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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Media Kesehatan Masyarakat Indonesia BERKALA FISIKA MATEMATIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS YOUNGSTER PHYSICS JOURNAL Jurnal Sistem Komputer Telematika : Jurnal Informatika dan Teknologi Informasi Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Imejing Diagnostik Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Manajemen Kesehatan Indonesia Jurnal Teknologi dan Sistem Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal Of Vocational Health Studies Jurnal Penelitian Pendidikan IPA (JPPIPA) Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Teknoinfo Journal of Physics and Its Applications Jurnal Sisfokom (Sistem Informasi dan Komputer) JURTEKSI Unnes Journal of Public Health Jurnal Komunika : Jurnal Komunikasi, Media dan Informatika JARES (Journal of Academic Research and Sciences) Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Information Systems and Informatics Jurnal Teknik Elektro dan Komputasi (ELKOM) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Aisyah : Jurnal Ilmu Kesehatan Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Jurnal Multidisiplin Madani (MUDIMA) East Asian Journal of Multidisciplinary Research (EAJMR) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Makara Journal of Technology International Journal Of Health And Social Behavior
Kusworo Adi
Jurusan Fisika, Fakultas Sains Dan Matematika, Universitas Diponegoro Jl. Prof. Soedharto, SH., Tembalang, Semarang, Jawa Tengah
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Journal : YOUNGSTER PHYSICS JOURNAL

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ANALISIS TEKSTUR CITRA MIKROSKOPIS KANKER PARU MENGGUNAKAN METODE GRAY LEVEL CO-OCCURANCE MATRIX (GLCM) DAN TRANFORMASI WAVELET DENGAN KLASIFIKASI NAIVE BAYES Rizky Ayomi Syifa; Kusworo Adi; Catur Edi Widodo
Youngster Physics Journal Vol 5, No 4 (2016): Youngster Physics Journal Oktober 2016
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

This research, conduct the lung cancer detection system on a microscopic image. The microscopic image used is the result from lung biopsy. If there is a cancerous tissue in the image of lung biopsy, the texture will be irregular, while the image of the normal lung biopsy will have a regular texture. The purpose of this reserach is to develope the lung cancer detection system and also to count the performance of the lung cancer detection system. The clasification process uses two methods, Gray Level Co-Occurance Matrix (GLCM) and Daubechies Wavelet Transform (db1). The Daubechies wavelet transformation is used in decomposition in level 4, while the offset of GLCM is 6. The feature extraction process is done in the transformation wavelet using the 4 subbands, approximation, horizontal Detils coefficients, vertical Detil coefficients and diagonal Detil coefficients, and the the feature extraction of GLCM uses the contrast, correlation, homogenity and energi as the parameter. The naïve bayes classification requires 2 parameter input, do a classification is 4 combination from each method of feature extraction. The result of this research is to extent the level of accuracy for the extraction of the feature extraction in 71,42% wavelet transformation method for the combination coefficients approximation-diagonal Detil coefficients and 80% accuration of GLCM method for the combination of homogeneity-correlation.
Rancang bangun penghitung dan pengidentifikasi kendaraan menggunakan Multiple Object Tracking Laila Rahmawati; Kusworo Adi
Youngster Physics Journal Vol 6, No 1 (2017): Youngster Physics Journal Januari 2017
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Detection of a vehicle with a video camera is one accurate technology for detecting vehicles efficiently and can be used for large-scale data collection. This study has been conducted implementation of counters and  identifiers vehicles on the highway using multiple object tracking. The system uses an algorithm Gaussian mixture models and Kalman filter to detect and track the position, speed, direction of motion and size of vehicles from time to time in each image frame. The process of counting and identifying the vehicle consists of several stages of image acquisition, object detection using a Gaussian mixture models, morphology, object tracking using a Kalman filter and counting as well as the identification of the vehicle. The results of system performance is obtained by calculating the value of accuracy. Best performance results from the system counters and identifiers of vehicles on the highway using multiple object tracking obtained by the time of the morning and the worst at night. The results of the performance measurement system and vehicle identifiers using multiple object tracking accuracy of the results obtained on the morning of 94%, by 90% during the day, in the afternoon by 85%, and the evenings of 59%.Keywords: Counters and vehicle identifiers, multiple object tracking, Gaussian mixture models, Kalman Filter
PENGHITUNGAN OTOMATIS JUMLAH SEL DARAH MERAH DAN IDENTIFIKASI FASE PLASMODIUM FALCIPARUM MENGGUNAKAN OPERASI MORFOLOGI Adi Pamungkas; Kusworo Adi; Choirul Anam
Youngster Physics Journal Vol 1, No 1 (2012): Youngster Physics Journal Oktober 2012
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Malaria disease still a public health issue in Indonesia. The incidence of malaria in Indonesia is increasing every year. The cause of malaria is a parasite of the genus plasmodium that infected red blood cells through the bite of Anopheles mosquitoes. One of plasmodium type that often the cause of malaria in Indonesia is the plasmodium falciparum. This type of plasmodium causes malignant tertian malaria which threatening for the sufferer’s life. This study’s function is to design a program that capable automatically to calculate the total number of red blood cells, the number of parasites, and identified the plasmodium falciparum phase. The image processing of red blood cells in digital using morphological operations. The results of the testing program has been designed showed the correlation coefficient for counting the total number of red blood cells is 0.997, the validation value for parasit counting is 87.5%, and validation value for phase identification of plasmodium falciparum is 87.5%. Key words : red blood cell, falciparum, calculation, identification, automatic http://ejournal-s1.undip.ac.id/index.php/bfd/article/view/63
IMPLEMENTASI OBJECT TRACKING UNTUK MENDETEKSI DAN MENGHITUNG JUMLAH KENDARAAN SECARA OTOMATIS MENGGUNAKAN METODE KALMAN FILTER DAN GAUSSIAN MIXTURE MODEL Havez Vazirani Al Kautsar; Kusworo Adi
Youngster Physics Journal Vol 5, No 1 (2016): Youngster Physics Journal Januari 2016
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Traffic density can be controlled by obtaining and managing the data of the traffic flows on the highway. Generally, the process of data acquisition of the traffic flows which passing on the highway are still done manually by assigning some officers to be on the highway and count each of passing vehicle, then divided by a certain time frame. This manual counting are still have many weaknesses such as time of collecting data become longer, and need much amount of the human resources. Based on these conditions, needs an accurate automatic vehicle detection and counting system as traffic monitors, traffic controllers and traffic analysis. At this time, it has been developed a vehicle detection system using a hardware system such as using sensors, Radio Frequency Identifier or other hardware which integrated by software in the microcontroller and works automatically to detect the speed and count the number of passing vehicles on the highway. The weaknesses of these detectors can only detect at the narrow range, design of the system, the complexity of the operation, and also has a significant operational cost. Based on those system weaknesses, this study was developed with a focus of designing the detection system and the vehicle counter system using Kalman filter and Gaussian Mixture Models (GMM) method. This system get the most accurate results in the morning (10,000-25,000 lux illumination) with F1 Score value of 0.91111, while counting the vehicles most inaccurate happen at night (illumination from 0.27 to 1.0 lux) with F1 Score only 0.16071.Keywords: Traffic flows data, vehicle counter system, Object Tracking, Gaussian Mixture Model, Kalman Filter.
KLASIFIKASI DAERAH LONGSOR BERBASIS PENGOLAHAN CITRA MENGGUNAKAN JARINGAN SYARAF TIRUAN PROPAGASI BALIK Putri Nuriskianti; Kusworo Adi; Tony Yulianto
Youngster Physics Journal Vol 4, No 2 (2015): Youngster Physics Journal April 2015
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Landslides are natural events that occur due to the ground movement of the earth's surface. The movement influenced by its constituent such as soil type, land use and intensity of rainfall in some place that causes a material such as ground was moving. Research on landslide done based on field surveys. The potential of a region in the category of landslides can be done by mapping parameters - parameters of landslides in the form of a calculation using the image of a network system that has been trained to predict the condition of an area.Image processing is done by segmenting color for any information presented in an image of landslides parameters. The color segmentation results performed labeling process to represent the information in the image. Then the landslides indices obtained from the manual calculation of weighting parameters. The result of the calculation is used as an instructional manual for the neural network. Where the value of the index 1 is the lowest level of landslide or safety category. While the index level 5 is the highest landslide or category of highly vulnerable to landslides. To process the data from the manual calculation in artificial neural network using backpropagation algorithm.The research data was training data and testing of tissue obtained from the manual calculation of weighting parameters landslides. Network training successfully conducted with a total accuration (index normal manual landslides and landslide index network) of 100% and accuration of test results 91,2% network. In the training data used 96 samples of data and test data as much as 34 data.Keywords: Landslide index, color segmentation, artificial neural network.
OTOMASI SISTEM DESTILASI MENGGUNAKAN PLC OMRON CP1H DAN KONTROL SUHU DENGAN KENDALI AUTO TUNING PID DALAM PENAMPIL SCADA Tito Rano Pradibto; Kusworo Adi
Youngster Physics Journal Vol 4, No 4 (2015): Youngster Physics Journal Oktober 2015
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Industrial world today can't be separated with the problem of automation for various production facilities, one of them is the process of distillation in industry or the oil refining industry. Distillation is the process of separating substance by boiling point, where the temperature becomes the focal point of the phase that change process so it to control of substances that aims to keep the temperature value in the range of desired values. In this study using a multilevel distillation system, so it has two set of controling temperature points. Operation of distillation system automatically works with the help of controls Service such as PLC OMRON CP1H and temperature control with auto tuning PID (Proportional Integral Derivative). The system is equipped with SCADA (Supervisory Control and Data Acquisition) and data logger so as to facilitate the operation of automation and configuration PID parameters such as proportional coefficient (Kp), the integral time (Ti), the time derivative (Td). Modeling materials processed using methanol with 64 oC boiling point and ethanol with a boiling point of 78 °C. Results of the research showed us that the temperature control system can use the auto tuning PID controled by a PLC can be done, a good temperature control is obtained with a small error rate. auto tuning method is still having oscillations, but a PID value will be automatically calculated quickly so that a constant parameter values obtained to get the stability of temperature. The value of maximum overshoot (Mp) of auto tuning of 9,09% and error steady state (ESS) of 1.53%. Results of calculation from the value of parameter auto tuning PID used as next tuning parameters and steady state response is obtained more quickly, with Mp of 4,61% and 0% of ESS.
SEGMENTASI CITRA MEDIS UNTUK PENGENALAN OBJEK KANKER MENGGUNAKAN METODE ACTIVE CONTOUR Fatkhurrazi Basyid; Kusworo Adi
Youngster Physics Journal Vol 3, No 3 (2014): Youngster Physics Journal Juli 2014
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Cancer diseases characterized by abnormal cell cycle, in which the body cells grow out of control (cell division beyond the normal limits) and invade nearby healthy tissue. Cancer cells are actively dividing sensitive to radiation exposure, so that cancer can be treated with a high dose of radiation that is commonly referred to radiotherapy. High-dose radiation is damaging tissue, therefore radiotherapy should be planned carefully. Dose in cancer cells should be precise and dangerous organs (organs at risk) should not receive high doses. Contouring is the process of determining the volume of cancer and other organs at risk. Research on contouring is done by developing a step-by-step algorithm that is able to localize the area detected as cancer and also borders cancer, so it is visually identifiable characteristics and forms of cancer. Active contour image segmentation methods used to separate and identify cancer cells with healthy cells. Active contour is able to recognize the limits of automatic edge, so as to know the boundary between cancer cells with healthy cells. Determination of volume and visualization of cancer is done by segmenting the image of each piece, then each piece of the image reconstruction process is carried out to obtain the volume visualization of cancer and dangerous organ in three dimensions. The results showed that the active contour segmentation method can perform image segmentation for multi-region with objects, objects that are close together but are sensitive to image noises.Keywords : cancer, radiotherapy, segmentation, active contour
KEMAMPUAN SEGMENTASI MENGGUNAKAN METODE DRLSE (DISTANCE REGULARIZED LEVEL SET EVOLUTION) TERHADAP PENGARUH DERAU Abdillah Noor Fajrin; Kusworo Adi; Choirul Anam
Youngster Physics Journal Vol 1, No 1 (2012): Youngster Physics Journal Oktober 2012
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Abstract DRLSE (Distance Regularized Level Set Evolution) Segmentation has been tested in this research under salt & pepper noise, gaussian and speckle influence. DRLSE uses curve fluctuations to carried segmentation. First process, image was be activated by using each noise (gaussian, speckle, and salt & pepper). Afterwards, it was be carried to segmentation under DRLSE. Image activating by distinct noise will shows us DRLSE performances under noise influences. The result show us maximal variants value of following noise as follow: in the image gourd is salt & pepper 0.002, gaussian 0.002 and speckle 0.007. image dua objek is salt & pepper 0.004, gaussian 0.0001 and speckle 0.008. Keywords :segmentation,salt & pepper, gaussian, speckle.
SISTEM IDENTIFIKASI KUALITAS DAGING SAPI DENGAN METODE PENGOLAHAN CITRA MENGGUNAKAN TELEPON SELULER DENGAN SISTEM OPERASI ANDROID Nurul Huda Prasetyo; Kusworo Adi
Youngster Physics Journal Vol 5, No 4 (2016): Youngster Physics Journal Oktober 2016
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Research on Beef quality identification system with image processing method using android smartphone had been carried out at Diponegoro University electronic and instrument Physics Laboratory. In this research, a segmentation algorithm extents and extent of meat and fat classification decision tree. Which can be run on smart phones with Android as the operating system. Characteristics that are used to distinguish the quality of beef (marbling score) in this study is the extent of fat,and meat. From the research that has been done can be concluded that the developed system is able to perform image acquisition and identifying beef marbling score well. The system is designed using decision tree-based classification method and the results obtained in the testing accuracy of 90% and 84% on the acquisition of training at a distance of 30 cm.
DETEKSI EFUSI PLEURA PADA CITRA THORAX MENGUNAKAN JARINGAN SYARAF TIRUAN PROPAGASI BALIK MELALUI EKSTRAKSI CIRI BINER Elvira Situmorang; Kusworo Adi; Evi Setiawati
Youngster Physics Journal Vol 3, No 4 (2014): Youngster Physics Journal Oktober 2014
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

The research about detection pleural effusion of the thoracic using neural network back propagation by binary feature extraction has been done. A common cause of pleural effusion disease is cancer. It is estimated that pleural effusion malignant affects 150,000 people every year in the United States. The normal pleural space only has a few milliliters of liquid that helps lubricate of the lungs during breathing. Pleural effusion (large amounts of liquid in the pleural space) can lead to a partial or complete compression of the lung. The difficulty to distinguish excess accumulation of fluid in the pleural cavity should be minimized by radiologist. This research contributes interpretation pleural effusion in the thoracic and reduces doubts of doctor in the treatment of patients. The purpose of this research is to develop algorithms to identify pleural effusion using artificial neural networks back propagation by binary feature extraction the thoracic. Binary feature extraction is obtained from the level set segmentation. The process of image enhancement by histogram equalization and contrast enhancement should be performed before the level set segmentation process. Binary feature extraction patterns were training on ANN was taken from 5% until 25% of costophrenic angle in the thoracic. Neural network can recognize the characteristic patterns of the binary feature 15% are well trained. Validation ANN pattern training by up to 100%, while process of testing the ANN is able to identify 14 data from 15 test data to test validation value reaches 93.33% on the condition of  setting 2 hidden layers, each of hidden layer contain 10 neurons. Keywords: Pleural effusion, Binary feature extraction, Artificial neural networks, Histogram, level set segmentation.
Co-Authors - Magister Sistem Informasi Universitas Diponegoro, Vincencius Gunawan S.K Abdillah Noor Fajrin Achmad Widodo Adi Pamungkas Adian Fatchur Rohim Adila Safitri Agus Atabik Anwar Agustini, Eka Puji Agvion Virsaw Alfajri, Willy Bima Andrian Bayu Suksmono Andriyan B. Suksmono Andriyan Suksmono Andriyan Suksmono, Andriyan Antono Suryo Putro Apoina Kartini Aprilia Ayu Andarinny Ardhi, Ovide Decroly Wisnu Ari Bawono Putranto Arief Rachman Aris P Widodo Aris Puji Widodo Aris Puji Widodo Aris Sugiharto Ary Setyadi Aryasa, Komang Budi Atik Zilziana Muflihati Noor Baital, Muhammad Sawal Basuki Wibowo Beta Noranita Cahya Tri Purnami Cahya Tri Purnami Carissa Devina Usman Catur Adi Widodo Catur Edi Widodo Chakim Annubaha Choirul Anam Choirul Anam AM Diponegoro Dartini Dartini Dartini Dartini, Dartini Dedi Apriyandi Dedi Sepriana Delfia, Fila Dewi, Adinda Cipta Dian Anggraini Didi Supriyadi Dwi Ely Kurniawan Dwi Rochmayanti Dyah Apriliani Eka Vickraien Dangkua, Eka Vickraien Eko Adi Sarwoko Eko Sediono Elvira Situmorang Esa Prakasa, Esa Evi Setiawati Evita Ayu Suryaningtyas Faikhin . Faisal Rahman Fanny, Nabilatul Fardana, Nouvel Izza Farid Agushybana Farid Farid Agushybana Fatkhurrazi Basyid Figur Humani Fila Delfia Frida Fallo Gatot Murti Wibowo Gatot Murti Wibowo, Gatot Murti Hadyan Arifianto Hariri, Ahmad Harnanto, Rudy Haryati Haryati Hastuti, Dyah Dewi Havez Vazirani Al Kautsar Hendra Gunawan HENDRA GUNAWAN B11211055 Hernowo Danusaputro Ibrahim, Muhammad Rivani Imam Syafii Ircham Ali Isnain Gunadi Isnain Gunadi Jatmiko Endor Suseno Jatmiko Endro Suseno Jatmiko Endro Suseno Jayawarsa, A.A. Ketut Julianto, Dewa Rizki Rahmat Laila Rahmawati Linda Nuryanti M.Irwan Katili Mailia Putri Utami Mailia Putri Utami MAIZZA NADIA PUTR Maratullatifah, Yulaikha MARTINI Martini Martini Mengko, Tati L.R. Muhammad Ikhsan Nahdi Saubari Nanang Sulaksono, Nanang Natalia Kristiani Nava Muzdalifah Nelly Mirnasari Neneng Neneng Nina Dwi Astuti Noor Azizah Nugroho Adhi Santoso Nugroho, Irwan Andriyanto Nur Hamid Nurul Firdausi Nuzula, Nurul Firdausi Nurul Huda Prasetyo Oky Dwi Nurhayati Pamungkas, Ardian Prakasa, Fawwaz Bimo Puji Widodo, Aris Purwanto Purwanto Puspita Sari, Kiki Putri Nuriskianti Qoriani Widayati R Rizal Isnanto Rachmat Gernowo Rachmatullah, Robby Rahmat Gernowo Rahmat Gernowo Rasyid Rasyid, Rasyid Retnaningsih Soeprobowati, Tri Ria Amitasari Rima Ayuning Ratri Riris Trima Derita Sari Rizky Ayomi Syifa Rr. Tony Yulianto Saiful Widianto Salsabila Naqiyah Sari, Kiki Puspita Septya Maharani, Septya Setyowati Setyowati Shahmirul Hafizullah Imanuddin Sidin Hariyanto Sifaunajah, Agus Siti A'isyah Siti Nur Endahyani Sri Bintang Pamungkas Suandari P.V.L Suryono Suryono Suseno, Jatmiko Endor Sutopo Patria Jati Tati Mengko Tati Mengko, Tati Tito Rano Pradibto Toni Wijanarko Adi Putra Tri Mulyono Tri Retnaningsih Soeprobowati Tri Sandhika Jaya Tutur Urip Undari Nurkalis Vincencius Gunawan, Vincencius Vincensius Gunawan S.K. Wahyu Setia Budi Wahyudi Setiawan Wahyuni, Wilda Waliyansyah, Rahmat Robi Weirna Yusanti Wicaksono, Januar Agung Widagdo, Krisan Aprian Wisnu Ardhi, Ovide Decroly Wiwit Agus Triyanto Yuliani Setyaningsih Zaenal Arifin Zaenul Muhlisin Zainal Bachrudin