Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

18.246

P-Index

This Author published in this journals

All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal INKOM TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal technoscientia Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control IJID (International Journal on Informatics for Development) Indonesian Journal of Electrical Engineering and Computer Science JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Teknik Informatika (JUTIF) Mechanical Engineering for Society and Industry Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika

Utaminingrum, Fitri

Fakultas Ilmu Komputer, Universitas Brawijaya

Author-ID : 627297

Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation

Published : 210 Documents Claim Missing Document

Claim Missing Document

Articles

Title

Voice Recognition to Classify “Buka” and “Tutup” Sound to Open and Closes Door Using Mel Frequency Cepstral Coefficients (MFCC) and Convolutional Neural Network (CNN) Laksono, Blessius Sheldo Putra; Syaifuddin, Tio; Utaminingrum, Fitri
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491579

The consequences of the coronavirus called COVID-19 have been really impactful on society. Many things need to be changed in order to survive this pandemic. People have to avoid physical contact to minimize the probability of getting caught by other people who have been infected. A doorknob has a really big potential to be the medium to spread the virus because the same surface is used by several people. Speech recognition can be used to solve this problem. In this study, Mel Frequency Cepstral Coefficients (MFCC) and Convolutional Neural Network (CNN) are going to be used as the extraction feature and classification method, respectively. We classify the sound signal into two classes (“buka” and “tutup”). People who want to open or close the door just need to say a specific command. This can be helpful to minimize the risk of COVID transmission. A CNN model is developed and fed with an audio file from a curated dataset for training and testing. With this system, we have successfully trained the model with an accuracy of 89% using an epoch of 50 and batch size of 32 as the parameters with a dataset distribution of 8:2 for training and validation. We believe this study will be influential in developing automated door systems using speech recognition, especially in the Indonesian language.

Personality Analysis through Handwriting Detection Using Android Based Mobile Device Wijaya, Waskitha; Tolle, Herman; Utaminingrum3, Fitri
Journal of Information Technology and Computer Science Vol. 2 No. 2: November 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Graphology is one of the psychology disciplines which aims to study the personality traits of individuals through interpretation of handwriting. We can get information of oneâ€™s personality through graphology. In addition, by using android based mobile device, graphology analysis could show oneâ€™s personality faster. This study was conducted by taking 42 samples of handwriting from different backgrounds. The feature used in this study was handwriting margin. Besides, Support Vector Machine method was employed to classify the result feature from extraction process. The result of this study showed the accurate average of the application reached 82.738%.

The Connectivity Between Leap Motion And Android Smartphone For Augmented Reality (AR)-Based Gamelan Permana, Frihandhika; Tolle, Herman; Utaminingrum, Fitri; Dermawi, Rizdania
Journal of Information Technology and Computer Science Vol. 3 No. 2: November 2018
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

The smartphone development today makes the gadget not only used as a communication tool but also as an entertainment tool such as to play games and play music. The development of the smartphone also supports many technologies that can be run on the smartphone itself, such as Augmented Reality (AR), for example. There are some studies evaluated the AR application combined with Leap Motion, but those studies were using the SDK alpha of the Leap Motion Corp. that is now no longer accessible for the developers to use. This research is meant to overcome such a problem. The method proposed in this study is a technique to connect the Leap Motion with Android for Augmented Reality application. This paper also evaluates the technique used to connect the AR technology to Leap Motion so it can be a visual instrument simulation, which applied to the Gamelan traditional music instrument. The experiments resulted in the accuracy rate of the application of 96.43% for right-hand movement and 97.86% for the left-hand motion. The high accuracy result obtained in the research can be a promising result for the future research.

Clustering of Human Hand on Depth Image using DBSCAN Method Yohannes, Ervin; Utaminingrum, Fitri; Shih, Timothy K.
Journal of Information Technology and Computer Science Vol. 4 No. 2: September 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

In recent years, depth images are popular research in imageprocessing, especially in clustering field. The depth image can captureby depth cameras such as Kinect, Intel Real Sense, Leap Motion, and etc.Many objects and methods can be implemented in clustering field andissues. One of popular object is human hand since has many functionsand important parts of human body for daily routines. Besides, theclustering method has been developed for any goal and even combinewith another method. One of clustering method is Density-Based SpatialClustering of Applications with Noise (DBSCAN) which automaticclustering method consists of minimum points and epsilon. Define theepsilon in DBSCAN is important thing since the result depends on those.We want to look for the best epsilon for clustering human hand in thedepth images. We selected the epsilon from 5 until 100 for getting thebest clustering results. Moreover, those epsilons will be testing in threedistance to get accurate results.

K-Value Effect for Detecting Stairs Descent using Combination GLCM and KNN Satria Bahari Johan, Ahmad Wali; Utaminingrum, Fitri; Budi, Agung Setia
Journal of Information Technology and Computer Science Vol. 5 No. 1: April 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

This study aims to analyze the k-value on K nearest neighbor classification. k-value is the distance used to find the closest data to label the class from the testing data. Each k-value can produce a different class label against the same testing data. The variants of k-value that we use are k=3, k=5 and k=7 to find the best k-value. There are 2 classes that are used in this research. Both classes are stairs descent and floor classes. The gray level co-occurrence matrix method is used to extract features. The data we use comes from videos obtained from the camera on the smart wheelchair taken by the frame. Refer to the results of our tests, the best k-value is obtained when using k=7 and angle 0Â° with accuracy is 92.5%. The stairs descent detection system will be implemented in a smart wheelchair

Road Damaged Analysis (RODA) using Built-in Accelerometer Sensor in Smartphone Huda, Choirul; Tolle, Herman; Utaminingrum, Fitri
Journal of Information Technology and Computer Science Vol. 5 No. 2: August 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Road damage produces serious problems for the driver such as travel efficiency, vehicle value, and even driver safety. In some cases, road damage causes accidents and ends in death. Currently, road damage detection research extends to grow and present various approaches such as the implementation of an accelerometer sensor. However, the implementations face lacks of accuracy since unable to work in real-time and poor implementation. In the end, the system inadequate to identify damaged roads effectively. Therefore, a comprehensive study was proposed. Firstly, data collection is conducted by applying a low-pass filter to obtain accurate data. The next step is estimating the range value of the accelerometer graph. In the final step, the classification is performed to identify road conditions into smooth, medium and poor. Based on some experiments that have been done, the proposed method accurately recognizes road conditions by 86.67%.

Application of YOLOv5 and EasyOCR for Odd-Even Detection and Recognition on License Plates Candra, Alvin; Utaminingrum, Fitri; Tolle, Herman
Journal of Information Technology and Computer Science Vol. 10 No. 2: August 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025102553

The increase in the number of vehicles in Indonesia is directly correlated with the escalation in traffic congestion. In addition to congestion, an indirect repercussion of vehicle proliferation is the rise in traffic accidents. The government has undertaken various measures to alleviate traffic congestion, one of which is the implementation of the odd-even system. Automatic License Plate Recognition (ALPR) can be employed to facilitate the identification of odd-even plate numbers. In this study, ALPR employs machine learning methods (K-Nearest Neighbors and Support Vector Machine) as well as deep learning techniques (YOLOv5). EasyOCR is utilized for character recognition on the license plates. Based on the test results, YOLOv5 emerges as the optimal approach for license plate detection. EasyOCR demonstrates proficient character recognition for license plates at distances less than 2 meters.

Co-Authors Abadi, Dendy Satria Abiyyu Herwanto Achmad Dinda Basofi Sudirman Achmad Jafar Al Kadafi Adam Ibrahim, Muhammad Adharul Muttaqin Adinugroho, Sigit Aditia Reza Nugraha Adiyanto Kusuma Nuhgraha, Nur Afdy Clinton Afrizal Rivaldi, Afrizal Agung Setia Budi Agung Setia Budi Agung Setia Budi, Agung Setia Agus Wahyu Widodo Ahmad Wali Satria Bahari Johan Ahmad Wildan Farras Mumtaz Ainandafiq Muhammad Alqadri Akbar Dicky Purwanto Akbar Wira Bramantya Akbar, Muhammad Danar Al Amin, Nisrina Fairuz Hafizhah Al Huda, Fais Alfan Rafi'uddin Ardhani Alfianto Palebangan Alhamdi, Achmad Fahri Aliffandi Purnama Putra Alrynto Alrynto Alvin Evaldo Darmawan Amalia Septi Mulyani Amaliah, Ichlasuning Diah Andhika, Maulana Andika Bayhaki Al Rasyid Syah Andika Kalvin Simarmata Andrika Wahyu Wicaksono Anugrah Zeputra Arthur Ahmad Fauzi Asep Ranta Munajat Asfar Triyadi Audrey Athallah Asyam Fauzan Aufa Nizar Faiz Auliya Firdaus Awalina, Aisyah Bagas Nur Rahman Bagus Septian Aditya Wijayanto Barlian Henryranu Prasetio Beryl Labique Ahmadie Blessius Sheldo Putra Laksono Budi Atmoko Budiman, Ibrahim Burhan, M.Shochibul Cahyo, Muhammad Pandu Dwi Candra, Alvin Choirul Huda Constantius Leonardo Pratama Dahnial Syauqy Danudoro, Kevin Daris Muhammad Yafi Desy Marinda Oktavia Sitinjak Dewi Amalia Dharmatirta, Brian Aditya Dimas Rizqi Firmansyah Dony Satrio Wibowo Duwi Purnama Sidik Dzakwan Daffa Ramdhana Edita Rosana Widasari, Edita Rosana Eko Sakti Pramukantoro, Eko Sakti Eko Setiawan Eko Setiawan Enny Trisnawati, Enny Ervin Yohannes Ester Nadya Fiorentina Lumban Gaol Faris Chandra Febrianto Farrassy, Muhtady Fatwa Ramdani, Fatwa Fernando, Leo Luis Figo Ramadhan Hendri Fikri, Aqil Dzakwanul Firdansyah Tegar Akmalillah, Achmad Fitra Abdurrachman Bachtiar Fitrahadi Surya Dharma Fitria Indriani Fitriyah, Hurriyatul Fitriyani, Rahma Nur Gabe Siringoringo Gagana Ghifary Ilham Gembong Edhi Setyawan Gunawan Guruh Adi Purnomo Haikal, M. Fikri Hashfi Firjatullah, Ilmam Hassadiqin, Hasbi Hendry Y. Nanlohy Herdikaputra, Daffa Aprilian Herman Tolle Hernanda Agung Saputra Hilman Syihan Ghifari Hilmy Bahy Hakim Hisdianton, Oktavian Huda Ahmad Hidayatullah Hurmuzi, Abdan Idza Hurriyatul Fitriyah Hurriyatul Fitriyah, Hurriyatul Ichsan Ali Rachimi Ida Yusnilawati Ikhsan Rahmad Ilham Imam Cholissodin Imam Faris Intan Fatmawati Irnayanti Dwi Kusuma Irsal, Riyandi Banovbi Putera Issa Arwani Jawahir, Asma Kamilah Nur Joan Chandra Kustijono Juniman Arief Kabisat, Aldiansyah Satrio Kelvin Himawan Eka Maulana Kezia Amelia Putri Kirana Sekar Ayu Kohichi Ogata, Kohichi Krisna Pinasthika Lailil Muflikhah Laksono Trisnantoro Laksono, Blessius Sheldo Putra Larasati, Anindya Zulva Leina Alimi Zain Lilo Nofrizal Akbar Linda Silvya Putri Lita Nur Fitriani LUTHFATUN NISA M. Ali Fauzi M. Fiqhi Hidayatulah M.Shochibul Burhan Mardyantoro, Samuel Sahat Marianingsih, susi Marsha Nur Shafira Masyita Lionirahmada Maulana Yusuf Meidiana Adinda Prasanty Mela Tri Audina Misran Misran Mochammad Bustanul Ilmi Mochammad Hannats Hanafi Ichsan Mohammad Andy Purwanto Mohammad Isya Alfian Mohammad Sezar Nusti Ilhami Muchlas Muchlas Muchlas Muchlas Mufita, Aulia Riza Muhadzdzib, Naufal Muhamad Fauzan Alfiandi Muhammad Amin Nurdin Muhammad Arga Farrel Arkaan Muhammad Fadhel Haidar Muhammad Hafid Khoirul Muhammad Ibrahim Kumail Muhammad Nazrenda Ramadhan Muhammad Rafi Zaman Muhammad Raihan Wardana Budiarto Muhammad Rizky Rais Muhammad Tri Buwana Zulfikar Ardi Muhammad Wafi Muzammilatul Jamiilah Neldi, Taufik Nico Dian Nugraha Niko Aji Nugroho Noza Trisnasari Alqoria Nugraheny Wahyu Try Nyoman Kresna Aditya Wiraatmaja Olivia Rumiris Sitanggang Onky Soerya Nugroho Utomo Paulus Ojak Parasian Permana, Frihandhika Prasetio, Barlian Prasetyo, Fahrudin Pratama, Aimar Abimayu Pratama, Wildan Bagus Priyanpadma, Sulthon Purboningrum, Fadhila Putera, Muhammad Reza Dahri Putra Pandu Adikara Putra, Firnanda Al Islama Achyunda Putra, Reza Qonita Luthfiyani Qurrotul A'yun Rachmad Jibril Al Kautsar Radithya, Muhammad Fathi Rahma Tiara Puteri Rahmatul Bijak Nur Kholis Rahmawati, Athirah Naura Rakhmadhany Primananda, Rakhmadhany Rakhmadina Noviyanti, Rakhmadina Rama Aprianto, Andika Ramadhani, Roihaan Randy Cahya Wihandika Randy Cahya Wihandika Rayhan Rasyad, Muhammad Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renaldi Primaswara Praetya Renita Leluxy Sofiana Rhaka Gemilang Sentosa Ringga Aulia Primahayu Riyandi Banovbi Putera Irsal Rizal Maulana Rizal Maulana, Rizal Rizdania, Rizdania Rizka Husnun Zakiyyah Rizky Haris Risaldi Rizky Teguh Nursetyawan Rizky Yuztiawan, Fachrie Robbani, Ihwanudien Hasan Rochmawanti, Ovy Samuel Andika Sanjaya, Muhamad Aditya Sasongko, Listyawan Dwi Shaleh, Achmad Rizqi Ilham Shih, Timothy K. Sigit Adinugroho Sihite, Chandra Ferdinan Simangunsong, Bryan Nicholas Josephin Hotlando Siswanti Slamet Arifmawan Sri Mayena Surga, Itsar Irsyada Syahrul Yoga Pradana Syaifuddin, Tio Tan, Evan Tiara Sri Mulati Tibyani Tibyani Tibyani Tobias Sion Julian Tsani, Farid Nafis Versa Christian Wijaya Vikorian, Eldad Virza Audy Ervanda Wahyu Adi Prijono Wayan Firdaus Mahmudy Widasari, Edita Rosana Wijaya Kurniawan Wijaya, Waskitha William Hutamaputra Willy Andika Putra Wisik Dewa Maulana Yazid Basthomi Yoke Kusuma Arbawa Yongki Pratama Yuita Arum Sari Yuita Arum Sari Yuita Arum Sari Zamaliq Zamaliq Zhuliand Rachman Zulfina Kharisma Frimananda `Ilmi, Aqna

Title Search

Found 7 Documents Search Journal : journal of information technology and computer science

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 7 Documents
Search
Journal : journal of information technology and computer science