 44.5121, with a total of 48 samples overlapping the threshold. In 2023, the distance ranged between 0.012843 and 36.986225 for abnormal cases. Meanwhile, for normal cases, the distance ranged between 0.002879 and 8.405225, with a total of 122 samples overlapping the threshold. For both 2022 and 2023, the data for normal and abnormal cases showed a strong negative correlation, with values of -0.6161, -0.3636, -0.5921, and -0.6252, respectively. Regarding the degree of contribution, seven parameters, namely fasting plasma glucose, untreated systolic blood pressure, treated systolic blood pressure, pulse, body mass index (BMI), body fat, and waist circumference, showed a positive degree of contribution in 2022. In 2023, ten parameters, including random plasma glucose, fasting plasma glucose, untreated systolic blood pressure, treated systolic blood pressure, diastolic blood pressure, pulse, BMI, body fat, skeletal muscle, and waist circumference, showed a positive degree of contribution. Therefore, MTS is a valuable tool for evaluating health performance among academicians, offering robust classification and optimization capabilities.