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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Teknik Elektro Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Panrita Abdi - Jurnal Pengabdian pada Masyarakat JIKO (Jurnal Informatika dan Komputer) Techne : Jurnal Ilmiah Elektroteknika JMM (Jurnal Masyarakat Mandiri) JUTEI (Jurnal Terapan Teknologi Informasi) Indonesian Journal of electronics, electromedical engineering, and medical informatics Jurnal Abdi Insani Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) Almufi Jurnal Pengabdian kepada Masyarakat KOMMAS: Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII eProceedings of Engineering Community Service Seminar and Community Engagement (COSECANT) Telkatika: Jurnal Telekomunikasi Elektro Komputasi & Informatika Jurnal Nasional Sains dan Teknik
Ledya Novamizanti
Telkom University
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Hand gesture recognition using discrete wavelet transform and hidden Markov models Erizka Banuwati Candrasari; Ledya Novamizanti; Suci Aulia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.13725

Abstract

Gesture recognition based on computer-vision is an important part of human-computer interaction. But it lacks in several points, that was image brightness, recognition time, and accuracy. Because of that goal of this research was to create a hand gesture recognition system that had good performances using discrete wavelet transform and hidden Markov models. The first process was pre-processing, which done by resizing the image to 128x128 pixels and then segmented the skin color. The second process was feature extraction using the discrete wavelet transform. The result was the feature value in the form of a feature vector from the image. The last process was gesture classification using hidden Markov models to calculate the highest probability of feature matrix which had obtained from the feature extraction process. The result of the system had 72% of accuracy using 150 training and 100 test data images that consist five gestures. The newness thing found in this experiment were the effect of acquisition and pre-processing. The accuracy had been escalated by 14% compared to Sebastien’s dataset at 58%. The increment effect propped by brightness and contrast value.
Robust audio watermarking based on transform domain and SVD with compressive sampling framework Ledya Novamizanti; Gelar Budiman; Elsa Nur Fitri Astuti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14773

Abstract

The growth of the internet and digital data has resulted forgery, modification and sharing of digital data without property rights. Audio watermarking is one of a solution to protect the copyright of an audio from copyright infringement. This paper proposes an audio watermarking method which is robust against attacks and high capacity. First, a synchronization bit is added to the audio host. After the audio host is decomposed by Lifting Wavelet Transform (LWT), then choose a subband from the output of LWT to be transformed by discrete cosine transform (DCT). Next, the matrix of the signal from DCT is selected for the singular value decomposition (SVD) process, so that is obtained U, S and V matrix. S matrix is embedded with the watermark. Before the embedding process, the watermark image is compressed by Compressive Sampling. The results show that the proposed watermarking system is highly robust against a kind attack of LPF, resampling, and linear speed change which is proven by its BER is zero.
DWT-SMM-based audio steganography with RSA encryption and compressive sampling Fikri Adhanadi; Ledya Novamizanti; Gelar Budiman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14833

Abstract

Problems related to confidentiality in information exchange are very important in the digital computer era. Audio steganography is a form of a solution that infuses information into digital audio, and utilizes the limitations of the human hearing system in understanding and detecting sound waves. The steganography system applies compressive sampling (CS) to the process of acquisition and compression of bits in binary images. Rivest, Shamir, and Adleman (RSA) algorithms are used as a system for securing binary image information by generating encryption and decryption key pairs before the process is embedded. The insertion method uses statistical mean manipulation (SMM) in the wavelet domain and low frequency sub-band by dividing the audio frequency sub-band using discrete wavelet transform (DWT) first. The optimal results by using our system are the signal-to-noise ratio (SNR) above 45 decibel (dB) and 5.3833 bit per second (bps) of capacity also our system has resistant to attack filtering, noise, resampling and compression attacks.
Modified DCT-based Audio Watermarking Optimization using Genetics Algorithm Ledya Novamizanti; Gelar Budiman; Irma Safitri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.10111

Abstract

Ease process digital data information exchange impact on the increase in cases of copyright infringement. Audio watermarking is one solution in providing protection for the owner of the work. This research aims to optimize the insertion parameters on Modified Discrete Cosine Transform (M-DCT) based audio watermarking using a genetic algorithm, to produce better audio resistance. MDCT is applied after reading host audio, then embedding in MDCT domain is applied by Quantization Index Modulation (QIM) technique. Insertion within the MDCT domain is capable of generating a high imperceptible watermarked audio due to its overlapping frame system. The system is optimized using genetic algorithms to improve the value of imperceptibility and robustness in audio watermarking. In this research, the average SNR reaches 20 dB, and ODG reaches -0.062. The subjective quality testing on the system obtains an average MOS of 4.22 out of five songs tested. In addition, the system is able to withstand several attacks. The use of M-DCT in audio watermaking is capable of producing excellent imperceptibility and better watermark robustness.
Hand gesture recognition using discrete wavelet transform and convolutional neural network Muhammad Biyan Priatama; Ledya Novamizanti; Suci Aulia; Erizka Banuwati Candrasari
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (753.476 KB) | DOI: 10.11591/eei.v9i3.1977

Abstract

Public services are available to all communities including people with disabilities. One obstacle that impedes persons with disabilities from participating in various community activities and enjoying the various public services available to the community is information and communication barriers. One way to communicate with people with disabilities is with hand gestures. Therefore, the hand gesture technology is needed, in order to facilitate the public to interact with the disability. This study proposes a reliable hand gesture recognition system using the convolutional neural network method. The first step, carried out pre-processing, to separate the foreground and background. Then the foreground is transformed using the discrete wavelet transform (DWT) to take the most significant subband. The last step is image classification with convolutional neural network. The amount of training and test data used are 400 and 100 images repectively, containing five classes namely class A, B, C, # 5, and pointing. This study engendered a hand gesture recognition system that had an accuracy of 100% for dataset A and 90% for dataset B.
Fast Algorithm to Measure the Types of Foot Postures with Anthropometric Tests Using Image Processing Husneni Mukhtar; Dien Rahmawati; Desri Kristina Silalahi; Ledya Novamizanti; Muhammad Rayhan Ghifari; Ahmad Alfi Adz Dzikri; Faris Fadhlur Rachman; Ahmad Akbar Khatami
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 2 No 1 (2020): February
Publisher : Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v2i1.10

Abstract

There are two types of tools for measuring the foot posture, uniplanar (anthropometric and radiographic types) and multiplanar tools (such as Foot Posture Index-6 and -8). The process of the foot posture measurement with both tools performed by a doctor were commonly carried out by using manual equipment such as ruler, arc, goniometer, marker and applying the observation skill by eyes. It needs time to measure for each foot. For research needs, a large number of samples has to be provided by a doctor to analyze data statistically which consumes much more time and exhaustion from work load in the measurement process. Hence, the aim of this study is to significantly decrease the measurement time and minimizing human error by developing a software of anthropometric measurements of foot posture based on digital image processing (DIP). The anthropometric tests used in this study consist of Rear Foot Angle (RFA), Medial Length Arc Angle (MLAA) and Arch Height Index (AHI). Instead of using equipment with a series of measurement to determine the foot posture, the DIP system only need two pictures of foot as the input of the system. The methods involved in the image processing are performed by a series of digital image processing, started from pre-image processing, noise filter, Sobel edge detection, feature extraction, calculation and classification. The result of the image processing is able to determine the foot posture types for all tests based on the values of angle and length of the foot variables. The error measurements of length and angle are 6.22 % and (0.26-1.74) %, respectively. This study has demonstrated the development algorithm in MATLAB to measure the foot posture, which is named Anthro-Posture v1.0 software. This software offers an efficient alternative way in measuring and classifying the foot posture in a shorter time and minimizing the human error in measurement process. In the future, this study can be improved to be used by doctors in obtaining large amounts of data for research needed.
Identifikasi Kematangan Daun Teh Berbasis Fitur Warna Hue Saturation Intensity (HSI) dan Hue Saturation Value (HSV)(Identification Maturity Tea Leaves Based on Color Feature Hue Saturation Intensity (HSI) and Hue Saturation Value (HSV)) Rahma Nur Auliasari; Ledya Novamizanti; Nur Ibrahim
JUITA : Jurnal Informatika JUITA Vol. 8 Nomor 2, November 2020
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1037.112 KB) | DOI: 10.30595/juita.v8i2.7387

Abstract

Indonesia merupakan negara penghasil komoditi perkebunan teh terbesar di dunia. Sampai saat ini, penentuan tingkat kematangan daun teh hanya menggunakan sistem gilir petik, dimana suatu blok tanam telah ditentukan kapan akan dipanen. Perancangan sistem identifikasi kematangan daun teh membuat daun teh dengan tingkat kematangan tertentu terlihat lebih jelas. Pada penelitian ini, telah dirancang sistem identifikasi kematangan daun teh. Citra diambil di setiap blok dimana blok tersebut memiliki umur petik yang berbeda yakni blok yang sedang dipanen (matang), blok yang dalam waktu dekat akan dipanen (setengah matang), dan blok yang belum untuk dipanen (belum matang). Ekstraksi fitur menggunakan Hue Saturation Intensity (HSI) dan Hue Saturation Value (HSV), serta metode klasifikasi K-Nearest Neighbor (K-NN). Akurasi pada fitur warna HSI 100% dan HSV 83.33% dengan waktu komputasi masing-masing 28.4 mili detik dan 27.3 mili detik.
PENINGKATAN PENGELOLAAN PAUD MELALUI APLIKASI MONITORING SISTEM KEAMANAN DAN ADMINISTRASI KEUANGAN BERBASIS PHP DI PG DAN TK LITTLE MOSLEM, BOJONGSOANG, BANDUNG Anggunmeka Luhur Prasasti; Ledya Novamizanti; Rochmawati; Tora Fahrudin; Ashri Dinimaharawati
Panrita Abdi - Jurnal Pengabdian pada Masyarakat Vol. 6 No. 2 (2022): Jurnal Panrita Abdi - April 2022
Publisher : LP2M Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/pa.v6i2.11855

Abstract

An orderly & transparent administrative management of Preschool institutions is critical to improving the service performance of any Preschool institution. The recording of income and expenditure at Little Moslem Preschool, Bojongsoang, Bandung, is currently still being manually carried out. This practice already causes several problems, such as difficulties finding data when needed, calculation errors, and making reports that related parties do not become readily accessible due to data factors. Apart from this, no security system can be accessed directly by interested parties for peace and comfort in the school environment. Therefore, a solution is needed in financial administration applications, CCTV assistance, and applications for monitoring security and activities in Little Moslem Preschool. As mentioned earlier, administrative & assistive goals can be realized through a combination of modules within a PHP-based application connected to the network. This program is accompanied by training on the use of the application by managers, teachers, and parents of Little Moslem Preschool students. Based on the survey, 98,45% of participants had understood and used this application, so that in addition to being able to face digital challenges, with this activity it is hoped that the creation of an early childhood education institution that has quality, good service, and satisfying service of the institution's users is eventually made possible. --- Pengelolaan lembaga PAUD (Pendidikan Anak Usia Dini) harus tertib, transparan, dan teratur secara administrasi demi meningkatkan kinerja Lembaga/instansi PAUD tersebut. Pencatatan pendapatan dan pengeluaran di PG dan TK IT Little Moslem, Bojongsoang, Bandung, saat ini masih dilakukan secara manual. Hal tersebut mengakibatkan beberapa permasalahan muncul seperti kesulitan pencarian data ketika dibutuhkan, adanya kesalahan perhitungan, dan dan kesalahan dalam pembuatan laporan karena faktor data yang tidak mudah diakses oleh pihak terkait. Selain hal tersebut, belum tersedia sistem keamanan yang dapat diakses secara langsung oleh pihak-pihak berkepentingan demi ketenangan dan kenyamanan di lingkungan sekolah. Oleh karena itu, diperlukan solusi berupa aplikasi administrasi keuangan, bantuan CCTV, serta aplikasi untuk monitoring keamanan dan kegiatan dalam PG dan TK IT Little Moslem yang dapat dipantau melalui aplikasi berbasis PHP yang terhubung ke jaringan. Program ini disertai pelatihan penggunaan aplikasi tersebut oleh pengelola, guru-guru, dan orang tua siswa PAUD Little Moslem. Berdasarkan hasil survey, sebanyak 98,45% peserta memahami dan menggunakan aplikasi pengelolaan administrasi keuangan berbasis PHP, sehingga selain mampu menghadapi tantangan digital, dengan adanya kegiatan ini diharapkan terwujudnya Lembaga PAUD yang memiliki mutu, layanan yang baik, serta dapat meningkatkan kepuasan pengguna Lembaga PAUD.
PENGENALAN WAJAH INDIVIDU BERBASIS 3D BIOMETRIK Harist Gymnovriza; Ledya Novamizanti; Eko Susatio
JURNAL INFORMATIKA DAN KOMPUTER Vol 6, No 1 (2022): ReBorn - February 2022
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.942 KB) | DOI: 10.26798/jiko.v6i1.182

Abstract

Saat ini sistem aplikasi pengenalan individu yang menggunakan media wajah 3D cukup menarik perhatian peneliti. Wajah merupakan identitas yang khas dan unik dari masing – masing individu. Dalam kasusnya, wajah dapat diolah sebagai citra berbasis 2D dan 3D. Oleh karena itu, pada tugas akhir ini sebagai pemecah masalah tersebut digunakanlah metode ekstraksi berdasarkan konsep ICP atau Iterative Closest Point. Citra 3D didapatkan dengan menggunakan kamera Kinect v2, dimana jumlah pengambilan sebanyak 48 foto setiap individunya. Citra hasil akuisisi diproses dengan memberikan beberapa kali iterasi yang terpusat pada wajah individu. Selain itu juga dilakukan partisi terhadap citra wajah 3D menjadi 3 dan 6 bagian untuk mengetahui pengaruh partisi wajah terhadap tingkat akurasi. Pengujian dilakukan terhadap citra wajah 3D hasil akuisisi dengan kamera Kinect Penggunaan metode K-Nearest Neighbor (KNN) pada studi kasus 3D face recognition mendapatkan akurasi sebesar 88,09 % pada percobaan iterasi 25, 6 partisi dan nilai K = 1.
CONVOLUTIONAL NEURAL NETWORK PADA KLASIFIKASI SIDIK JARI MENGGUNAKAN RESNET-50 Novelita Dwi Miranda; Ledya Novamizanti; Syamsul Rizal
Jurnal Teknik Informatika (Jutif) Vol. 1 No. 2 (2020): JUTIF Volume 1, Number 2, December 2020
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2020.1.2.18

Abstract

Pengenalan sidik jari merupakan bagian dari teknologi biometrik. Klasifikasi sidik jari yang paling popular adalah Henry classification system. Henry membagi sidik jari berdasarkan garis polanya menjadi lima kelas yaitu arch (A), tented arch (T), left loop (L), right loop (R), dan whorl (W). Penelitian ini menggunakan Convolutional Neural Network (CNN) dengan model arsitektur Residual Network-50 (ResNet-50) untuk mengembangkan sistem klasifikasi sidik jari. Dataset yang digunakan diperoleh dari website National Institute of Standards and Technology (NIST) berupa citra sidik jari grayscale 8-bit. Hasil pengujian menunjukkan bahwa pemrosesan awal Contrast Limited Adaptive Histogram Equalization (CLAHE) dalam model CNN dapat meningkatkan performa akurasi dari sistem klasifikasi sidik jari sebesar 11,79%. Pada citra tanpa CLAHE diperoleh akurasi validasi 83,26%, sedangkan citra dengan CLAHE diperoleh akurasi validasi 95,05%.
Co-Authors ABDULFATTAH, MUHAMMAD EFAN Aditya, Ghanes Mahesa ADRIAN KURNIA, ADRIAN Adviatmadja, Sebastian Danny Agnes Gabriela Putri Winata Agung Nugroho Jati Ahmad Akbar Khatami Ahmad Alfi Adz Dzikri Ahmad Fauzan Fauzan Aldra Kasyfil Aziz Amini, Siti Aisyah Andy Ruhendy Putra ANGGUNMEKA LUHUR PRASASTI Annida, Nurafifah Aqilah Mamur Tanjung , Najmi Arindaka, Hafizhan Bhamakerti Armanda Nur Fadhlillah Ashri Dinimaharawati Aulia Wibowo Bambang Hidayat Cindy Angelista Deltika Cucu Alex Zaenudin Danny Adviatmadja, Sebastian David Chandra De Lima, Nadya Viana Dedy Rahman Wijaya Denny Meilika Setiawati Desri Kristina Silalahi Dias Wardana Dick Maryopi Dien Rahmawati Dimitri Mahayana Dine Octavia Kumalasari Eko Susatio Elsa Nur Fitri Astuti Elsa Nur Fitri Astuti Erizka Banuwati Candrasari Fahriansyah, Ardy Fajri, Farhan Ulil FARDAN FARDAN, FARDAN Faris Fadhlur Rachman Fathiyya, Dhiya Faza, Lulu Balqis Zianka Felix Pidha Hilman Fenty Alia Fikri Adhanadi Firdaus, Rifqi Fadhilah Fityanul Aditya Fityanul Akhyar Fredigo, Agno Gelar Budiman Gogi Gautama Al Hadiid HAFIZHANA, YASQI Hakim, Farhan Nur HANNAN HARAHAP, HANNAN Hanum, Mirza Alifia Harist Gymnovriza Hermawan, Laksamana Mikhail Husneni Mukhtar I Gusti Putu Agung Satria Bayu Mahendra I N Apraz Ramatryana I Nyoman Apraz Ramatryana Ilman, Mukhamad Zidni Imansyah Basudewa , Muhammad Indra Aulia Intan Sulviyani Irma Safitri Ivandy Chaniago Ivany Sesa Rehadi Iwan Iwut Iwan Iwut Tritoasmoro Iwut Tritoasmoro, Iwan Jangkung Raharjo Koredianto Usman Kurnia Ramadani Kurniawan Nur Ramadhani Mahanani, Edo Lutfi Mahfuz, Muhammad Rafi Marlindia Ike Sari Maulana , Muhammad Dafa Mertu, Aidi Mirsa Bayu Prasetyo Mochamad Reyhand Landrenzy Zulfikar Mohamad Alfaj’ri Muhammad Alief Hidayah Baso Muhammad Azwar Zulmi Muhammad Biyan Priatama Muhammad Fikri Aufa Muhammad Hablul Barri Muhammad Harits Ibrahim Muhammad Iqbal Rabbani Muhammad Raia Pratama Putra Wibowo Muhammad Rayhan Ghifari Muhammad Rizqy Alfarisi Muhammad Sindu Ramadhan Muhammad Wahyu Setiawan Nabila Setya Utami Novelita Dwi Miranda Novialdy Nugroho Santoso Nur Ibrahim Paradila I., Dela Parjuangan, Sabam Pinasthika Aulia Fadhila Pratama , Nyoman Raflly Prawita, Fat’hah Noor Priyambodo, Afif Putra, Afi Athallah Syamsulhadi Putu Harry Gunawan R Ricki Juniansyah R. Yunendah Nur Fu’adah Rabby Fitriana Adawiyah Rahma Nur Auliasari Rahmawati, Aulya RAMATRYANA, I NYOMAN APRAZ Randy Hamzah Hardianto Ratri Dwi Atmaja Razendra Zahran Firdaus Reyhan Radifan Jordy RIANTIARNI, TITA Rita Magdalena Rita Purnamasari Rita Rismala Rizal, Mochammad Fahru Rochmawati Ruslan , Ramah Rinaldi Ryan Anggara Sa'idah, Sofia Sari, Rina Media Satria Mandala Sa’idah, Sofia Setyagraha , Muhammad Rafi Mahfuz SIDDIK, MUHAMMAD ARSYAD Siti Azizah Suci Aulia Sugondo Hadiyoso Sulistyowati, Syifa Dwi Suryo Adhi Wibowo Susatio, Eko Susi Diriyanti Novalina Syamsul Rizal Syamsul Rizal Tanjung, Najmi Aqilah Mamur Thomhert Suprapto Siadari Thoriq Bayu Aji Tora Fahrudin Wahidin Wahidin WANANDA, PUTU DEBBY WIBOWO, BHISMA ADI Wicaksono, Muhammad Rievnuansyah YUYUN SITI ROHMAH Zahra Zettira Zukhrufuljannah Zaky, Pavel Manaf El