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All Journal Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics INOVTEK Polbeng - Seri Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Informatika dan Rekayasa Elektronik Indonesian Journal of Electrical Engineering and Computer Science
Riyanto Sigit
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Electrical & Electronics Engineering Engineering

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Improved echocardiography segmentation using active shape model and optical flow Riyanto Sigit; Calvin Alfa Roji; Tri Harsono; Son Kuswadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11821

Abstract

Heart disease is one of the most dangerous diseases that threaten human life. The doctor uses echocardiography to analyze heart disease. The result of echocardiography test is a video that shows the movement of the heart rate. The result of echocardiography test indicates whether the patient’s heart is normal or not by identifying a heart cavity area. Commonly it is determined by a doctor based on his own accuracy and experience. Therefore, many methods to do heart segmentation is appearing. But, the methods are a bit slow and less precise. Thus, a system that can help the doctor to analyze it better is needed. This research will develop a system that can analyze the heart rate-motion and automatically measure heart cavity area better than the existing method. This paper proposes an improved system for cardiac segmentation using median high boost filter to increase image quality, followed by the use of an active shape model and optical flow. The segmentation of the heart rate-motion and auto measurement of the heart cavity area is expected to help the doctor to analyze the condition of the patient with better accuracy. Experimental result validated our approach.
DETEKSI KUALITAS BERAS MENGGUNAKAN SEGMENTASI CITRA BERDASARKAN PECAHAN BULIR DAN SEBARAN WARNA Eko Supriyadi; Achmad Basuki; Riyanto Sigit
Jurnal Informatika dan Rekayasa Elektronik Vol. 3 No. 1 (2020): JIRE April 2020
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v3i1.210

Abstract

Ada banyak kasus penipuan dalam pemalsuan beras dengan mencampur beras berkualitas baik dengan beras berkualitas rendah untuk kenaikan harga. Untuk melindungi masyarakat dari pemalsuan, kami melakukan penelitian untuk mendeteksi kualitas beras yang nantinya dapat membantu masyarakat untuk dapat membedakan kualitas baik dan buruk. Penelitian ini menyajikan sistem pemrosesan citra beras berbiaya rendah untuk menilai kualitas beras. Banyak faktor yang mempengaruhi kualitas beras seperti fragmen biji-bijian, warna yang tidak seragam, bau dan faktor lainnya. Penelitian ini menggunakan prosentase butiran beras pecah dan keseragaman warna untuk menentukan kualitas beras. Kami mengusulkan fitur tekstur dengan segmentasi Otsu untuk menentukan jumlah butiran pecah dan distribusi warna untuk menentukan seragam warna. Hasil klasifikasi menggunakan validasi K Folddengan k=10 pada data asli menunjukkan hasil K-Nearest Neigbour memiliki akurasi 99,87%.
HAND GESTURE RECOGNITION FOR INDONESIAN SIGN LANGUAGE INTERPRETER SYSTEM WITH MYO ARMBAND USING SUPPORT VECTOR MACHINE Aditiya Anwar; Achmad Basuki; Riyanto Sigit
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 7, No 2 (2020)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v7i2.320

Abstract

Hand gestures are the communication ways for the deaf people and the other. Each hand gesture has a different meaning.  In order to better communicate, we need an automatic translator who can recognize hand movements as a word or sentence in communicating with deaf people. This paper proposes a system to recognize hand gestures based on Indonesian Sign Language Standard. This system uses Myo Armband as hand gesture sensors. Myo Armband has 21 sensors to express the hand gesture data. Recognition process uses a Support Vector Machine (SVM) to classify the hand gesture based on the dataset of Indonesian Sign Language Standard. SVM yields the accuracy of 86.59% to recognize hand gestures as sign language.Keywords: Hand Gesture Recognition, Feature Extraction, Indonesian Sign Language, Myo Armband, Moment Invariant
Implementation of Myo Armband on Mobile Application for Post-stroke Patient Hand Rehabilitation Tri Bintang Dewantoro; Riyanto Sigit; Heny Yuniarti; Yudith Dian Prawitri; Fridastya Andini Pamudyaningrum; Mahaputra Ilham Awal
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (720.059 KB) | DOI: 10.11591/eecsi.v5.1585

Abstract

Medical rehabilitation is one of the efforts to restore motor function of post-stroke patients, but the biggest factor that makes patients quickly restore motor function by active patient movement exercises. The movement in question is the movement carried out every day outside medical rehabilitation at the hospital. On the other hand, patients are reluctant to do therapy independently outside the hospital, because there is no tool that supports patients to do so. So, we need a device that helps patients to do therapy independently. The device is connected to Myo Armband to read the gestures of the patient by looking at the EMG signal from the patient's hand. Then the system performs matching gestures during therapy with EMG signal data that has been trained. The motion matching is done by calculating the Euclidean distance between the two EMG signal data obtained from the Myo Armband device. From the results of the tests carried out, the accuracy of movement matching results obtained an average accuracy of 89.67 percent for flexion-extension gestures and 82 percent for pronation-supination gestures. It can be concluded that Myo Armband in the Mobile Application can be used for Rehabilitation of post stroke patient hands.
Klasterisasi Kualitas Beras Berdasarkan Citra Pecahan Bulir Dan Sebaran Warna Eko Supriyadi; Achmad Basuki; Riyanto Sigit
Jurnal Inovtek Polbeng Seri Informatika Vol 6, No 1 (2021)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v6i1.1657

Abstract

Intisari – Berassebagai bahan pokok makanan masyarakat Indonesia , karena di dalam beras terdapat kandungan karbohidrat kompleks, serta dapat memberikan berbagai zat gizi lain yang penting bagi tubuh. Masih banyak masyarakat yang berasumsi jika beras dalam keadaan bersih, tak berbau, dan memiliki harga lebih mahal, beras tersebut berkualitas baik, padahal belum tentu beras yang dimaksud tersebut mempunyai kualitas baik. Untuk itu dalam melakukan penelitian mendeteksi kualitas beras yang nantinya dapat membantu masyarakat untuk dapat membedakan kualitas baik dan buruk. Banyak faktor yang mempengaruhi kualitas beras seperti fragmen biji- bijian, warna yang tidak seragam, bau dan faktor lainnya. Penelitian ini menggunakan persentase buliran beras pecah dan keseragaman warna untuk menentukan kualitas beras. Penelitian ini menggunakan parameter buliran pecah dan distribusi warna yang selanjutnya  diproses klasterisasi dengan metode K-Means di mana nilai klaster dijadikan sebagai nilai class untuk melabeli jenis beras sesuai mutu dari medium 1,2, dan 3. Selanjutnya data yang terlabel klaster dilakukan proses klasifikasi untuk mendapatkan akurasi yang terbaik, dan metode klasifikasi yang terbaik adalah neural network sebesar 99,85%.Kata kunci – kualitas beras, citra beras, K-Mean, Neural Network.
Penerapan Fuzzy Tsukamoto pada Alat Deteksi Penyakit Hipoksemia, Hipotermia, Hipertensi, dan Diabetes untuk Health Care Kiosk Heny Yuniarti; Riyanto Sigit; Muhammad Aunur Rofiq
Journal of Applied Informatics and Computing Vol 4 No 2 (2020): Desember 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v4i2.2643

Abstract

Most of people in Indonesia need fast, right, and accurate health medical service. But as we know in hospital takes many time just for check our health condition. This research make a Health Care Kiosk for medical check up, without using a doctor, so that kiosk can detect many deseases automatically. This research focused on 4 deseases such as hypothermia, hypoxemia, hypertension and diabetes. System using Embedded PC for data processing automatically. There are many medical sensor such as thermometer, heart rate sensor, blood pressure sensor, SPO2 sensor, and glucometer sensor for check health condition. System can make a decision if that patient healthy or not automatically because it uses fuzzy method for that decision. The result of this paper is this system can detect every deseases and that error for each sensor are body temperature has 1.05% error, oxygen level has 1.90% error, heart rate has 5.78% error, blood pressure sistolic has 4.16% error, blood pressure diastolic has 4.87% error and glucosa level in blood has 4.01% error. This system integrated with database MySQL for save that result. The accuracy from fuzzy method is 100% right and fuzzy tsukamoto can process input well.
Veins projection performance based on ultrasonic distance sensor in various surface objects I Putu Adi Surya Gunawan; Riyanto Sigit; Agus Indra Gunawan
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1362-1370

Abstract

Intravenous therapy aims to inject fluids such as medicine or nutritions into the body via vein vessel. This procedure is needed in various cases whether in an ordinary or emergency. Every person has a different difficulty level thus a nurse usually encountered a problem when locating the position of vein vessel. A visualization device that able to work in realtime and have high mobility is really necessary for an emergency situation to speed up the intravenous access. In this study, a stand-alone veins visualization system was developed. The back-projection method that can adjust based on distance was used to speed up the visualization process. The distance between the device and the object is obtained by an ultrasonic distance sensor. The results of this projection method with a flat surface have maximum shift of 0.48 mm. While on various surfaces, projection shifts under 0.9 mm reach 89% from 140 measurement points. Projection shifts that reach more than 0.9 mm occurred due to the sensor readings are on steep curvature or large angles between segments and sensors.
Hand Wrist Bone Identification Using Quadrant Ballon Snake Riyanto Sigit; Moch. Rochmad; Tri Harsono; Farah Devi Isnanda
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i2.pp335-342

Abstract

In this research, hand wrist bone Identification for human forensic is discussed. Hand wrist bone is one of the effective methods used in the forensic science for age identification. There are four techniques used in this research: cropping image, preprocessing, Quadrant Ballon Snake and identification. The first step is to crop an image on metaphysis and epiphysis bone. The second step is preprocessing using morphology and edge detection. The third step is to apply Quadrant Ballon Snake to segment hand wrist bone. The last step is to use ratio metaphysis and epiphysis to identify a person. The performance segmentation for assessment hand wrist bone showed an average age identification 91%, bone age metaphysis 95% and bone age epiphysis 95%. The experiments resulted in the fact that Quadrant Ballon Snake method is able to find and improve the segmentation of hand wrist bone images accurately. This indicates that this method is effective for segmenting hand wrist bone.
Automatic Cardiac Segmentation Using Triangle and Optical Flow Riyanto Sigit; Ali Ridho Barakbah; Indra Adji Sulistijono; Adam Shidqul Aziz
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i2.pp315-326

Abstract

Cardiac function assessment plays an important role in daily cardiology and ultrasound. Full automatic cardiac segmentation is a challenging study because cardiac ultrasound imaging has low contrast and irregular moves. In this research, full automatic cardiac segmentation for cardiac diseases is presented. The technique used Initial Center Boundary, Pre-processing, Triangle Segmentation and Optical Flow. The first step is determining the initial center boundary. The second step is using Pre-processing to eliminate noise. The third step is Triangle Segmentation to detect cardiac boundary and reconstruct the accurate border. The last step is applying Optical Flow method to detect and track the border for every frame in a cardiac video. The performance segmentation for assessment errors cardiac cavity obtained an average triangle 8.18%, snake 19.94% and watershed 15.97%. The experiments showed that triangle method is able to find and improve the segmentation of cardiac cavity images with accurate. The result can be seen that error between system and average of users is only less than 5.6%. This indicates that this method is effective to segment and tracking cardiac cavity in a cardiac video.
Implementation of optical flow: good feature definition for tracking of heart cavity Anwar Anwar; Riyanto Sigit; Achmad Basuki; I Putu Adi Surya Gunawan
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp1057-1065

Abstract

Echocardiography is a method of examination using high-frequency sound waves to capture images of the heart organ structure. Echocardiography video is used by a doctor to analyze heart wall cavity movements and identify heart disease. Several points of view including the long axis, the two and four cavities in the left ventricle can be used in the examination of heart function. Cardiac assessment is still performed conventionally, which requires a level of thoroughness. This research proposes a method for tracking the movement of the heart wall. In this method, the good feature was defined only in the first frame. Furthermore, the whole frame will be processed by the optical flow method. Good feature definition consists of image enhancement, segmentation and tracking processes using the optical flow. Furthermore, the calculation of contour similarity from the proposed method by forming contour manually using 24 point initialization to draw the heart cavity. The proposed method shows the calculation results with a sensitivity of 90% and an accuracy of 87.451%.
Co-Authors Achmad Basuki Aditiya Anwar Agus Indra Gunawan Ahmad Fauzi Makarim Ali Ridho Barakbah Anwar Anwar Anwar Arya Brahmanta Aziz, Adam Shidqul Bima Sena Bayu Dewantara Calvin Alfa Roji Eko Supriyadi Farah Devi Isnanda Fildzah Aure Gehara Zhafirah Fridastya Andini Pamudyaningrum Heny Yuniarti I Putu Adi Surya Gunawan Indra Adji Sulistijono Mahaputra Ilham Awal Moch. Rochmad Mohamad Walid Asyhari Muhammad Anwar Sanusi Muhammad Aunur Rofiq Prawitri, Yudith Dian Rika Rokhana Setiawardhana Son Kuswadi Taufik Hidayat Tita Karlita Tri Bintang Dewantoro Tri Harsono