How to cite this paper
Priyanto, S., Soeprijanto, S., Badrujaman, A & Sahara, S. (2024). Evaluation approach of the mechanical engineering competency test certification using the assessment evaluability and performance monitoring model.Decision Science Letters , 13(1), 249-260.
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Asplund, S., & Kilbrink, N. (2020). Lessons from the welding booth: theories in practice in vocational education. Empirical Research in Vocational Education and Training, 12(1). https://doi.org/10.1186/s40461-020-0087-x
Bharambe, Y., Mored, N., Mulchandani, M., Shankarmani, R., & Shinde, S. G. (2017). Assessing employability of students using data mining techniques. 2017 Int. Conf. Adv. Comput. Commun. Informatics, 2017, 2110–2114.
https://doi.org/10.1109/icacci.2017.8126157.
Billett, S. (2000). Defining the demand side of vocational education and training: industry, enterprises, individuals and regions. Journal of Vocational Education & Training, 52(1), 5–31. https://doi.org/10.1080/13636820000200104.
Boyce, A. S., & McGowan, B. L. (2018). An exploration of two novice evaluation educators’ experiences developing and implementing introduction to evaluation courses. American Journal of Evaluation, 40(1), 119–136. https://doi.org/10.1177/1098214018778812
Budiyanto, B., & Suyanto, W. (2020). The evaluation of competency certification program through the LSP P-1 at vocational high school. Jurnal Pendidikan Vokasi, 10(1). https://doi.org/10.21831/jpv.v10i1.30155
Conejero, J. M., Preciado, J. C., Prieto, A. E., Bas, M., & Bolós, V. J. (2021). Applying data driven decision making to rank vocational and educational training programs with TOPSIS. Decision Support Systems, 142, 113470. https://doi.org/10.1016/j.dss.2020.113470
Cook, J. A. (2006). Employment barriers for persons with psychiatric disabilities: Update of a report for the President’s Commission. Psychiatric Services, 57(10), 1391–1405. https://doi.org/10.1176/ps.2006.57.10.1391
Edwards, R., & Holland, J. (2020). Reviewing challenges and the future for qualitative interviewing. International Journal of Social Research Methodology, 23(5), 581–592. https://doi.org/10.1080/13645579.2020.1766767
Finegold, D., & Soskice, D. (1988). The failure of training in britain: analysis and prescription. Oxford Review of Economic Policy, 4(3), 21–53. https://doi.org/10.1093/oxrep/4.3.21
Ibrahim, A. B. (2022). Trends and patterns of needs assessments in technical and vocational education: A thematic review. International Journal of Evaluation and Research in Education, 11(1), 88. https://doi.org/10.11591/ijere.v11i1.21940
Jackson, D. (2013). Factors influencing job attainment in recent Bachelor graduates: evidence from Australia. Higher Education, 68(1), 135–153. https://doi.org/10.1007/s10734-013-9696-7
Leckie, G. J., & Fullerton, A. M. (1999). Information Literacy in Science and Engineering Undergraduate Education: Faculty attitudes and pedagogical practices. College & Research Libraries, 60(1), 9–29. https://doi.org/10.5860/crl.60.1.9
Li, C. (2018). The Building of Teaching Quality Evaluation System of Higher Vocational Education under the New Situation. No. Iceemr, 182, 309–313. https://doi.org/10.2991/iceemr-18.2018.71
Li, P., Wu, J., & Qian, H. (2011). Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China. Environmental Monitoring and Assessment, 184(8), 4841–4854. https://doi.org/10.1007/s10661-011-2306-1
Li, Z., Luo, Z., Wang, Y., Fan, G., & Zhang, J. (2022). Suitability evaluation system for the shallow geothermal energy implementation in region by Entropy Weight Method and TOPSIS method. Renewable Energy, 184, 564–576.
https://doi.org/10.1016/j.renene.2021.11.112
Mahmudah, F. N., & Santosa, B. (2021). Vocational school alignment based-on industry needs. Journal of Vocational Education Studies (JOVES), 4(1), 36. https://doi.org/10.12928/joves.v4i1.3611
Mewburn, I., Grant, W. J., Suominen, H., & Kizimchuk, S. (2018). A machine learning analysis of the non-academic employment opportunities for Ph.D. graduates in Australia. Higher Education Policy, 33(4), 799–813. https://doi.org/10.1057/s41307-018-0098-4
Muharam, Y. A. (2022, February 17). Evaluation of the competency certification program of the national professional certification board in vocational high school. https://conference.loupiasconference.org/index.php/icogemt2/article/view/288
Ni, Z., & Wang, F. (2022). Quality Assessment of Vocational Education Teaching reform based on Deep learning. Computational and Mathematical Methods in Medicine, 2022, 1–11. https://doi.org/10.1155/2022/1499420
Nurtanto, M., Sofyan, H., Pardjono, P., & Suyitno, S. (2020). Development model for competency improvement and national vocational qualification support frames in Automotive technology. International Journal of Evaluation and Research in Education, 9(1), 168. https://doi.org/10.11591/ijere.v9i1.20447
Rahdiyanta, D., Nurhadiyanto, D., & Munadi, S. (2019). The effects of situational factors in the implementation of Work-Based Learning Model on vocational education in Indonesia. International Journal of Instruction, 12(3), 307–324. https://doi.org/10.29333/iji.2019.12319a
Rodríguez, R. S., Svensson, G., & Wood, G. (2020). Assessing corporate planning of future sustainability initiatives in private healthcare organizations. Evaluation and Program Planning, 83, 101869. https://doi.org/10.1016/j.evalprogplan.2020.101869
Rodríguez-Dorans, E., & Jacobs, P. (2020). Making narrative portraits: a methodological approach to analysing qualitative data. International Journal of Social Research Methodology, 23(6), 611–623. https://doi.org/10.1080/13645579.2020.1719609
Rusmulyani, K., Yudana, I. M., Natajaya, I. N., & Divayana, D. G. H. (2022). E-Evaluation based on CSE-UCLA Model Refers to Glickman Pattern for Evaluating the Leadership Training Program. International Journal of Advanced Computer Science and Applications, 13(5). https://doi.org/10.14569/ijacsa.2022.0130534
Sara, N., Halland, R., Igel, C., & Alstrup, S. (2015). High-School dropout prediction using machine Learning: a Danish large-scale study. The European Symposium on Artificial Neural Networks. https://dblp.uni-trier.de/db/conf/esann/esann2015.html#SaraHIA15
Schwenger, B. (2017). Research on training wheels – embedding academic literacy and numeracy in vocational pedagogy through action research. Educational Action Research, 26(2), 288–300. https://doi.org/10.1080/09650792.2017.1310053
Sen, B., Uçar, E., & Delen, D. (2012). Predicting and analyzing secondary education placement-test scores: A data mining approach. Expert Systems With Applications, 39(10), 9468–9476. https://doi.org/10.1016/j.eswa.2012.02.112
Shippee, N. D., Finch, M., & Wholey, D. R. (2018). Using statewide data on health care quality to assess the effect of a Patient-Centered Medical Home Initiative on quality of care. Population Health Management, 21(2), 148–154. https://doi.org/10.1089/pop.2017.0017
Stofkova, Z., & Sukalova, V. (2020). Sustainable development of human resources in globalization period. Sustainability, 12(18), 7681. https://doi.org/10.3390/su12187681.
Sumbodo, W., Yudiono, H., Salim, & Setiadi, R. (2019). The role of industry partners to improving student competency of vocational high school. Journal of Physics, 1387, 012031. https://doi.org/10.1088/1742-6596/1387/1/012031
Suyasa, P. W. A., & Kurniawan, P. S. (2018). Pemberdayaan Model CSE-UCLA Dalam Pelaksanaan Evaluasi Program Blended Learning di SMA Negeri 1 Ubud. Wacana Akademika. https://doi.org/10.30738/wa.v2i2.2627.
Wahyuni, D. S., Agustini, K., Sindu, I. G. P., & Sugihartini, N. (2020). Analysis on vocational high school teacher competency gaps: implication for VHS teacher training needs. Journal of Physics, 1516(1), 012051. https://doi.org/10.1088/1742-6596/1516/1/012051
Wholey, D. R., White, K., Adair, R., Christianson, J. B., Lee, S., & Elumba, D. (2013). Care guides. Health Care Management Review. https://doi.org/10.1097/hmr.0b013e31825f3df9
Wholey, D. R., Zhu, X., Knoke, D., Shah, P. P., Zellmer-Bruhn, M. E., & Witheridge, T. F. (2012). The teamwork in Assertive Community Treatment (TACT) scale: development and validation. Psychiatric Services, 63(11), 1108–1117. https://doi.org/10.1176/appi.ps.201100338
Amin, M. S. (2018). Pendekatan Alternatif Sebagai Strategi Evaluasi Program Daur Ulang Sampah Dengan Metode Takakura. Jurnal Kiprah. https://doi.org/10.31629/kiprah.v6i1.582
Asplund, S., & Kilbrink, N. (2020). Lessons from the welding booth: theories in practice in vocational education. Empirical Research in Vocational Education and Training, 12(1). https://doi.org/10.1186/s40461-020-0087-x
Bharambe, Y., Mored, N., Mulchandani, M., Shankarmani, R., & Shinde, S. G. (2017). Assessing employability of students using data mining techniques. 2017 Int. Conf. Adv. Comput. Commun. Informatics, 2017, 2110–2114.
https://doi.org/10.1109/icacci.2017.8126157.
Billett, S. (2000). Defining the demand side of vocational education and training: industry, enterprises, individuals and regions. Journal of Vocational Education & Training, 52(1), 5–31. https://doi.org/10.1080/13636820000200104.
Boyce, A. S., & McGowan, B. L. (2018). An exploration of two novice evaluation educators’ experiences developing and implementing introduction to evaluation courses. American Journal of Evaluation, 40(1), 119–136. https://doi.org/10.1177/1098214018778812
Budiyanto, B., & Suyanto, W. (2020). The evaluation of competency certification program through the LSP P-1 at vocational high school. Jurnal Pendidikan Vokasi, 10(1). https://doi.org/10.21831/jpv.v10i1.30155
Conejero, J. M., Preciado, J. C., Prieto, A. E., Bas, M., & Bolós, V. J. (2021). Applying data driven decision making to rank vocational and educational training programs with TOPSIS. Decision Support Systems, 142, 113470. https://doi.org/10.1016/j.dss.2020.113470
Cook, J. A. (2006). Employment barriers for persons with psychiatric disabilities: Update of a report for the President’s Commission. Psychiatric Services, 57(10), 1391–1405. https://doi.org/10.1176/ps.2006.57.10.1391
Edwards, R., & Holland, J. (2020). Reviewing challenges and the future for qualitative interviewing. International Journal of Social Research Methodology, 23(5), 581–592. https://doi.org/10.1080/13645579.2020.1766767
Finegold, D., & Soskice, D. (1988). The failure of training in britain: analysis and prescription. Oxford Review of Economic Policy, 4(3), 21–53. https://doi.org/10.1093/oxrep/4.3.21
Ibrahim, A. B. (2022). Trends and patterns of needs assessments in technical and vocational education: A thematic review. International Journal of Evaluation and Research in Education, 11(1), 88. https://doi.org/10.11591/ijere.v11i1.21940
Jackson, D. (2013). Factors influencing job attainment in recent Bachelor graduates: evidence from Australia. Higher Education, 68(1), 135–153. https://doi.org/10.1007/s10734-013-9696-7
Leckie, G. J., & Fullerton, A. M. (1999). Information Literacy in Science and Engineering Undergraduate Education: Faculty attitudes and pedagogical practices. College & Research Libraries, 60(1), 9–29. https://doi.org/10.5860/crl.60.1.9
Li, C. (2018). The Building of Teaching Quality Evaluation System of Higher Vocational Education under the New Situation. No. Iceemr, 182, 309–313. https://doi.org/10.2991/iceemr-18.2018.71
Li, P., Wu, J., & Qian, H. (2011). Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China. Environmental Monitoring and Assessment, 184(8), 4841–4854. https://doi.org/10.1007/s10661-011-2306-1
Li, Z., Luo, Z., Wang, Y., Fan, G., & Zhang, J. (2022). Suitability evaluation system for the shallow geothermal energy implementation in region by Entropy Weight Method and TOPSIS method. Renewable Energy, 184, 564–576.
https://doi.org/10.1016/j.renene.2021.11.112
Mahmudah, F. N., & Santosa, B. (2021). Vocational school alignment based-on industry needs. Journal of Vocational Education Studies (JOVES), 4(1), 36. https://doi.org/10.12928/joves.v4i1.3611
Mewburn, I., Grant, W. J., Suominen, H., & Kizimchuk, S. (2018). A machine learning analysis of the non-academic employment opportunities for Ph.D. graduates in Australia. Higher Education Policy, 33(4), 799–813. https://doi.org/10.1057/s41307-018-0098-4
Muharam, Y. A. (2022, February 17). Evaluation of the competency certification program of the national professional certification board in vocational high school. https://conference.loupiasconference.org/index.php/icogemt2/article/view/288
Ni, Z., & Wang, F. (2022). Quality Assessment of Vocational Education Teaching reform based on Deep learning. Computational and Mathematical Methods in Medicine, 2022, 1–11. https://doi.org/10.1155/2022/1499420
Nurtanto, M., Sofyan, H., Pardjono, P., & Suyitno, S. (2020). Development model for competency improvement and national vocational qualification support frames in Automotive technology. International Journal of Evaluation and Research in Education, 9(1), 168. https://doi.org/10.11591/ijere.v9i1.20447
Rahdiyanta, D., Nurhadiyanto, D., & Munadi, S. (2019). The effects of situational factors in the implementation of Work-Based Learning Model on vocational education in Indonesia. International Journal of Instruction, 12(3), 307–324. https://doi.org/10.29333/iji.2019.12319a
Rodríguez, R. S., Svensson, G., & Wood, G. (2020). Assessing corporate planning of future sustainability initiatives in private healthcare organizations. Evaluation and Program Planning, 83, 101869. https://doi.org/10.1016/j.evalprogplan.2020.101869
Rodríguez-Dorans, E., & Jacobs, P. (2020). Making narrative portraits: a methodological approach to analysing qualitative data. International Journal of Social Research Methodology, 23(6), 611–623. https://doi.org/10.1080/13645579.2020.1719609
Rusmulyani, K., Yudana, I. M., Natajaya, I. N., & Divayana, D. G. H. (2022). E-Evaluation based on CSE-UCLA Model Refers to Glickman Pattern for Evaluating the Leadership Training Program. International Journal of Advanced Computer Science and Applications, 13(5). https://doi.org/10.14569/ijacsa.2022.0130534
Sara, N., Halland, R., Igel, C., & Alstrup, S. (2015). High-School dropout prediction using machine Learning: a Danish large-scale study. The European Symposium on Artificial Neural Networks. https://dblp.uni-trier.de/db/conf/esann/esann2015.html#SaraHIA15
Schwenger, B. (2017). Research on training wheels – embedding academic literacy and numeracy in vocational pedagogy through action research. Educational Action Research, 26(2), 288–300. https://doi.org/10.1080/09650792.2017.1310053
Sen, B., Uçar, E., & Delen, D. (2012). Predicting and analyzing secondary education placement-test scores: A data mining approach. Expert Systems With Applications, 39(10), 9468–9476. https://doi.org/10.1016/j.eswa.2012.02.112
Shippee, N. D., Finch, M., & Wholey, D. R. (2018). Using statewide data on health care quality to assess the effect of a Patient-Centered Medical Home Initiative on quality of care. Population Health Management, 21(2), 148–154. https://doi.org/10.1089/pop.2017.0017
Stofkova, Z., & Sukalova, V. (2020). Sustainable development of human resources in globalization period. Sustainability, 12(18), 7681. https://doi.org/10.3390/su12187681.
Sumbodo, W., Yudiono, H., Salim, & Setiadi, R. (2019). The role of industry partners to improving student competency of vocational high school. Journal of Physics, 1387, 012031. https://doi.org/10.1088/1742-6596/1387/1/012031
Suyasa, P. W. A., & Kurniawan, P. S. (2018). Pemberdayaan Model CSE-UCLA Dalam Pelaksanaan Evaluasi Program Blended Learning di SMA Negeri 1 Ubud. Wacana Akademika. https://doi.org/10.30738/wa.v2i2.2627.
Wahyuni, D. S., Agustini, K., Sindu, I. G. P., & Sugihartini, N. (2020). Analysis on vocational high school teacher competency gaps: implication for VHS teacher training needs. Journal of Physics, 1516(1), 012051. https://doi.org/10.1088/1742-6596/1516/1/012051
Wholey, D. R., White, K., Adair, R., Christianson, J. B., Lee, S., & Elumba, D. (2013). Care guides. Health Care Management Review. https://doi.org/10.1097/hmr.0b013e31825f3df9
Wholey, D. R., Zhu, X., Knoke, D., Shah, P. P., Zellmer-Bruhn, M. E., & Witheridge, T. F. (2012). The teamwork in Assertive Community Treatment (TACT) scale: development and validation. Psychiatric Services, 63(11), 1108–1117. https://doi.org/10.1176/appi.ps.201100338