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All Journal EMITTER International Journal of Engineering Technology Jurnal Teknologi Informasi dan Terapan (J-TIT)
Achmad Basuki
Politeknik Elektronika Negeri Surabaya, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Komputasi Budaya Untuk Pencarian Gambar Semantik Pada Lukisan Budaya Indonesia Dengan Deteksi Dan Informasi Aliran Lukisan Ratri Cahyaning Winedhar; Ali Ridho Barakbah; Achmad Basuki; Arvita Agus Kurniasari
Jurnal Teknologi Informasi dan Terapan Vol 8 No 1 (2021)
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v8i1.224

Abstract

Lukisan merupakan salah satu gambaran kompleks yang mencerminkan pengamatan dan perasaan seniman terhadap lingkungan. Kondisi ini memperluas kebutuhan akan sistem pendeteksi citra budaya karena masyarakat awam yang kurang memiliki pengalaman artistik akan sulit mendapatkan kesan lukisannya. Oleh karena itu, peneliti menekankan penerapan lukisan budaya Indonesia ke dalam aplikasi mobile. Sistem yang diusulkan telah diimplementasikan pada 239 lukisan budaya Indonesia yang terdiri dari lima kategori gaya lukisan. Kategorinya adalah abstraksionisme, naturalisme, ekspresionisme, realisme, dan romantisme. Sistem mengekstrak 3 fitur, yaitu fitur warna, bentuk, dan tekstur. Ekstraksi ciri warna menggunakan Histogram 3D Color Vector Quantization. Ekstraksi fitur bentuk menggunakan Connected Component Labeling Algorithm (CCL) dengan menghitung nilai area, diameter setara, luas, convex hull, soliditas, eksentrisitas, dan perimeter masing-masing objek. Ekstraksi fitur tekstur menggunakan Gabor Transformation dengan 40 kernel. Sedangkan untuk ekstraksi impresi dilakukan survey terhadap beberapa orang tentang impresi lukisan budaya Indonesia. Survei ini dilakukan terhadap responden yang memahami seni lukis seperti pelukis, pemerhati lukisan, dan orang-orang yang berkecimpung di dunia seni rupa. Untuk menunjukkan gaya lukisan peneliti menggunakan proses klasifikasi menggunakan K-Nearest Neighbor. Hasil eksperimen menunjukan fitur warna sebagai fitur terbaik dalam impression query
Automatic Samples Selection Using Histogram of Oriented Gradients (HOG) Feature Distance Inzar Salfikar; Indra Adji Sulistijono; Achmad Basuki
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v5i2.182

Abstract

Finding victims at a disaster site is the primary goal of Search-and-Rescue (SAR) operations. Many technologies created from research for searching disaster victims through aerial imaging. but, most of them are difficult to detect victims at tsunami disaster sites with victims and backgrounds which are look similar. This research collects post-tsunami aerial imaging data from the internet to builds dataset and model for detecting tsunami disaster victims. Datasets are built based on distance differences from features every sample using Histogram-of-Oriented-Gradient (HOG) method. We use the longest distance to collect samples from photo to generate victim and non-victim samples. We claim steps to collect samples by measuring HOG feature distance from all samples. the longest distance between samples will take as a candidate to build the dataset, then classify victim (positives) and non-victim (negatives) samples manually. The dataset of tsunami disaster victims was re-analyzed using cross-validation Leave-One-Out (LOO) with Support-Vector-Machine (SVM) method. The experimental results show the performance of two test photos with 61.70% precision, 77.60% accuracy, 74.36% recall and f-measure 67.44% to distinguish victim (positives) and non-victim (negatives).
Content-Dependent Image Search System for Aggregation of Color, Shape and Texture Features Arvita Agus Kurniasari; Ali Ridho Barakbah; Achmad Basuki
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (717.8 KB) | DOI: 10.24003/emitter.v7i1.361

Abstract

The existing image search system often faces difficulty to find a appropriate retrieved image corresponding to an image query. The difficulty is commonly caused by that the users’ intention for searching image is different with dominant information of the image collected from feature extraction. In this paper we present a new approach for content-dependent image search system. The system utilizes information of color distribution inside an image and detects a cloud of clustered colors as something - supposed as an object. We applies segmentation of image as content-dependent process before feature extraction in order to identify is there any object or not inside an image. The system extracts 3 features, which are color, shape, and texture features and aggregates these features for similarity measurement between an image query and image database. HSV histogram color is used to extract color feature of image. While the shape feature extraction used Connected Component Labeling (CCL) which is calculated the area value, equivalent diameter, extent, convex hull, solidity, eccentricity, and perimeter of each object. The texture feature extraction used Leung Malik (LM)’s approach with 15 kernels.  For applicability of our proposed system, we applied the system with benchmark 1000 image SIMPLIcity dataset consisting of 10 categories namely Africans, beaches, buildings historians, buses, dinosaurs, elephants, roses, horses, mountains, and food. The experimental results performed 62% accuracy rate to detect objects by color feature, 71% by texture feature, 60% by shape feature, 72% by combined color-texture feature, 67% by combined color-shape feature, 72 % combined texture-shape features and 73% combined all features.
Observation of Fish Dissemination Pattern on Madura Coastal Using Segmentation of Satellite Images Citra Nurina Prabiantissa; Achmad Basuki; Wahjoe Tjatur Sesulihatien
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1187.692 KB) | DOI: 10.24003/emitter.v7i1.383

Abstract

Almost traditional fishermen still use manual methods to catch fish that rely on experience in fishing and information among fellow fishermen. This method is not effective for maximizing fish production. A good pattern or strategy is needed to increase fish production. In determining dissemination pattern of fish, it can be predicted from physical parameters such as temperature, salinity, chlorophyll, turbidity, total suspended solids, and colored dissolved organic matter using the Landsat 8 images.  This research area is on the Island of Madura Coast. The pattern is determined by using Lagrange Interpolation and clustering using K-Means. The results of the study of the pattern of fish dissemination were then validated with data from the Dinas Kelautan dan Perikanan Jawa Timur. The results between fish patterns and validation data in 2015 showed similarities in January, February, March, May, June, July, August, September. In 2016, results between fish patterns and validation data showed that similarities in July, August, September, and December. In 2017, results between fish patterns and validation data showed similarities in November. 2015 has the most similarities between the patterns and validation data and the least similarity are 2017.
Automatic Detection of Wrecked Airplanes from UAV Images Anhar Risnumawan; Muhammad Ilham Perdana; Alif Habib Hidayatulloh; A. Khoirul Rizal; Indra Adji Sulistijono; Achmad Basuki; Rokhmat Febrianto
EMITTER International Journal of Engineering Technology Vol 7 No 2 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i2.424

Abstract

Searching the accident site of a missing airplane is the primary step taken by the search and rescue team before rescuing the victims. However, due to the vast exploration area, lack of technology, no access road, and rough terrain make the search process nontrivial and thus causing much delay in handling the victims. Therefore, this paper aims to develop an automatic wrecked airplane detection system using visual information taken from aerial images such as from a camera. A new deep network is proposed to distinguish robustly the wrecked airplane that has high pose, scale, color variation, and high deformable object. The network leverages the last layers to capture more abstract and semantics information for robust wrecked airplane detection. The network is intertwined by adding more extra layers connected at the end of the layers. To reduce missing detection which is crucial for wrecked airplane detection, an image is then composed into five patches going feed-forwarded to the net in a convolutional manner. Experiments show very well that the proposed method successfully reaches AP=91.87%, and we believe it could bring many benefits for the search and rescue team for accelerating the searching of wrecked airplanes and thus reducing the number of victims.
Fire Image Set for Evoking Panic Iqbal sabilirrasyad; Achmad Basuki; Tri Harsono
EMITTER International Journal of Engineering Technology Vol 8 No 2 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i2.504

Abstract

Fire is the closest disaster to us, a person who put cigarettes around flammable objects could burn one to dozens of houses. The last thing that happens was a mass panic. In this kind of situation, panic is one of the keys to determine how much probability someone will survive. However, detecting someone's panic during a fire is impossible. This leads some scientists to assume that mass panic was never happening and some studies use simple functions to determine someone when panic. Currently, thanks to technological advances we can easily build virtual worlds that resemble real events. To build a virtual world that could evoke panic we still need the right stimulus. In this paper, we will discuss with terms of fire disaster stimulus that possible to impel someone to feel panic. While some stimulus datasets that already exist have more broad categories, we wanted to focus on a specific problem. The determined parameters are considered through several elements that could cause a person to panic, either before or during a fire. By using the Self-Assessment Manikin system to obtain valance and arousal matrix, we conduct a test to see how much influence the fire categories stimulus provided.
Developing Shooter Game Interaction using Eye Movement Glasses Abdullah Iskandar; Achmad Basuki; Artiarini Kusuma Nurindiyani; Faris Rasyadi Putra; Mohamad Safrodin
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.509

Abstract

A quadriplegic is a paralysis that affects limitations in some physical movements and psychological disorders. They have limited media to interact with computers so a suitable solution is needed in the form of a media that can recognize other body parts movements which in this research uses eye movement. one of the solutions to this problem is to propose alternative technologies to interact and play games. We propose a simple technique by using a camera mounted on the glasses that will take the eye area. This technique will help reduce unnecessary parts of eye detection so that performance increases. The eyes will be processed using basic image processing and then determined the center position of the pupil using the Mean method. This system consists of pupil movements for pointer motion control and blinking of eyes for shooting. The performance test of this method toward the system, which has used 10 people with 7 experiments, shows an accuracy of 84.86 percent, the speed of movement with a duration of 2.22 seconds and the speed of response blinking with a duration of 0.026 seconds. In addition, we can distinguish between intentional blink and unintentional blink in which intentional blink has a duration of 0.30 seconds and unintentional 0.12 seconds. It can be concluded that by using this method and this technique is able to achieve good accuracy and also able to use intentional blink as shoot trigger.
Co-Authors A. Khoirul Rizal Abdullah Iskandar Ali Ridho Barakbah Alif Habib Hidayatulloh Artiarini Kusuma Nurindiyani Arvita Agus Kurniasari Arvita Agus Kurniasari Citra Nurina Prabiantissa Faris Rasyadi Putra Indra Adji Sulistijono Iqbal Sabilirrasyad Mohamad Safrodin Muhammad Ilham Perdana Ratri Cahyaning Winedhar Risnumawan, Anhar Rokhmat Febrianto Solly Aryza Tri Harsono Wahjoe Tjatur Sesulihatien