Article Per Year (5 Year)
p-Index From 2021 - 2026
2.286
P-Index
This Author published in this journals
All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JTERA (Jurnal Teknologi Rekayasa) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Informatik : Jurnal Ilmu Komputer Indonesian Journal of Business Intelligence (IJUBI) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Madaniya Jurnal Polimesin The Indonesian Journal of Computer Science Journal of Islamic Economics Studies and Practices (JIESP).
Khoirunnisa, Hilda
Department Automation And Mechatronic Engineering, Bandung Polytechnic For Manufacturing, Indonesia
Religion Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
PENERAPAN FUZZY LOGIC DALAM SISTEM PEMANTAUAN VITAL SIGN BERBASIS INTERNET OF THINGS Rahmatulloh, Muhammad Rafy; Indroasyoko, Narwikant; Khoirunnisa, Hilda
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4112

Abstract

The development of the Internet of Things (IoT) has brought innovations in healthcare, especially in vital sign monitoring, crucial for detecting physiological changes and supporting disease diagnosis. Outpatient vital sign monitoring is often neglected due to time and equipment constraints. Previous research, such as using Bluetooth technology, showed range limitations, while other solutions couldn't classify patient conditions. This study develops an IoT-based vital sign monitoring device with four parameters: blood pressure, body temperature, heart rate, and oxygen saturation, accessible online. The device uses fuzzy logic to classify patient status. Test results show accuracy rates of 96.4% and 91.3% for blood pressure, 98% for heart rate, 98% for oxygen saturation, and 98% for body temperature readings. Patient classification tests showed 9 out of 10 samples had the same risk output as the NEWS assessment.
PID-controlled active damping to mitigate chatter in lathe machining Sunarya, Adhitya Sumardi; Khoirunnisa, Hilda; Lilansa, Noval; Anggraeni, Pipit; Nugraha, Nurwisma; Mumtaha, Raden Malik Hakim Muslim
Jurnal Polimesin Vol 23, No 4 (2025): August
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v23i4.6418

Abstract

Chatter is a result of undesired vibration in manufacturing that damages product surfaces and reduces production efficiency. Addressing chatter requires enhancing machine-tool dynamic stability, optimizing cutting parameters, and implementing real-time monitoring and control. This study presents a PID-controlled active damping system developed through theoretical analysis, simulation, and experimental testing on LabVIEW and Arduino platforms. Orthogonal turning simulations were conducted with spindle speed of 1000 RPM, feed rate of 0.2 mm/rev, and depth of cut of 1 mm. Vibration sensors enabled rapid chatter detection, and real-time PID adjustments suppressed instability within 0.02 seconds, achieving 98.11% suppression accuracy. Data acquisition was carried out using NI DAQ USB-6218, with Arduino and LabVIEW results showing close agreement, apart from minor deviations due to communication delay. The system improved surface finish, reduced tool wear, and enhanced overall machining performance. These results show the potential of PID-based active damping as an effective solution for real-time chatter suppression and efficiency improvement in lathe machining.
Implementasi Fuzzy Logic pada Sistem Robotik Ball Balancing Table dengan Konfigurasi Ball Joint untuk Stabilitas Dinamis Khoirunnisa, Hilda; Suryatini, Fitria; Pancono, Suharyadi; Al Ghafara, Muhamad; Ramdani, Cepi
Informatik : Jurnal Ilmu Komputer Vol 21 No 1 (2025): April 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i1.11168

Abstract

Penelitian ini bertujuan untuk menerapkan Fuzzy Logic Controller (FLC) pada sistem Ball Balancing Table (BBT) dengan konfigurasi struktur mekanik Ball Joint untuk stabilitas dinamis. Sistem ini dirancang untuk dapat menempatkan bola pada posisi tertentu. Posisi bola dideteksi secara real-time menggunakan panel touchscreen resistif dan sinyal posisi diproses oleh kontroler fuzzy pada NI myRIO, yang kemudian mengendalikan aktuator motor servo untuk menyesuaikan kemiringan permukaan meja. Hasil pengujian menunjukkan bahwa sistem mampu menempatkan bola pada posisi target dengan tingkat akurasi yang baik sebesar 93.63% untuk sumbu X dan 90.41% untuk sumbu Y. Rerata Kesalahan posisi bola pada sumbu X tercatat sebesar 17.33 mm sedangkan pada sumbu Y sebesar 14.55 mm. Untuk waktu respons penempatan bola terhadap titik target, hasil pengujian mencatat waktu tercepat 10.8 detik dan waktu terlama 16.82 detik. Hasil ini menunjukkan bahwa implementasi fuzzy logic dan struktur mekanik Ball Joint menghasilkan sistem kendali yang cukup akurat dan responsif.
Boosting CNN Accuracy for Sundanese Script Recognition through Feature Extraction Techniques Pradana, Musthofa Galih; Khoirunnisa, Hilda
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11332

Abstract

Sundanese script is included in the cultural heritage in Indonesia, especially the culture in West Java. As a society that appreciates and preserves Indonesian culture and art, active participation can be realized through efforts to strengthen and preserve this script, one of which is by utilizing digital media. One of the technology-based digital media that can be used to preserve culture is image detection to make it easier to recognize Sundanese script. One of the models that can be used is the Convolutional Neural Network (CNN) with the MobileNetV2 architecture, with limited resources this architecture is able to produce good detection. This study applies the Convolutional Neural Network (CNN) algorithm with the MobileNetV2 architecture which will be tested with two main test scenarios, namely by applying feature extraction and without using feature extraction. The focus of this study will explore the influence and significance of the influence of feature extraction on the final results of image detection using the Convolutional Neural Network (CNN). The two feature extraction models used are Local Binary Pattern and Gray-Level Co-occurrence Matrix. These two feature extraction models will be tested with Sundanese script image data with data of 2,300 Sundanese script images. The results of this study show that the best results were obtained in the Convolutional Neural Network (CNN) with Gray-Level Co-occurrence Matrix (GLCM) with the best accuracy results at 93.8%. This is because the addition of the Gray-Level Co-occurrence Matrix (GLCM) is able to capture spatial texture statistics such as contrast, homogeneity, entropy, and correlation between pixel pairs. With these results, it can be concluded that in this study feature extraction has an effect and is able to increase the detection accuracy of the Convolutional Neural Network (CNN) model with the MobileNetV2 architecture in Sundanese script image data.
Analisis Performa Algoritma Convolutional Neural Networks Menggunakan Arsitektur LeNet dan VGG16 Pradana, Musthofa Galih; Khoirunnisa, Hilda
Indonesian Journal of Business Intelligence (IJUBI) Vol 6 No 2 (2023): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v6i2.3765

Abstract

Identifying a person's self-identity can be done by recognizing facial images, where faces can often represent a person's identity. Facial identification with technology can benefit the effectiveness efficiency and accuracy of data. This identification process can be used with the help of algorithms that will check digital images with the necessary detection results. One algorithm that can be applied in classifying and detecting gender through facial image algorithms is Convolutional Neural Networks. Convolutional Neural Network algorithms have various architectures that have advantages in each architecture. This study compared the process of identifying a person's face to obtain information in the form of gender. The models compared in this study are the LeNet model and the VGG16 model. The identification and detection process was carried out using 800 photos for data training with gender labeling data and 240 photos for testing data. A comparison of these two models is necessary to get the best final model result. The final results obtained from this study the best accuracy of both architectures was obtained in the VGG16 architecture which reached an average accuracy of 100 in several epochs compared to the VGG16 architecture at 0.925 in the 46th epoch. This is due to a Rectified Linear Unit (ReLU) on the VGG16 architecture which can minimize errors and saturation.
Co-Authors Al Ghafara, Muhamad Anggraeni Mulyadewi Ariantara, Raden Giovanni Aris Budiyarto Bustami Ibrahim Feri Apryandi Fitria Suryatini Hamdan Ali Masduqie, Muhammad Handayani, Mustika Rahmah Heri Setiawan Hilman Mujahid Purnama Indroasyoko, Narwikant Ismail Rokhim Latuheru, Ariel Muhammad Asfari Nashrurrazzaq Muhammad Nursyam Rizal Mulyadewi, Anggraeni Mumtaha, Raden Malik Hakim Muslim Musthofa Galih Pradana Niti Purbayudha, Manida Nugraha, Nurwisma Nur Jamiludin Ramadhan Nur Wisma Nugraha Pancono, Suharyadi Pipit Anggraeni Pipit Anggraeni, Pipit Pipit Angraeni PRASENDA, SENDI DIKA Rahmatulloh, Muhammad Rafy Ramdani, Cepi Razan, Safira Hafizhah Rifa'i, Afaf Fadhil Setyawan Ajie Sukarno Sunarya, Adhitya Sumardi Taqi, Khoutal Theo Kristian