Garuda - Garba Rujukan Digital

DETEKSI MANUSIA MENGGUNAKAN METODE HISTOGRAM OF ORIENTED GRADIENT DAN EUCLIDEAN DISTANCE Mufarroha, Fifin Ayu; Sirajuddin, Indah Agustien; Kusumaningsih, Ari
Network Engineering Research Operation [NERO] Vol 3, No 3 (2018): NERO
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Prinsip utama dari human detection adalah menemukan objek atau manusia didalam sebuah gambar. Banyak keuntungan yang bisa diambil dari hal ini, terutama dalam video pengawasan. Human detection dalam sebuah gambar lebih sulit karena banyaknya kendala yang dihadapi seperti pencahayaan, pakaian atau penampilan objek dan pose objek didalam setiap gambar yang berbeda. Pada penelitian ini akan diusulkan suatu metode ekstraksi fitur yang menggunakan histogram untuk melakukan human detection disebut dengan histogram of oriented gradient. Metode diawali dengan menghitung nilai gradien dari konversi citra grayscale yang kemudian citra akan dibagi menjadi sel dan tiap sel akan dibuat sebuah histogram dari nilai perhitungan gradien tersebut. Langkah selanjutnya adalah membentuk sebuah blok yang merupakan kumpulan dari sel. Setelah di bentuk sebuah blok, blok tersebut akan dinormalisasi dan hasil dari normalisasi blok tersebut adalah fitur. Sehingga dari hasil ekstraksi fitur akan dilakukan pengukuran kemiripan dengan citra file dengan menggunakan metode Euclidean Distance. Citra pelatihanÂ dan citra pengujian coba yang digunakan adalah 200 citra dengan 50 data positif, 50 data negatif, dan 100 citra uji. Dari uji coba aplikasi menggunakan pengukuran kemiripan Euclidean Distance dengan nilai threshold= 2,3,4, dan 5 pada skenario 1 dan 2 diperoleh rata â rata akurasi sebesar 80,55%.Kata kunci: Deteksi, fitur, Human Detection, Histogram of Oriented Gradient, Euclidean Distance.

KEAMANAN CITRA DENGAN WATERMARKING MENGGUNAKAN PENGEMBANGAN ALGORITMA LEAST SIGNIFICANT BIT Kurniawan, Kurniawan; Siradjuddin, Indah Agustien; Muntasa, Arif
Jurnal Informatika Vol 13, No 1 (2015): MAY 2015
Publisher : Institute of Research and Community Outreach - Petra Christian University

Image security is a process to save digital. One method of securing image digital is watermarking using Least Significant Bit algorithm. Main concept of image security using LSB algorithm is to replace bit value of image at specific location so that created pattern. The pattern result of replacing the bit value of image is called by watermark. Giving watermark at image digital using LSB algorithm has simple concept so that the information which is embedded will lost easily when attacked such as noise attack or compression. So need modification like development of LSB algorithm. This is done to decrease distortion of watermark information against those attacks. In this research is divided by 6 process which are color extraction of cover image, busy area search, watermark embed, count the accuracy of watermark embed, watermark extraction, and count the accuracy of watermark extraction. Color extraction of cover image is process to get blue color component from cover image. Watermark information will embed at busy area by search the area which has the greatest number of unsure from cover image. Then watermark image is embedded into cover image so that produce watermarked image using some development of LSB algorithm and search the accuracy by count the Peak Signal to Noise Ratio value. Before the watermarked image is extracted, need to test by giving noise and doing compression into jpg format. The accuracy of extraction result is searched by count the Bit Error Rate value.

Multi-Criteria in Discriminant Analysis to Find the Dominant Features Arif Muntasa; Indah Agustien Siradjuddin; Rima Tri Wahyuningrum
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3472

A crucial problem in biometrics is enormous dimensionality. It will have an impact on the costs involved. Therefore, the feature extraction plays a significant role in biometrics computational. In this research, a novel approach to extract the features is proposed for facial image recognition. Four criteria of the Discriminant Analysis have been modeled to find the dominant features. For each criterion is an objective function, it was derived to obtain the optimum values. The optimum values can be solved by using generalized the Eigenvalue problem associated to the largest Eigenvalue. The modeling results were employed to recognize the facial image by the multi-criteria projection to the original data. The training sets were also processed by using the Eigenface projection to avoid the singularity problem cases. The similarity measurements were performed by using four different methods, i.e. Euclidian Distance, Manhattan, Chebyshev, and Canberra. Feature extraction and analysis results using multi-criteria have shown better results than the other appearance method, i.e. Eigenface (PCA), Fisherface (Linear Discriminant Analysis or LDA), Laplacianfaces (Locality Preserving Projection or LPP), and Orthogonal Laplacianfaces (Orthogonal Locality Preserving Projection or O-LPP).

Double Difference Motion Detection and Its Application for Madura Batik Virtual Fitting Room Rima Triwahyuningrum; Indah Agustien Siradjuddin; Yonathan Fery Hendrawan; Arik Kurniawati; Ari Kusumaningsih
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 4: December 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i4.2236

Madura Batik Virtual Fitting Room using double difference algorithms motion detection is proposed in this research. This virtual fitting room consists of three main stages, i.e. motion detection, determination of region of interest of the detected motion, superimposed the virtual clothes into the region of interest. The double difference algorithm is used for the motion detection stage, since in this algorithm, the empty frame as the reference frame is not required. The double difference algorithm uses the previous and next frame to detect the motion in the current frame. Perception Test Images Sequences Dataset are used as the data of the experiment to measure the performance accuracy of this algorithm before the algorithm is used for the Madura batik virtual fitting room. The accuracy is 57.31%, 99.71%, and 78.52% for the sensitivity, specificity, and balanced accuracy, respectively. The build Madura batik virtual fitting room in this research can be used as the added feature of the Madura batik online stores, hence the consumer is able to see whether the clothes is fitted to them or not, and this virtual fitting room is also can be used as the promotion of Madura batik broadly.

Contradictory of the Laplacian Smoothing Transform and Linear Discriminant Analysis Modeling to Extract the Face Image Features Arif Muntasa; Indah Agustien Siradjuddin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6576

Laplacian smoothing transform uses the negative diagonal element to generate the new space. The negative diagonal elements will deliver the negative new spaces. The negative new spaces will cause decreasing of the dominant characteristics. Laplacian smoothing transform usually singular matrix, such that the matrix cannot be solved to obtain the ordered-eigenvalues and corresponding eigenvectors. In this research, we propose a modeling to generate the positive diagonal elements to obtain the positive new spaces. The secondly, we propose approach to overcome singularity matrix to found eigenvalues and eigenvectors. Firstly, the method is started to calculate contradictory of the laplacian smoothing matrix. Secondly, we calculate the new space modeling on the contradictory of the laplacian smoothing. Moreover, we calculate eigenvectors of the discriminant analysis. Fourth, we calculate the new space modeling on the discriminant analysis, select and merge features. The proposed method has been tested by using four databases, i.e. ORL, YALE, UoB, and local database (CAI-UTM). Overall, the results indicate that the proposed method can overcome two problems and deliver higher accuracy than similar methods.

Particle Filter with Gaussian Weighting for Human Tracking Indah Agustien Siradjuddin; M. Rahmat Widyanto; T. Basaruddin T. Basaruddin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 4: December 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i4.869

Particle filter for object tracking could achieve high tracking accuracy. To track the object, this method generates a number of particles which is the representation of the candidate target object. The location of target object is determined by particles and each weight. The disadvantage of conventional particle filter is the computational time especially on the computation of particle’s weight. Particle filter with Gaussian weighting is proposed to accomplish the computational problem. There are two main stages in this method, i.e. prediction and update. The difference between the conventional particle filter and particle filter with Gaussian weighting is in the update Stage. In the conventional particle filter method, the weight is calculated in each particle, meanwhile in the proposed method, only certain particle’s weight is calculated, and the remain particle’s weight is calculated using the Gaussian weighting. Experiment is done using artificial dataset. The average accuracy is 80,862%. The high accuracy that is achieved by this method could use for the real-time system tracking

Pembuatan dan Digitalisasi Batik Tulis Madura Pada UKM Batik Bangkalan Indah Agustien Siradjuddin; Kautsar Sophan; Arik Kurniawati; Rima Triwahyuningrum
Jurnal Ilmiah Pangabdhi Vol 4, No 1: April 2018
Publisher : LPPM Universitas Trunojoyo Madura

Batik Madura dikenal akan jenis batik tulis Madura yang memiliki motif batik dan warna batik yang unik. Keseluruhan produksi batik tulis Madura ini dilakukan secara manual, mulai dari desain batik, menggambar batik pada kain, mencanting, fiksasi, pewarnaan, dan lain-lain. Proses manual inilah yang tetap menjaga keaslian batik tulis Madura. Hanya saja, kain batik yang dihasilkan pada batik tulis Madura ini, tidak menghasilkan pola yang simetris ketika kain batik dibuat menjadi sebuah pakaian. Motif-motif yang terdapat pada pakaian yang berasal dari kain batik tulis Madura, tidak membentuk pola yang simetris. Oleh karena itu diperlukan upaya agar motif-motif yang dibuat oleh pengrajin batik, dapat membentuk pola simetris pada suatu pakaian. Kegiatan pengabdian yang diusulkan adalah pembuatan motif batik tulis Madura, agar pakaian yang dihasilkan menampilkan pola simetris, dengan bantuan perangkat lunak. Tahap pertama yang dilakukan adalah pembuatan mal atau template pakaian yang akan dibuat, penyusunan mal ini pada desain kain batik, penyusunan motif-motif batik pada kain sehingga sesuai dengan mal pakaian yang telah ada.

PENGEMBANGAN KOMPETENSI GURU SMKN 1 LABANG BANGKALAN MELALUI PEMBUATAN MEDIA PEMBELAJARAN AUGMENTED REALITY DENGAN METAVERSE Ariesta Kartika Sari; Puji Rahayu Ningsih; Wanda Ramansyah; Arik Kurniawati; Indah Agustien Siradjuddin; Mochammad Kautsar Sophan
Panrita Abdi - Jurnal Pengabdian pada Masyarakat Vol. 4 No. 1 (2020): Jurnal Panrita Abdi - Februari 2020
Publisher : LP2M Universitas Hasanuddin

An Improvement on Competence of SMKN 1 Labang Bangkalan Educators by Creating Augmented Reality Learning Media Using MetaverseAbstract. Currently, technology has entered the Information Technology Era 4.0, where technology using the internet is increasingly being used. Along with the development of technology and information and referring to the competence of teachers in the Teacher Law and Lecturer Number 14 of 2005, a teacher is expected to be able to utilize technology, information and communication in the application of learning. This is needed in order to improve the quality of education and learning in schools. One of the efforts in increasing teacher competency related to instructional media is through training in making augmented reality learning media using the metaverse application. The learning media development activity is located at SMK Negeri 1 Labang Bangkalan Madura with the Participants being 14 teachers. The method of this activities is workshops and presentations. The evaluation method in this activity is through the distribution of the questionnaire response instruments. This activity produces: (a) augmented reality learning media by using the metaverse application and (b) teacher responses. This activity giving conclusion that: (a) training in the development of Augmented Reality learning media using metaverse application can develop the competency of teacher skills which related to learning media, (b) 100% of the activity participants expressed interest, and (c) 93% of the training participants stated that the development of media Augmented Reality learning by using the metaverse application is useful.Keywords: competence, learning media, Augmented Reality, MetaverseAbstrak. Saat ini teknologi telah memasuki Era Teknologi Informasi 4.0, yang mana teknologi dengan memanfaatkan internet makin banyak digunakan. Seiring dengan perkembangan teknologi dan informasi tesebut serta mengacu pada kompetensi guru dalam Undang-undang Guru dan Dosen Nomor 14 Tahun 2005 tersebut, maka seorang guru diharapkan mampu memanfaatkan teknologi, informasi dan komunikasi dalam penerapan pembelajaran. Hal ini diperlukan dalam rangka peningkatan kualitas pendidikan dan pembelajaran dalam sekolah. Salah satu upaya dalam peningkatan kompetensi guru terkait media pembelajaran adalah melalui adanya pelatihan pembuatan media pembelajaran Augmented Reality dengan menggunakan aplikasi metaverse. Kegiatan pengabdian pengembangan media pembelajaran ini bertempat di SMKN 1 Labang Bangkalan Madura, Peserta Kegiatan adalah guru-guru sebanyak 14 orang. Metode kegiatan pengabdian adalah berupa workshop dan presentasi. Metode evaluasi pada kegiatan pengabdian ini adalah melalui penyebaran instrumen angket respon. Kegiatan ini menghasilkan media pembelajaran Augmented Reality dengan menggunakan aplikasi metaverse serta respon guru. Kegiatan pengabdian ini menghasilkan kesimpulan bahwa: (a) pelatihan pengembangan media pembelajaran Augmented Reality dengan aplikasi metaverse dapat mengembangkan kompetensi keterampilan guru terkait media pembelajaran, (b) 100% peserta kegiatan menyatakan tertarik, dan (c) 93% peserta pelatihan menyatakan bahwa pengembangan media pembelajaran Augmented Reality dengan menggunakan aplikasi metaverse adalah bermanfaat.Kata Kunci: kompetensi, media pembelajaran, Augmented Reality, Metaverse

Identification of Pedestrians Attributes Based on Multi-Class Multi-Label Classification using Convolutional Neural Network (CNN) Wrida Adi Wardana; Indah Agustien Siradjuddin; Arif Muntasa
Journal of Data Science and Its Applications Vol 3 No 1 (2020): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/jdsa.2020.3.43

The usage of computer vision in identifying pedestrians attributes has received a great attention, especially in the visual surveillance systems. For instance, searching for system based on the attributes. Attributes Identification using Convolutional Neural Network architecture is presented in this article, since the architecture can perform feature learning. CNN consist of convolution layer, ReLU, Pooling, and Fully-connected. There are three experiment scenarios are conducted based on the number of convolution layers, to determine the effect of layers on CNN performance. Three different CNN architectures were trained and tested using a PETA dataset with 35 attributes. The highest accuracy achieved is 75.66% based on number of convolutional layers. The conducted experiments showed that more numbers of convolution layers used would produce the better CNN's performance.

PEMBUATAN DAN DIGITALISASI BATIK TULIS MADURA PADA UKM BATIK BANGKALAN Indah Agustien Siradjuddin; M. Kautsar Sophan; Arik Kurniawati; Rima Triwahyuningrum
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 3 No. 1 (2019): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Batik Madura dikenal akan jenis batik tulis Madura yang memiliki motif batik dan warna batik yang unik. Keseluruhan produksi batik tulis Madura ini dilakukan secara manual, mulai dari desain batik, menggambar batik pada kain, mencanting, fiksasi, pewarnaan, dan lain-lain. Proses manual inilah yang tetap menjaga keaslian batik tulis Madura. Hanya saja, kain batik yang dihasilkan pada batik tulis Madura ini, tidak menghasilkan pola yang simetris ketika kain batik dibuat menjadi sebuah pakaian. Motif-motif yang terdapat pada pakaian yang berasal dari kain batik tulis Madura, tidak membentuk pola yang simetris. Oleh karena itu diperlukan upaya agar motif-motif yang dibuat oleh pengrajin batik, dapat membentuk pola simetris pada suatu pakaian. Kegiatan pengabdian yang diusulkan adalah pembuatan motif batik tulis Madura, agar pakaian yang dihasilkan menampilkan pola simetris, dengan bantuan perangkat lunak. Tahap pertama yang dilakukan adalah pembuatan mal atau template pakaian yang akan dibuat, penyusunan mal ini pada desain kain batik, penyusunan motif-motif batik pada kain sehingga sesuai dengan mal pakaian yang telah ada.

Title

Found 14 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 14 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 14 Documents
Search