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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JETT (Jurnal Elektro dan Telekomunikasi Terapan) IT JOURNAL RESEARCH AND DEVELOPMENT TECHNO-SOCIO EKONOMIKA Jurnal Nasional Teknik Elektro dan Teknologi Informasi eProceedings of Applied Science eProceedings of Engineering Jurnal Rekayasa elektrika Jurnal INFOTEL Jurnal Hukum, Administrasi Publik dan Negara Proceeding of Community Service and Engagement
Suci Aulia
Telkom Univeristy
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : Jurnal INFOTEL

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Human height and weight classification based on footprint using gabor wavelet and K-NN methods Ryan Bagus Wicaksono; Suci Aulia; Sugondo Hadiyoso; Bambang Hidayat
JURNAL INFOTEL Vol 14 No 2 (2022): May 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i2.728

Abstract

Height and weight are parameters to identify a person, especially for a forensic. To identify height and weight is usually done manually. In addition to manually using height measuring devices and scales, you can also use information related to the foot length. There is a relationship between height and foot length can be expressed in the correlation coefficient (r) as same as for weight. Therefore, in this study, a system for measuring human height and weight based on images of the footprint is implemented on Android. The methods used in this study are Gabor Wavelet and k-Nearest Neighbor (k-NN). The simulation results generate the best accuracy of 75%. The system can also used to categorize the ideal body level according to the Body Mass Index (BMI). The system is able to process images with an average computation time of 8.92 seconds.
Co-Authors Aaron Abel Abraham Caesar Yanuar Putra Adri Achmad Farhan Agus Gunarso Alvinas Deva Sih Illahi Alya Khalisa Nadira Amri Khurniawan Anatasya Bella Andik Wijanarko Angga Rusdinar Ardyandrea Erstya Surya Arif Setiawan Arif Setiawan Asep Mulyana ATIK NOVIANTI Audry Stevany Aulia Ayu Dyah Aulia Ayu Dyah Lestari Aulya Ellanda Bagus Budhi L. Bambang Hidayat Bayuaji Kurniadhani Burhanuddin Burhanuddin Burhanuddin D. Dadan Nur Ramadan Dadan Nur Ramadhan Della Oktriani Denny Darlis Didin Yulian Dimitri Mahayana Diovani Estidia Akbar Dwi Nuha Nabilah Efri Suhartono Erizka Banuwati Candrasari Erty Kasdiantika Fony Ferliana Widianingrum Galuh Laksmita Ranggi Gelar Budiman Grislend Gloria Natalies Hafiddudin Hafiddudin Hafidudin Hafiidh As Syahidulhaq Hafiz Adriansyah Handoko Supeno Hengki Setiadi Indrarini Dyah Irawati Inung Wijayanto Jean Pierre Uwiringiyimana Khairunnisa Alfiyanti Suharja Kusumawardhani, Eka Ledya Novamizanti Lestari Lestari M. Dyovan Uidy Okta Meidi Mahendra Rahmatullah Melina Melina Muhammad Alfachri Akbar Muhammad Arly Gunawan Muhammad Biyan Priatama Muhammad Iqbal Muhammad Iqbal Muhammad Obi Nugraha Muhammad Obi Nugraha Muhammad Panji Kusuma Praja Muhammad Rafki Nur Ramadhani Nuril Amri Ependi Nurmala Sari Patricia Lovenia Garcia Raditiana Patmasari Rahmat Sopian Rajali Ginting Ratri Dwi Atmaja Raymond Y. Purba Reivind P. Persada Restu Wardani Ridha Muldina Negara Rita Magdalena Rita Purnamasari Rizky Edi Saputra Rudy Gunawan Ryan Bagus Wicaksana Ryan Bagus Wicaksono Ryandhika Gumelar Siti Nurlaila Siti Syahnah Siti Syahnah Syahrial Sri Dewi Sartika Sugondo Hadiyoso Syahban Rangkuti Syahrial Thoriq Dharmawan Unang Sunarya Viona Apryaleva Yafis Sukma Kurniawan YULI SUN HARIYANI Yuyun Siti R. YUYUN SITI ROHMAH