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Feasibility Study on the Implementation of PostureSmart as an Artificial Intelligence-Based Body Posture Analysis System in Education and Sports

Jurnal Panjar: Pengabdian Bidang Pembelajaran · Vol. 6 No. 1 (2026) · hlm. 43–50

DOI
10.15294/panjar.v6i1.62844
ISSN
2809-4778, 2656-2405
Terbit
2026-06-30
Penerbit
Universitas Negeri Semarang
Bahasa
eng

Abstrak

This study aims to develop and evaluate the feasibility of PostureSmart, an Artificial Intelligence (AI) and Computer Vision-based posture analysis system designed to support posture screening and evaluation in the fields of education and sport. The study employs a Research and Development (R&D) approach comprising the stages of requirements analysis, design, system development, expert validation, product revision, and implementation feasibility testing. PostureSmart integrates image capture, body landmark detection, biomechanical parameter analysis, data storage, and digital presentation of results via a web-based platform. Product validation involved three experts comprising specialists in biomechanics, sports coaching, and information technology. Implementation feasibility was subsequently analysed using the TELOS framework, which covers Technical, Economic, Legal, Operational, and Schedule Feasibility. The research results show that PostureSmart achieved an expert validation feasibility rating of 93.0%, categorised as ‘highly feasible’. The biomechanics aspect received the highest score of 94.0%, followed by information technology at 93.0% and sports coaching at 92.0%. The TELOS analysis indicated an implementation feasibility rate of 92.4%, categorised as ‘highly feasible’, with the highest score of 95.0% in the ‘Schedule Feasibility’ category. The results indicate that PostureSmart is well-prepared from technical, economic, legal, operational and implementation perspectives. The system has the potential to serve as a technology that supports more objective, efficient and integrated posture assessment in the contexts of education and sport. Further research is required to test the system’s accuracy and effectiveness on a larger and more diverse sample.

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  • State University of Semarang
  • State University of Jakarta
  • Universitas Negeri Surabaya
  • Universitas Nahdlatul Ulama Sunan Giri
  • Universiti Teknologi MARA
  • Shanghai University of Sport
  • Indonesia University of Education
  • Afiliasi tidak diketahui
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  • Afiliasi tidak diketahui
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Rekan penulisOrganisasiArtikel bersama
Cahyo YuwonoState University of Semarang15
Dicky Budhi SetyawanState University of Semarang7
Mahenderan AppukuttyUniversiti Teknologi MARA5
Mohamad Da’iUniversitas Nahdlatul Ulama Sunan Giri3
Bhayu BilliandriState University of Semarang2
Afdol FebriansyahShanghai University of Sport2
Dewangga YudhistiraUniversitas Negeri Surabaya2
Mohamad Miftahul UlumState University of Semarang1
Agus Budi RaharjoState University of Semarang1
Agung WahyudiState University of Semarang1
Fery DarmantoState University of Semarang1
Bayu Aji SantosoIndonesia University of Education1
SupriyonoState University of Semarang1
Pastika Candra NurjanahState University of Semarang1
Ipang SetiawanState University of Semarang1
Agus PujiantoState University of Semarang1
Faizal Anwar Al MukharomState University of Semarang1
Dwi Tiga PutriState University of Semarang1
Donny Wira Yudha KusumaState University of Semarang1
Muhammad Ardi PratamaState University of Semarang1
Faradz JiddanState University of Semarang1
Lina MeilaniState University of Semarang1
Rafi Tri IndarwanState University of Semarang1
Endien Miswangga Bena AgataState University of Semarang1
Aisyah Dini NuraryatiState University of Semarang1
Firman Said Dwi ArdianState University of Semarang1
Krisna AngganaState University of Semarang1
Muhammad Haikal IlmaState University of Semarang1
Diky RomadhonState University of Semarang1
Dian Eka WulandariState University of Semarang1
Dema SetiawanState University of Semarang1
Dian Ekavianti FefantAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/journals/panjar/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en">Feasibility Study on the Implementation of PostureSmart as an Artificial Intelligence-Based Body Posture Analysis System in Education and Sports</dc:title>
	<dc:creator xml:lang="en">Adi S</dc:creator>
	<dc:creator xml:lang="en">Tommy Soenyoto</dc:creator>
	<dc:creator xml:lang="en">Sri Indah Ihsani</dc:creator>
	<dc:creator xml:lang="en">Laily Mita Andriana</dc:creator>
	<dc:creator xml:lang="en">Made Bang Redy Utama</dc:creator>
	<dc:creator xml:lang="en">Hilmy Aliriad</dc:creator>
	<dc:creator xml:lang="en">Afriana, Erika</dc:creator>
	<dc:creator xml:lang="en">Karina Permata Andhini</dc:creator>
	<dc:subject xml:lang="en">Artificial Intelligence</dc:subject>
	<dc:subject xml:lang="en">Computer Vision</dc:subject>
	<dc:subject xml:lang="en">posture analysis</dc:subject>
	<dc:subject xml:lang="en">biomechanics</dc:subject>
	<dc:subject xml:lang="en">PostureSmart</dc:subject>
	<dc:subject xml:lang="en">TELOS</dc:subject>
	<dc:description xml:lang="en">This study aims to develop and evaluate the feasibility of PostureSmart, an Artificial Intelligence (AI) and Computer Vision-based posture analysis system designed to support posture screening and evaluation in the fields of education and sport. The study employs a Research and Development (R&amp;amp;D) approach comprising the stages of requirements analysis, design, system development, expert validation, product revision, and implementation feasibility testing. PostureSmart integrates image capture, body landmark detection, biomechanical parameter analysis, data storage, and digital presentation of results via a web-based platform. Product validation involved three experts comprising specialists in biomechanics, sports coaching, and information technology. Implementation feasibility was subsequently analysed using the TELOS framework, which covers Technical, Economic, Legal, Operational, and Schedule Feasibility. The research results show that PostureSmart achieved an expert validation feasibility rating of 93.0%, categorised as ‘highly feasible’. The biomechanics aspect received the highest score of 94.0%, followed by information technology at 93.0% and sports coaching at 92.0%. The TELOS analysis indicated an implementation feasibility rate of 92.4%, categorised as ‘highly feasible’, with the highest score of 95.0% in the ‘Schedule Feasibility’ category. The results indicate that PostureSmart is well-prepared from technical, economic, legal, operational and implementation perspectives. The system has the potential to serve as a technology that supports more objective, efficient and integrated posture assessment in the contexts of education and sport. Further research is required to test the system’s accuracy and effectiveness on a larger and more diverse sample.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2026-06-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/journals/panjar/article/view/62844</dc:identifier>
	<dc:identifier>10.15294/panjar.v6i1.62844</dc:identifier>
	<dc:source xml:lang="en">Jurnal Panjar: Pengabdian Bidang Pembelajaran; Vol. 6 No. 1 (2026); 43-50</dc:source>
	<dc:source>2809-4778</dc:source>
	<dc:source>2656-2405</dc:source>
	<dc:source>10.15294/panjar.v6i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/panjar/article/view/62844/11379</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Jurnal Panjar: Pengabdian Bidang Pembelajaran</dc:rights>
</oai_dc:dc>