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All Journal Jurnal Teknologi dan Manajemen Informatika TEKNOLOGI: Jurnal Ilmiah Sistem Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology Teknika: Engineering and Sains Journal Knowledge Engineering and Data Science JICTE (Journal of Information and Computer Technology Education) SMARTICS Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Konvergensi Jurnal Sisfokom (Sistem Informasi dan Komputer) INTECOMS: Journal of Information Technology and Computer Science Antivirus : Jurnal Ilmiah Teknik Informatika Journal of Information System,Graphics, Hospitality and Technology Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Teknika Teknika Journal of Electrical Engineering and Computer (JEECOM) Best : Journal of Applied Electrical, Science and Technology Insyst : Journal of Intelligent System and Computation J-Intech (Journal of Information and Technology) Joutica : Journal of Informatic Unisla Jurnal Nasional Teknik Elektro dan Teknologi Informasi JOINCS (Journal of Informatics, Network, and Computer Science) Insand Comtech : Information Science and Computer Technology Journal Jurnal Indonesia Sosial Teknologi JEECS (Journal of Electrical Engineering and Computer Sciences) Eksplorasi Teknologi Enterprise & Sistem Informasi (EKSTENSI) EduTech Journal
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Journal : J-Intech (Journal of Information and Technology)

Pengukuran Nilai Keseimbangan Gerakan Manusia terhadap Dataset Tari Remo dengan High-level Matrix/Array Language Salim, Shierly Kartika; Zaman, Lukman; Setyati, Endang
J-INTECH (Journal of Information and Technology) Vol 11 No 2 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i2.829

Abstract

Remo Dance is one of Indonesia’s traditional dance that originated from East Java and need to be preserved. The preservation act from collaboration of the Goventment and the Society started with a mass Remo Dance at Surabaya city on the year of 2022 that successfully granted a MURI record. This research is meant to support all the effort by calculating balance of the movements as one of the aspect of biomechanics. Biomechanics it self is a branch of study that learns about movement mechanism of living organism. The calculation of balance as an ability to keep a posistion on the change of movements is aim to analyze which movements has the most difficulty in balance and which one is the most stable from the chunk of motion capture data. Computation is done with high-level matrix/array language and the data form is a biovision hierarchy file (BVH). The Visualization of data shows that ‘ucek-ucek’ motion is the most stable movements, while 360 degree spin motion is a difficult movements and require great balance.
Identifikasi Viseme Untuk Fonem Bahasa Madura Berbasis Clustering Berdasarkan Facial Landmark Point Andriyanto, Pyepit Rinekso; San, Joan; Setyati, Endang
J-INTECH (Journal of Information and Technology) Vol 11 No 1 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i1.835

Abstract

The most effective form of language in communicating is spoken or spoken language. When speaking humans will move their mouth and lips to say certain words. This mouth and lip movement model describes a viseme (visual-phonem), namely a group of phonemes that have a visual or almost the same appearance. Madurese language is a unique language and has certain characteristics. In addition to having a language level, Madurese has aspirated phonemes or exhaled word pronunciations such as: /bh/, /dh/, /Dh/, /gh/ and /jh/ which do not exist in other languages. This research discusses the identification of viseme classes for Madurese phonemes based on clustering based on facial landmark points. Of the 47 Madurese language phonemes, 9 Madurese language visemes were obtained from the K-Means clustering process. The clustering process uses feature extraction based on facial landmark points so that the distance calculation for each feature is obtained. The features used are geometric features. The Madurese viseme model is used to build 2D mouth animations in uttering Madurese words or sentences based on input in the form of text. The benefit of this research is for learning purposes in pronouncing Madurese words or sentences, because Madurese has different writing and pronunciation.