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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal INKOM TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal technoscientia Jurnal Mahasiswa TEUB 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

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 : 193 Documents Claim Missing Document

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Sistem Pelacakan Pemandu untuk Kursi Roda Pintar Menggunakan Efficient Convolution Operator dan Weighted-Thresholded Histogram Equalization Kabisat, Aldiansyah Satrio; Utaminingrum, Fitri; Pramukantoro, Eko Sakti
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 9 No 3 (2025): Maret 2025
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Kursi roda merupakan alat bantu mobilitas bagi penyandang disabilitas. Namun, jika seseorang memiliki disabilitas ganda kaki dan tangan, diperlukan bantuan seorang pemandu untuk menggerakkan kursi roda. Hal ini dapat menyebabkan masalah apabila pengguna kursi roda memiliki berat badan tinggi yang dapat berakibat pemandu kesulitan memandu dikarenakan kesulitan mendorong akibat beban yang berat. Sistem pelacakan pemandu merupakan salah satu solusi navigasi pada kursi roda pintar untuk mendukung mobilitas penyandang disabilitas ganda yang memungkinkan kursi roda dapat dituntun oleh seorang pemandu tanpa perlu mendorong kursi roda. Penelitian ini mengimplementasikan sistem pelacakan berbasis algoritma Efficient Convolution Operator (ECO) dan Weighted-Thresholded Histogram Equalization (WTHE). Penelitian mengujikan sistem dalam berbagai interferensi seperti objek terhalangi, perubahan penampilan, pencahayaan rendah, dan objek serupa. Hasil evaluasi menunjukkan sistem mampu melacak pemandu secara akurat dan robust. WTHE dengan parameter root 0.75, value 0.75, dan lower 0 mampu meningkatkan performa dari ECO pada metrik precision dari 0.4328 menjadi 0.4398, normalized precision dari 0.7645 menjadi 0.7678, dan failure rate dari 1 menjadi 0. Meskipun demikian, pada metrik success rate, nilai metrik turun dari 0.7302 menjadi 0.7148. Sistem yang diimplementasikan menggunakan hardware NUC NUC8i3BEH mencatatkan kecepatan rata-rata 25 FPS yang menunjukkan sistem dapat dijalankan secara real-time pada perangkat keras yang relatif murah.

Deteksi Pergerakan Arah Kepala Minim Pencahayaan Menggunakan CLAHE dan YOLOv10N Pada Kursi Roda Pintar Putra, Reza; Utaminingrum, Fitri
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 9 No 3 (2025): Maret 2025
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Penyandang disabilitas khususnya individu dengan keterbatasan fisik, sering kali menghadapi tantangan dalam melakukan mobilitas sehari-hari. Kursi roda pintar hadir sebagai solusi guna mendukung mobilitas secara mandiri tanpa ketergantungan pada alat bantu konvensional seperti joystick pada kursi roda atau bantuan fisik lainnya. Penelitian yang dilakukan bertujuan untuk mengembangkan sistem deteksi peregrakan arah kepala berbasis YOLOv10N yang diimplementasikan pada kursi roda pintar guna mendukung navigasi secara real-time, terutama dalam kondisi minim pencahayaan. CLAHE (Contrast Limited Adaptive Histogram Equalization) merupakan metode yang diterapkan sebagai metode pre-processing pada dataset pelatihan untuk meningkatkan kualitas citra, sehingga memungkinkan proses pendeteksian pergerakan arah kepala pengguna menjadi lebih akurat, terutama dalam lingkungan dengan kondisi minim pencahayaan. Hasil pengujian yang dilakukan menunjukkan bahwasanya penerapan CLAHE mampu meningkatkan performa model secara signifikan, dengan peningkatan nilai Macro Average F1-Score sebesar 34,72% jika dibandingkan dengan model tanpa penerapan CLAHE. Teknik peningkatan citra seperti CLAHE dirasa penting guna meningkatkan kehandalan sistem deteksi dalam berbagai lingkungan dengan kondisi pencahayaan yang beragam, sehingga mampu memastikan sistem yang dikembangkan dapat berfungsi secara optimal.

Implementasi Mobilevit-S Untuk Deteksi Permukaan Jalan Berbasis Jetson Nano Pada Kursi Roda Pintar Surga, Itsar Irsyada; Utaminingrum, Fitri
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 9 No 4 (2025): April 2025
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Pada penelitian ini, dikembangkan sistem kursi roda pintar yang mampu mendeteksi jenis permukaan jalan menggunakan Mobile Vision Transformer (MobileViT), yang diimplementasikan pada Jetson Nano sebagai unit pemrosesan utama. Sistem ini dirancang untuk membantu penyandang disabilitas fisik dalam meningkatkan keamanan dan kenyamanan mobilitas, khususnya di lingkungan dengan variasi permukaan jalan seperti lantai, paving, bump, dan tangga. MobileViT dipilih karena kemampuannya yang unggul dalam pengenalan pola visual dengan efisiensi komputasi tinggi. Data pelatihan terdiri dari 3.352 gambar permukaan jalan yang mencakup empat kelas utama. Selain itu, sistem dilengkapi dengan fitur pengaturan kecepatan motor otomatis berdasarkan hasil deteksi jenis permukaan jalan. Hasil pengujian menunjukkan bahwa MobileViT-S berhasil mendeteksi permukaan jalan dengan akurasi tinggi mencapai 97% dan rata-rata waktu komputasi 0,0854 detik per frame. Sistem ini diharapkan menjadi solusi inovatif yang efisien dan terjangkau untuk meningkatkan kemandirian pengguna kursi roda pintar

A Review of the artificial neural network’s roles in alternative fuels: Optimization, prediction, and future prospects Nanlohy, Hendry Y.; Marianingsih, Susi; Utaminingrum, Fitri
Mechanical Engineering for Society and Industry Vol 4 No 3 (2024): Special Issue on Technology Update 2024
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/mesi.12742

Artificial Neural Networks (ANN) are increasingly employed in alternative fuels to enhance efficiency and mitigate environmental impacts. This article comprehensively reviews the application of ANNs in modeling, optimizing, and predicting the properties of various alternative fuels. ANNs excel at capturing the complex non-linear relationships inherent in these fuels' physicochemical properties and combustion processes, which can be challenging to forecast using traditional mathematical models. By leveraging ANNs, combustion parameters can be optimized, thereby improving fuel efficiency, reducing exhaust emissions, and enhancing overall engine performance. Additionally, this research explores the effective use of ANNs in forecasting engine performance and emissions for alternative fuels, while also addressing key challenges, including the need for high-quality data and the optimization of algorithms for better accuracy. Additionally, the article considers the future potential of ANNs in supporting sustainable energy development and facilitating the transition to a green fuel economy. With advancements in computing technology, ANNs are anticipated to remain a vital instrument in the progression of alternative fuel research and its associated applications.

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%.

Handwriting Arabic Character Recognition Using Features Combination Qomariyah, Fitriyatul; Utaminingrum, Fitri; Muchlas, Muchlas
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.2360

The recognition of Arabic handwriting is a challenging problem to solve. The similarity among the fonts appears as a problem in the recognition processing. Various styles, shapes, and sizes which are personal and different across individuals make the Arabic handwriting recognition process even harder. In this paper, the data used are Arabic handwritten images with 101 sample characters, each of which is written by 15 different handwritten characters (total sample 101x15) with the same size (81x81 pixels). A well-chosen feature is crucial for making good recognition results. In this study, the researcher proposed a method of new features extraction to recognize Arabic handwriting. The features extraction was done by grabbing the value of similar features among various types of font writing, to be used as a new feature of the font. Then, City Block was used to compare the obtained feature to other features of the sample for classification. The Average accuracy value obtained in this study was up to 82%.

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 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 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 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 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 Fitra Abdurrachman Bachtiar Fitrahadi Surya Dharma Fitria Indriani Fitriyah, Hurriyatul Fitriyani, Rahma Nur Gabe Siringoringo Gagana Ghifary Ilham Gembong Edhi Setyawan Guruh Adi Purnomo Haikal, M. Fikri Hassadiqin, Hasbi Hendry Y. Nanlohy Herman Tolle Hernanda Agung Saputra Hilman Syihan Ghifari Hilmy Bahy Hakim Hisdianton, Oktavian Huda Ahmad Hidayatullah Hurmuzi, Abdan Idza Hurriyatul Fitriyah 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 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 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 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 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 Rahma Tiara Puteri Rahmatul Bijak Nur Kholis Rahmawati, Athirah Naura Rakhmadina Noviyanti, Rakhmadina Ramadhani, Roihaan Randy Cahya Wihandika Randy Cahya Wihandika 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 Sasongko, Listyawan Dwi Shaleh, Achmad Rizqi Ilham Shih, Timothy K. Sigit Adinugroho Simangunsong, Bryan Nicholas Josephin Hotlando Siswanti Slamet Arifmawan Sri Mayena Surga, Itsar Irsyada Syahrul Yoga Pradana Syaifuddin, Tio 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

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