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All Journal MEDIA KOMUNIKASI TEKNIK SIPIL Medical Journal of Indonesia Indonesian Journal of Cancer EMITTER International Journal of Engineering Technology Jurnal Mantik Matriks Teknik Sipil
Achmad Basuki
Teknologi Informasi, Politeknik Elektronika Negeri Surabaya (PENS) – ITS Jl. Raya ITS, Keputih-Sukolilo, Surabaya, 60111. Telp. +62-31-5947280
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Medicine & Pharmacology

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Remo Dance Motion Estimation with Markerless Motion Capture Using The Optical Flow Method Kurniati, Neny; Basuki, Achmad; Pramadihanto, Dadet
EMITTER International Journal of Engineering Technology Vol 3, No 1 (2015)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v3i1.33

Abstract

Motion capture has been developed and applied in various fields, one of them is dancing. Remo dance is a dance from East Java that tells the struggle of a prince who fought on the battlefield. Remo dancer does not use body-tight costume. He wears a few costume pieces and accessories, so required a motion detection method that can detect limb motion which does not damage the beauty of the costumes and does not interfere motion of the dancer. The method is Markerless Motion Capture. Limbs motions are partial behavior. This means that all limbs do not move simultaneously, but alternately. It required motion tracking to detect parts of the body moving and where the direction of motion. Optical flow is a method that is suitable for the above conditions. Moving body parts will be detected by the bounding box. A bounding box differential value between frames can determine the direction of the motion and how far the object is moving. The optical flow method is simple and does not require a monochrome background. This method does not use complex feature extraction process so it can be applied to real-time motion capture. Performance of motion detection with optical flow method is determined by the value of the ratio between the area of the blob and the area of the bounding box. Estimate coordinates are not necessarily like original coordinates, but if the chart of estimate motion similar to the chart of the original motion, it means motion estimation it can be said to have the same motion with the original.Keywords: Motion Capture, Markerless, Remo Dance, Optical Flow
A Prediction System of Dengue Fever Using Monte Carlo Method Roziqin, Mochammad Choirur; Basuki, Achmad; Harsono, Tri
EMITTER International Journal of Engineering Technology Vol 4, No 1 (2016)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.598 KB) | DOI: 10.24003/emitter.v4i1.111

Abstract

Dengue fever is an acute disease that clinically can cause death because there is no prediction system to estimate dengue fever cases so it resulted in the growing of dengue fever cases every year. Original data gathering in Jember area that uses technique of partial data gathering has caused data missing. To make this secondary data can be processed in prediction stage there is need to conduct missing imputation by using Monte Carlo method with four different randomization method, followed by data normality test with chi-square, then continued to regression stage. We use MSE (Mean Square Error) to measure prediction error. The smallest MSE result of regression is the best regression model for prediction.
Mobile Application to Identify Indonesian Flowers on Android Platform Karlita, Tita; Basuki, Achmad; Makarti, Lakmi
EMITTER International Journal of Engineering Technology Vol 1, No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v1i1.10

Abstract

Although many people love flowers, they do not know their name. Especially, many people do not recognize local flowers. To find the flower image, we can use search engine such as Google, but it does not give much help to find the name of local flower. Sometimes, Google cannotshow the correct name of local flowers. This study proposes an application to identify Indonesian flowers that runs on the Android platform for easy use anywhere. Flower recognition is based on the color features using the Hue-Index, shape feature using Centroid Contour Distance (CCD), and the similarity measurement using Entropy calculations. The outputs of this application are information about inputted flower image including Latinname, local name, description, distribution and ecology. Based on tests performed on 44 types of flowers with 181 images in the database, the best similarity percentage is 97.72%. With this application, people will be expected to know more about Indonesia flowers.Keywords: Indonesian flowers, android, hue-index, CCD, entropy
Semantic Songket Image Search with Cultural Computing of Symbolic Meaning Extraction and Analytical Aggregation of Color and Shape Features Amirullah, Desi; Barakbah, Ali Ridho; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 3, No 1 (2015)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v3i1.37

Abstract

The term "Songket" comes from the Malay word "Sungkit", which means "to hook" or "to gouge". Every motifs names and variations was derived from plants and animals as source of inspiration to create many patterns of songket. Each of songket patterns have a philosophy in form of rhyme that refers to the nature of the sources of songket patterns and that philosophy reflects to the beliefs and values of Malay culture. In this research, we propose a system to facilitate an understanding of songket and the philosophy as a way to conserve Songket culture. We propose a system which is able to collect information in image songket motif variations based on feature extraction methods. On each image songket motif variations, we extracted philosophy of rhyme into impressions, and extracting color features of songket images using a histogram 3D-Color Vector quantization (3D-CVQ), shape feature extraction songket image using HU Moment invariants. Then, we created an image search based on impressions, and impressions search based on image. We use techniques of search based on color, shape and aggregation (combination of colors and shapes). The experiment using impression as query : 1) Result based on color, the average value of true 7.3, total score 41.9, 2) Result based on shape, the average value of true 3, total score 16.4, 3) Result based on aggregation, the average value of true 3, total score 17.4. While based using Image Query : 1) Result based on color, the average precision 95%, 2) Result based on shape, average precision 43.3%, 3) Based aggregation, the average precision 73.3%. From our experiments, it can be concluded that the best search system using query impression and query image is based on the color.Keyword : Image Search, Philosophy, impression, Songket, cultural computing, Feature Extraction, Analytical aggregation.
Automatic Samples Selection Using Histogram of Oriented Gradients (HOG) Feature Distance Salfikar, Inzar; Sulistijono, Indra Adji; Basuki, Achmad
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).
Moment Invariant Features Extraction for Hand Gesture Recognition of Sign Language based on SIBI Rahagiyanto, Angga; Basuki, Achmad; Sigit, Riyanto
EMITTER International Journal of Engineering Technology Vol 5, No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4951.447 KB) | DOI: 10.24003/emitter.v5i1.173

Abstract

Myo Armband became an immersive technology to help deaf people for communication each other. The problem on Myo sensor is unstable clock rate. It causes the different length data for the same period even on the same gesture. This research proposes Moment Invariant Method to extract the feature of sensor data from Myo. This method reduces the amount of data and makes the same length of data. This research is user-dependent, according to the characteristics of Myo Armband. The testing process was performed by using alphabet A to Z on SIBI, Indonesian Sign Language, with static and dynamic finger movements. There are 26 class of alphabets and 10 variants in each class. We use min-max normalization for guarantying the range of data. We use K-Nearest Neighbor method to classify dataset. Performance analysis with leave-one-out-validation method produced an accuracy of 82.31%. It requires a more advanced method of classification to improve the performance on the detection results.
Comparison of The Data-Mining Methods in Predicting The Risk Level of Diabetes Wicaksono, Andri Permana; Badriyah, Tessy; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 4, No 1 (2016)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (813.592 KB) | DOI: 10.24003/emitter.v4i1.119

Abstract

Mellitus Diabetes is an illness that happened in consequence of the too high glucose level in blood because the body could not release or use insulin normally. The purpose of this research is to compare the two methods in The data-mining, those are a Regression Logistic method and a Bayesian method, to predict the risk level of diabetes by web-based application and nine attributes of patients data. The data which is used in this research are 1450 patients that are taken from RSD BALUNG JEMBER, by collecting data from 26 September 2014 until 30 April 2015. This research uses performance measuring from two methods by using discrimination score with ROC curve (Receiver Operating Characteristic).  On the experiment result, it showed that two methods, Regression Logistic method and Bayesian method, have different performance excess score and are good at both. From the highest accuracy measurement and ROC using the same dataset, where the excess of Bayesian has the highest accuracy with 0,91 in the score while Regression Logistic method has the highest ROC score with 0.988, meanwhile on Bayesian, the ROC is 0.964. In this research, the plus of using Bayesian is not only can use categorical but also numerical.
Analysis on Handwritten Document Text to Identify Human Personality Characteristics by Using Preprocessing and Feature Extraction Perdanasari, Lukie; Sigit, Riyanto; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 6, No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (677.827 KB) | DOI: 10.24003/emitter.v6i2.289

Abstract

It is important that a company uses the right means to recruit employees with certain personal characteristics as needed. Nowadays, the techniques to respond to psychological tests on people’s characteristics have been widely understood by most job applicants, so that it is difficult to know their true personality. Graphology is a way to identify a person’s characteristics by analyzing the handwriting from the document text made by the applicant. The two types of text document of each applicant are obtained from people of different ages and different writing times. The methods of graphology used in this research for identifying the handwriting are preprocessing and feature extraction. The preprocessing method uses projection integrals, shear transformations, and template matching. While the feature extraction process applies 10 features, they are, margins, line spacing, space between words, size of writing, style, zone, direction of writing, slope of writing, width of writing and shape of the letter. The result of the experiment from five writers shows the accuracy of writing identification equals to 82%, while personality identification equals to 67,4%.
Terapi Bedah pada Fraktus Patologis Tulang Panjang Ekstremitas Di Rumah Sakit Kanker Dharmais Basuki, Achmad
Indonesian Journal of Cancer Vol 1, No 3 (2007): Jul - Sep 2007
Publisher : National Cancer Center - Dharmais Cancer Hospital

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1346.017 KB) | DOI: 10.33371/ijoc.v1i3.19

Abstract

Fraktur patologis tulang panjang ekstremitas pada pasien kanker metastasis tulang mengakibatkan morbiditas yang sangat serius. Kejadian ini terus meningkat dengan semakin baiknya harapan hidup pasien kanker. Tujuan pengobatan pasien penyakit kanker pada stadium lanjut adalah meningkatnya kualitas hidup yaitu : hilang rasa nyeri, mencegah terjadi fraktur patologis dan memudahkan perawatan medis. Intervensi bedah lebih agresif pada pasien dengan metastasis tulang yang risiko fraktur (impending fracture) dapat mencegah pasien jatuh ke keadaan yang lebih buruk dan pasien dapat melajutkan terapi tambahan.Pada evaluasi, didapat 24 pasien fraktur patologis pada pasien kanker metastasis tulang. 17 pasien dilakukan operasi sisanya 7 pasien tidak dioperasi. Dari 24 pasien, 9 pasien fraktur patologis ekstremitas atas dan 15 pasien fraktur patologis ekstremitas bawah. Paska operasi, pasien dapat mobilisasi dan rasa nyeri hilang. Penatalaksanaan bedah pada fraktur patologis metastasis tulang sebaiknya berpegang pada keadaan umum pasien, bukan pada harapan hidup pasien.Kata kunci: fraktur patologis, kanker, risiko fraktur
Content-Dependent Image Search System for Aggregation of Color, Shape and Texture Features Kurniasari, Arvita Agus; Barakbah, Ali Ridho; Basuki, Achmad
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.
Co-Authors A.A. Ketut Agung Cahyawan W Aditya, Sri Praba Agus Supriyadi Ali Awaludin Ali Ridho Barakbah Ardhiantika, Pitra As'ad, Sholihin As'ad, Sholihin Bagus Adi Pamungkas Bambang Suhendro, Bambang Bima Sena Bayu Dewantara Budi Utomo Citra Nurina Prabiantissa Dadet Pramadihanto Debianto, Ikhsan Debianto, Ikhsan Desi Amirullah, Desi Dianawanti, Dianawanti Duanda, Prada Dwi Susanto Edy Purwanto Errol U. Hutagalung Fikri Aulia, Fikri Gumilang B, R. Lintang Guznan, Mahendra Hantara, Hana Imam, Eriria Indra Adji Sulistijono Jabbar Nendra Putra, Jabbar Kurniasari, Arvita Agus Kushendrahayu, Kartika Kusno Adi Sambowo Kuspadwati, Andriyani Budi Lakmi Makarti, Lakmi Mindrasari, Pricillia Muhammad Muttaqin Muhammad Nashirudin, Muhammad Neny Kurniati Nugraha, Aditya Nugraha Pamenang, Muhammad Unggul Perdanasari, Lukie Pramanto, Aris Cholid Baicuni Puji Astutik, Herna Puji Astutik, Herna Pujianto Pujianto Putri, Rismaya Nurrahma R. Susworo Rahagiyanto, Angga Ramadhani, Muhammad Fauzan Ramadhani, Muhammad Fauzan Riyanto Sigit, Riyanto Royani, Itzna Fauziah Roziqin, Mochammad Choirur Salfikar, Inzar Sasongko, Harjun Adhitya Sesulihatien, Wahjoe Tjatur Setiono Setiono Setiya Budi, Agus Setyowati Setyowati Sunarmasto, Sunarmasto Sunarmasto, Sunarmasto Suprapto Siswosukarto Tessy Badriyah, Tessy Tita Karlita Tri Harsono Tri Pranoto, Ferry Wicaksono, Adi Purwoko Wicaksono, Andri Permana