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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.20 No.1 pp.1-8

Sizing System for Indonesian Policewomen’s Body Armour

Hari Purnomo, Fikrihadi Kurnia*
Industrial Engineering Department, Universitas Islam Indonesia, Yogyakarta, 55584, Indonesia
*Corresponding Author, E-mail:
January 15, 2019 August 5, 2019 January 22, 2021


Existing body armour sizes are focused on male users, as they are the majority of the population. The personal equipment of female and male soldiers should be separated because these groups have different sizes and matches. In other words, body armour design should correspond with user anthropometry. Good body armour must fit properly and be comfortable for the users. To solve this problem, this study develops a new sizing system. The study’s subjects were 150 with 20-to-30-year-old policewomen working in the Regional Police Department of Special Region of Yogyakarta. Data collection was performed with the simple random sampling method. Two statistical analysis methods, Principle Component Analysis (PCA) and clustering, were used to assist with the assessment of data. Analysis of the subjects indicated 15 size groups for body armour in three larger groups: S (VS, S, N, L and VL), M (VS, S, N, L and VL), and T (VS, S, N, L and VL). All size groups were validated using Euclidean distance, with an accuracy result of 66.67%.



    Historically, the Indonesian National Armed Forces and Indonesian Police were part of the Armed Forces of the Republic of Indonesia. However, since the implementation of Law No. 34 in 2004, the National Armed Forces have been separated from Indonesian Police. The National Armed Forces have no authority in security issues, which are the duties of Indonesian Police, unless by order of the President or if Indonesian Police orders National Armed Forces to assist Indonesian Police in security and public order tasks (Andrizal, 2014). To resist armed attack, personnel are given personal protective equipment. The equipment includes helmets, bulletproof vests and shields. Beside protecting the user, personal protective equipment must also be designed to be as comfortable and light as possible so as not to burden the user (Horsfall, 2012). For protective military equipment and gear, body dimension measurements are used to ensure user satisfaction, reduce weight, facilitate body movement and adjust elements to create comfort for users (Carr et al., 2012;Crouch, 2019). Therefore, military equipment design should correspond with user anthropometry.

    Anthropometry is a branch of ergonomics that analyses the shape and size of the human body and that can be used to measure a product to be consistent with user needs (Gupta, 2014;Kim and Kim, 2018;Vergara et al., 2019). Anthropometry is widely used even in the military, e.g., for apparel, aircraft, battleships and tanks in the United States and Europe (Gupta, 2014;Nicholson, 1991). Anthropometry for military use is unique because it directly affects the safety, performance and work of many individuals (Lee, 2014;Abtew et al., 2019).

    Measurements that are consistent with users require size classification (Pang et al., 2018;Lee et al., 2018). This allows for standard sizes for the product based on the diversity of user body dimensions (Widyanti et al., 2017;Kim and Kim, 2018). Classification starts with determining the key dimensions, which requires a statistical analysis of anthropometric data. The purpose of these key dimensions is to identify the level of significance of the specific dimensions used to divide population samples into clusters with similar body dimensions (Zakaria, 2014;Chan, 2014;Hamad et al., 2017). The common key dimensions used are height, chest girth, bust girth, waist girth and hip girth (Zakaria and Gupta, 2014). After obtaining key dimensions, size analysis must be performed consistent with the population sample (Zakaria and Gupta, 2014;Zakaria, 2014). The size classification is suitable if it has undergone a data validation process using Euclidean distance (Zakaria, 2014;Alfakih, 2018). Generally, the entire process of developing this classification is called the sizing system process.

    The number of policewomen is smaller than the number of policemen, and the existing equipment accordingly focuses on male personnel (Boussu et al., 2008). However, there are still female personnel who need equipment, and gender is one of the factors that affects anthropometric data, along with age, ethnicity or race and occupation (Wijaya et al., 2016;Reddy-Best et al., 2018;Abtew et al., 2019). The personal equipment of female and male soldiers should be separated, because these groups have different sizes and therefore different physical matches.

    There is no sizing system of body armour for police women in Indonesia, leaving female police officers inadequately equipped. This research paper aims to fill that gap by developing a sizing system for body armour for policewomen in Indonesia. Our study develops a sizing system using female police officers’ anthropometric data, which has before now not been gathered in Indonesia. The study results are expected to be implemented to make personal protective equipment for women that can be adjusted to improve their work performance


    2.1 Subject

    The research subjects were 20-to-30-year-old po-licewomen working in the Regional Police Department of Special Region of Yogyakarta. The sample number was 150 police officers with sample size of 10% from one cluster in Special Region of Yogyakarta, Indonesia. The selection of one cluster due to the conditions for admission has been regulated nationally, so there is not much difference, especially height. Data collection was performed by the simple random sampling method, with the following criteria: the subject had to be (1) an active police officer, (2) female, (3) 20 to 30 years old, (4) in possession of a normal Body Mass Index (BMI), and (5) able-bodied.

    2.2 Sizing System

    Generally, clothes are made to suit the physical needs of the wearer. This becomes an issue because the human body has many shapes and dimensions, so only having one clothing size means that clothing will be too small or too big for the wearer. Another issue is that the protective clothes must meet requirements for fitness and comfort (NIJ, 2014). Fitness means that the clothes are suitable to the body dimensions of the user, with a predetermined looseness tolerance. Comfort means that the clothes feel comfortable and do not restrict the wearer’s freedom of movement, avoiding the risk of danger (NIJ, 2014;CAST, 2017).

    To make suitable clothes, an analysis of the body dimensions of the user population is required (Kuo et al., 2020). The dimensions must be adjusted as required to make the desired clothes. Then, the population is divided into groups with similar body sizes. The combination of two or more dimensions is required to describe body shapes to determine the body types of a population that has been divided into groups. Finally, a label must be made, with each size is represented as certain symbol or number. This system makes it easier for wearers to choose and determine clothes that suit their needs without needing to be measured again and is the general method used for the analysis of sizing systems for clothing (Mpampa et al., 2010;Zakaria and Gupta, 2014;Gupta, 2014).

    A sizing system is an analysis process used to obtain size groups that can represent certain body dimensions of population, which are used as standard in making clothes (Gupta and Gangadhar, 2004;Mpampa et al., 2010;Gupta, 2014). Sizing systems were first introduced in 1884 in the United States to make standard clothing sizes using women’s body dimensions (Geršak, 2013). Over time, the measurement objects of sizing systems were changed, and the measurement method was improved. Today, sizing systems have been used nationally and internationally. Nationally, every country has their own standardization agency that uses a specific population as their measurement population. The globally recognized international standardization agency is the International Organization for Standardization, known as ISO (ISO, 2017).

    2.3 Anthropometry of Body Armour

    As described above, a sizing system is developed using a set of body dimensions of a population, adjusted for the requirements of the clothes to be made. Generally, the analysis of body dimension measurements is known as anthropometric analysis (Lee et al., 2018;Kuo et al., 2020). Anthropometry was used for the sizing system of body armour in the present study, using body dimensions based on Centre for Applied Science and Technology (CAST) standards (CAST, 2017). CAST is a standardization agency for bulletproof vests that has become a reference point for making and designing vests internationally. We adapted our measured body dimensions adapted from the CAST model as presented in Figure 1.

    Based on Figure 1, the dimensions required in the present study are presented in Table 1 below:

    Table 1 shows the 11 body parts used to make body armour (CAST, 2017). In general, the dimensions for body armour are not very different from those used in making clothes. In application, only two or three of the dimensions stated above are used as key dimensions. The common dimensions in a sizing system are the chest/bust circumference, the waist circumference and the height (ISO, 2017;Zakaria and Gupta, 2014;Reddy-Best et al., 2018). For women body armour, chest/bust area is additional dimensions that are specially used for measurement (Abtew et al., 2019). To be certain about the application of these dimensions, an analysis was first performed so that the dimensions could be applied in the present study.

    2.4 Research Procedure

    The measurement was performed at the Regional Police office in Special Region of Yogyakarta. Statistical calculation was performed manually and using statistics software, including Microsoft Excel 2016, XLSTAT 2018 and SPSS-25. The measurement steps were the following: 1) the collection of the anthropometric data (Table 1) and preliminary data analysis by univariate analysis; 2) PCA calculation to determine the group of every dimension and determine key dimensions; 3) cluster analysis using the cluster statistical method to group initial sample sizes; 4) data classification for the second-stage grouping; 5) data validation to determine the accuracy of the analysis results; and 6) a sizing proposal.


    3.1 Anthropometry Analysis

    Data was collected from 150 policewomen. The criteria for respondents were as follows: 1) that they were female police officers who had worked for over one year and were active personnel; 2) that the average age was 23.58±2.3 years old; 3) that they had an average height of 165.9±3.5 cm, with average requirements to enrol for police women in Indonesia is 163 cm; (4) an average weight of 55.6±3.8 kg; and 5) that they had an average Body Mass Index (BMI) of 20.2±1.1 kg/m2, thus showing a normal BMI. There are 11 body dimensions based on the use of body armour. Data distribution analysis is the calculation of mean, DS (Deviation Standard), CV (Coefficient of variation), and percentiles.

    3.2 Principal Component Analysis (PCA)

    PCA aims to classify variables into several homogenous components and reduce the variables. PCA is multivariate technique that analyzes data in which are described by several inter-correlated quantitative dependent variables (Mishra et al., 2017). In some studies, the PCA method is used in the sizing system process (Gupta and Gangadhar, 2004;Zakaria et al., 2008;Zakaria and Gupta, 2014). The PCA results are presented in Table 3.

    Based on calculations using the statistical software SPSS, three groups were created (Table): (1) Group 1, composed of BC, FTL, RTL, BH, FSH, FBW, BW and WBA; (2) Group 2, composed of one dimension (H), which was used as the primary dimension for the sizing system; and (3) Group 3, composed of BBC and WC. Group members were selected based on their scores in these dimensions. The minimum score of this study was 0.5. It was concluded that H should be used as the primary dimension to determine sizes, while BC and WC were secondary dimensions to be used to measure the drop value (Zakaria and Gupta, 2014;ISO, 2017).

    3.3 Cluster Analysis

    Cluster analysis is a calculation that is often used in data classification (Kuo et al., 2020). Hierarchical clusters were applied to identify differences between groups (Vergara et al., 2019). Here, the process serves to identify sizes based on body dimension types (Capelassi et al., 2017;Vergara et al., 2019). Body dimensions were classified by height into three groups: Short, Medium, and Tall. The results of calculations using this software are presented in Table 4:

    Based on Table 4, Cluster 1 was a part of the Medium group with 63 samples (164 ≥ 165.8 ≤ 168), Cluster 2 was a part of the Short group with 45 samples (160 ≥ 161.8 ≤ 163), and Cluster 3 was a part of the Tall group with 42 samples (169 ≥ 170.6 ≤ 172).

    3.4 Classification

    Grouping is used to group size populations by body shape (Zakaria and Gupta, 2014;Lee, 2014). The sizing system for women uses BC and WC to determine body sizes (Mpampa et al., 2010;ISO, 2017). Our classifica-tion produced two measurement patterns: H, which represented length (vertical size); BC and WC, which represented girth (horizontal size). The classification results are presented in Table 5.

    There are five size groups formed in this study, namely, Very Small (VS), Small (S), Normal (M), Large (L), and Very Large (VL). Classification in this process uses the differentiation distance between the dimensions of BC and WC. The sample used for this process was 150 personnel. Based on the differentiation results of BC and WC dimensions, the largest percentage of the size group was L (34%), then M (30%), VL (18%), S (14%), and VS (4%).

    3.5 Validation

    Validation was used to determine the deviation or accuracy of the proposed measurements in relation to the body dimension sizes of wearers in the field. The process was performed by comparing the proposed sizes using Euclidean distance. The proposed sizes were obtained using the Euclidean distance calculation of key dimen-sions (BC and WC) (Zakaria and Gupta, 2014;Mpampa et al., 2010). Meanwhile, a comparison of the proposed sizing was simulated using percentile and range. Lastly, the smallest value of the Euclidean distance was used for the minimum and maximum limit values of the final proposed sizes. The results of the calculation are presented in Table 6.

    Based on the results in Table 6, the 10th-to-90th per-centile range was used for the limit value of the final proposed sizing. The accuracy of this sizing is 66.67%, and the total average is 8.47 cm. For this result, the conclusion of the number limit value (minimum and maximum) for all dimension uses this percentile.

    3.6 Proposed Sizes

    Based on the calculation, there were three size groups with 15 final sizes proposed: S (VS, S, N, L and VL), M (VS, S, N, L and VL) and T (VS, S, N, L and VL).

    As shown in Table 7, there are 15 size variations formed based on data percentiles and intervals. The percentile used to determine the minimum measurement is the tenth percentile, while the 90th was used for the maximum measurement. Interval implementation was done by reducing the minimum and maximum limits in one size group or between groups of sizes, e.g., the dimensions of BC (with the S–VS size having 2 cm intervals), the dimensions of WC (with the S–VS size having 1 cm intervals), and the dimensions of BBC (where the S–VS size was reduced with SS size so the interval would be 1 cm). The process of determining intervals was applied to all dimensions and adjusted to the minimum and maximum size values.

    Summary of sizes that can be produced according to needs as in Table 8. The proposed research uses sub-size N (Normal) as a simplification of the number of sizes. The sub-size development is because Normal size is the body's ideal body shape. Research related to the sizing system for female police in Indonesia has not been found. However, this study is supported by the research of Esty Nurbaity et al. (2019), for sizing clothing which has almost the same results. Comparison of research results with International Standards for women’s body armour from the Centre for Applied Science and Technology (CAST), from the United Kingdom (CAST, 2017) is shown in Table 9 below:

    Table 9 is a comparison of the size between CAST and research results. The calculation results of measure-ments differ from the CAST standard due to differences in body dimensions of European and Indonesian people. In general, the bodies of Europeans are bigger than the bodies of Southeast Asians. The size of the body armour from CAST in the S size category while the body armour size results from the majority of M and L measurements.


    Anthropometry is the basic method and start of sizing system calculation. Based on the analysis of policewomen, there were three size groups with fifteen final sizes proposed: S (VS, S, N, L and VL), M (VS, S, N, L and VL), and T (VS, S, N, L and VL). All size groups have been validated to determine the accuracy of the sizes. The results are the proposed sizes targeted for policewomen in Indonesia. The present study is expected to be used as a reference for producing special body armour for Indonesian female users. This study could also be a reference for future studies to improve and develop future body armour.



    Anthropometry dimensions (CAST, 2017).


    Example sizing.


    Body dimensions for a sizing system for body armour

    Distribution data

    Result of PCA

    Cluster results

    Result of classification base on drop value

    Validation results

    Sizing results

    The measurement is possibilities for production

    Comparation study


    1. Abtew, M. A., Bruniaux, P., and Boussu, F. (2019), Customizations of women bullet-proof jacket through 3D design process, Textile & Leather Review, 2(1), 23-31.
    2. Alfakih, A. Y. (2018), On yielding and jointly yielding entries of Euclidean distance matrices, Linear Algebra and its Applications, 556, 144-161.
    3. Andrizal (2014), Analisis yuridis tentang kedudukan tentara nasional indonesia (TNI) setelah berlakunya undang-undang nomor 34 tahun 2004, Jurnal Ilmu Hukum, 110-119.
    4. Boussu, F., Ragot, A., Kulinska, M., and Bruniaux, P. (2008), Customization of a lightweight ballistic vest, Proceedings of the 2nd International Scientific Conference Textiles of the Future, Kortrijk, Belgium.
    5. Capelassi, C. H., Carvalho, M. A., El-Kattel, C., and Xu, B. (2017), Sizing for the apparel industry using statistical analysis: A Brazilian case study, IOP Conf. Series: Materials Science and Engineering,254(17), 1-5.
    6. Carr, D. J., Wilson, C. A., and Laing, R. M. (2012), Anthropometric methods for the successful design of military clothing and equipment, Advances in Military Textiles and Personal Equipment, Woodhouse Publishing, United Kingdom, No. 122, Part 3, 49-63.
    7. CAST (2017), The Home Office: Body Armour Standard (2017), CAST Publication number: 012/17, Centre for Applied Science and Technology, United Kingdom.
    8. Chan, A. C. K. (2014), The development of apparel sizing systems from anthropometric data, Anthropometry, Apparel Sizing and Design, Woodhouse Publishing, United Kingdom, No. 148, Part 2, 167-196.
    9. Crouch, I. G. (2019), Body armour – New materials, new systems, Defence Technology, 15(3), 241-253.
    10. Esty Nurbaity, A., Suryawati, and Zahra, E. L. (2019), The Analysis of the Standardization of the Sizing of Muslim Women’s Clothing in Indonesia, In 3rd UNJ International Conference on Technical and Vocational Education and Training 2018, KnE Social Science, 573-578.
    11. Geršak, J. (2013), Clothing sizing systems, Anthropometry, Apparel Sizing and Design, Woodhouse Publishing, United Kingdom, No. 147, Chapter 2, 21-52.
    12. Gupta, D. (2014), Anthropometry and the design and production of apparel: An overview, Anthropometry, Apparel Sizing and Design, Woodhouse Publishing, United Kingdom, No. 148, Part 1, Chapter 2, 34-66.
    13. Gupta, D. and Gangadhar, B. R. (2004), A statistical model for developing body size charts for garments, International Journal of Clothing Science and Technology, 16(5), 458-469.
    14. Hamad, M., Thomassey, S., and Bruniaux, P. (2017), A new sizing system based on 3D shape descriptor for morphology clustering, Computers & Industrial Engineering, 113, 683-692.
    15. Horsfall, I. (2012), Key issues in body armour: Threats, materials and design, Advances in Military Textiles and Personal Equipment, Woodhead Publishing, United Kingdom, No. 122, Part 1, 3-20.
    16. ISO (2017), ISO/DIS 8559-3:2017(E): Size designation of clothes- Part 3: Methodology of the creation of the body measurement tables and intervals, International Organization for Standardization, Switzerland.
    17. Kim, M. and Kim, S. (2018), Development of a script-based versatile three-dimensional body measurement system, International Journal of Clothing Science and Technology, 30(5), 598-609.
    18. Kuo, C. C., Wang, M. J., and Lu, J. M. (2020), Developing sizing systems using 3D scanning head anthropometric data, Measurement, 152, 107264.
    19. Lee, W., Lee, B., Yang, X., Jung, H., Bok, I., Kim, C., Kwon, O., and You, H. (2018), A 3D anthropometric sizing analysis system based on North American CAESAR 3D scan data for design of head wearable products, Computers & Industrial Engineering, 117, 121-130.
    20. Lee, Y. S. (2014), Developing apparel sizing systems for particular groups, Anthropometry Apparel Sizing and Design, Woodhead Publishing, United Kingdom, 197-254.
    21. Mishra, S. P., Sarkar, U., Taraphder, S., Datta, S., Swain, D. P., Saikhom, R., Panda, S., and Laishram, M. (2017), Multivariate statistical data analysis-principal component analysis (PCA), International Journal of Livestock Research, 7(5), 60-78.
    22. Mpampa, M. L., Azariadis, P. N., and Sapidis, N. S. (2010), A new methodology for the development of sizing systems for the mass customization of garments, International Journal of Clothing Science and Technology, 22(1), 49-68.
    23. Nicholson, A. S. (1991), Anthropometry in workspace design, Advances in Human Factors/Ergonomics, 15, 3-28.
    24. NIJ (2014), Selection & Application Guide 0101.06 to Ballistic-Resistant Body Armor, National Institute of Justice, U.S.
    25. Pang, T. Y., Lo, T. S. T., Ellena, T., Mustafa, H., Babalija, J., and Subic, A. (2018), Fit, stability and comfort assessment of custom-fitted bicycle helmet inner liner designs, based on 3D anthropometric data, Applied Ergonomics, 68, 240-248.
    26. Reddy-Best, K. L., Choi, E., and Park, H. (2018), Race, colorism, body size, body position, and sexiness: Critically analyzing Women in fashion illustration textbooks, Clothing and Textiles Research Journal, 36(4), 281-295.
    27. Vergara, M., Agost, and M. J., Bayarri, V. (2019), Anthropometric characterisation of palm and finger shapes to complement current glove-sizing systems, International Journal of Industrial Ergonomics, 74, 102836.
    28. Widyanti, A., Mahachandra, M., Soetisna, H. R., and Sutalaksana, I. Z. (2017), Anthropometry of Indonesian Sundanese children and the development of clothing size system for Indonesian Sundanese children aged 6-10 years, International Journal of Industrial Ergonomics, 61, 37-46.
    29. Wijaya, M. A., Siboro, B. A. H., and Purbasari, A. (2016), Analisa perbandingan antropometri bentuk tubuh mahasiswa pekerja galangan kapal dan mahasiswa pekerja elektronika, Jurnal Profisiensi, 4(2), 110.
    30. Zakaria, N. (2014), Anthropometry and the design and production of apparel, Anthropometry, Apparel Sizing and Design, Woodhouse Publishing, United Kingdom, No. 148, Part 1, Chapter 4, 95-119.
    31. Zakaria, N. and Gupta, D. (2014), Apparel sizing: existing sizing systems and the development of new sizing systems, Anthropometry, Apparel Sizing and Design, Woodhouse Publishing, United Kingdom, No. 148, Part 1, Chapter 1, 3-33.
    32. Zakaria, N., Mohd, J. S., Taib, N., Tan, Y. Y., and Wah, Y. B. (2008), Using data mining technique to explore anthropometric data towards the development of sizing system, ITSim 2008: International Symposium on Information Technology, 2, 1-7.
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