riries rulaningtyas - Academia.edu (original) (raw)

Papers by riries rulaningtyas

AIP Conference Proceedings

Maize is the second most important agricultural commodity after rice. In Indonesia, maize is an a... more Maize is the second most important agricultural commodity after rice. In Indonesia, maize is an alternative complimentary food, even in some areas it is used as the main food. The future prospect, maize production was increased for national sufficient. However, there are obstacles for achieving it. One of them is the attack of pests and diseases. In this article, image classification on maize leaf diseases is presented. Image classification is a common task when performing image mining. However, classification without a visual explanation certainly makes it difficult for the user to understand the results. This article aims to classify as well as visually explanation the abnormality or emergence of maize leaf diseases. The research is divided into 2 steps: classification and visual explanation. Classification uses Convolutional Neural Network (CNN) Squeezenet while visual explanation uses Gradient-Weighted Class Activation Map (Grad-CAM). The data experiment used from PlantVillage dataset with 4 classes: healthy, blight, spots, and rust. The percentage of training , validation, and testing data was 60:20:20. Validation using 10 fold cross-validation. The novelty was apply the visual explanation using GradCAM on maize leaf diseases. Performance Measure for classification are 95.2%, 94.03%, and 94.28% for accuracy, precision and recall, respectively.

2021 International Conference on Instrumentation, Control, and Automation (ICA), 2021

Bio-impedance measurement of the test object is carried out by inserting an electric current and ... more Bio-impedance measurement of the test object is carried out by inserting an electric current and measuring its voltage using an electrode. The amount of bio-impedance is based on the assumption that the cell network is a conductor with extracellular and intracellular functions as resistors and capacitors. This principle is the basic for measuring the quality of meat using the bio-impedance spectroscopy method. In this research, bio-impedance spectroscopy has been built from the programable function generator AD9850, DC block which is composed of R and C components, each with a value of 1 kΩ and 100µF, Buffer and Voltage/current source (VCCS) which are composed of OPA 2134 Ammeters and The voltmeter are built from the AD620 differential amplifier, as well as the phase-gain detector from the AD8302. This device has been tried to determine the impedance and phase of objects of mutton, chicken, and beef. This device can distinguish the three types of meat and also provides information on changes in the characteristics of meat from day to day from the impedance value.

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2020

ABSTRACT Cervical cancer is a malignant tumour that attacks the female genital area originating f... more ABSTRACT Cervical cancer is a malignant tumour that attacks the female genital area originating from epithelial metaplasia in the squamous protocol junction area. One method of diagnosis of cervical cancer is to do a Pap smear examination by taking a cervical cell smear from the woman’s cervix and observing its cell development. However, examination of cervical cancer from Pap smear results usually takes a long time. This is because medical practitioners still rely on visual observations in the analysis of the results of Pap smear so that the results are subjective. Therefore, we need a programme that can help the classification process in establishing a diagnosis of cervical cancer with high accuracy results. In this study, a cervical cancer classification program was developed using a combination of the Grey Level Co-occurrence Matrix (GLCM) and Extreme Learning Machine (ELM) methods. There are three classes of cervical cell images classified, namely adenocarcinoma, High Squamous Intraepithelial Lesion (HSIL) and Squamous Cell Carcinoma (SCC). From the results of the training program obtained an accuracy 100% and from the testing program obtained an accuracy of 80%.

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 2021

Maize productivity growth is expected to increase by the year. However, there are obstacles to ac... more Maize productivity growth is expected to increase by the year. However, there are obstacles to achieving it. One of the causes is diseases attack. Generally, maize plant diseases are easily detected through the leaves. This article discusses maize leaf disease classification using computer vision with a convolutional neural network (CNN). It aims to compare the deep convolutional neural network (CNN) AlexNet and Squeezenet. The network also used optimization, stochastic gradient descent with momentum (SGDM). The dataset for this experiment was taken from PlantVillage with 3852 images with 4 classes i.e healthy, blight, spot, and rust. The data is divided into 3 parts: training, validation, and testing. Training and validation are 80%, the rest for testing. The results of training with cross-validation produce the best accuracy of 100% for AlexNet and Squeezenet. Furthermore, the best weights and biases are stored in the model for testing data classification. The recognition results ...

2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM), 2020

The process of identifying bacteria is an essential factor in the medical field. One of the germs... more The process of identifying bacteria is an essential factor in the medical field. One of the germs that cause lung damage in pneumonia is gram-negative bacteria. The convolutional neural network method is the newest approach to machine learning because it has a high degree of accuracy. But the drawback is due to his in-depth knowledge, the computation time for the training process takes a long time. The method offered in this research is automatic contrast addition in the preprocessing stage and the use of custom layers. Also, augmentation data added to increase the variation in the amount of data in the training process. In using custom layers, the objective is to obtain minimal computational training time while maintaining maximum accuracy values. The results show that an average accuracy around 98.59% with average training time around 01 minutes 56 seconds, average MSE 0.0274, RMSE 0.1693, and MAE 0.0185.

THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019, 2020

Hemoglobin is the protein molecule that binds oxygen in the blood. Hemoglobin level can be used a... more Hemoglobin is the protein molecule that binds oxygen in the blood. Hemoglobin level can be used as a benchmark of the human physiological condition, such as anemia, hypoxia, and postoperative bleeding. Generally, measurement of hemoglobin levels is performed by an invasive method that takes blood samples to be tested. This study offers a tele-monitoring system for measuring the hemoglobin level non-invasively, so it could reduce the possibility of infection or contamination to the body and can be monitored anywhere by using a website. This tele-monitoring device of non-invasive hemoglobin and oxygen saturation levels were designed by integrating the pulse oximetry sensor with signal conditioning circuit, Arduino Uno as a microcontroller, Ethernet module, an internet network, cloud server, and website. Pulse oximetry measured the oxygen saturation in the blood that indicate the vital state of human and became essential to determine the amount of hemoglobin level. The system performance in this study was tested on participants who had a good daily exercise and participants who never had daily activities to discover the correlation between hemoglobin levels with human physical activity and obtained 89% of accuracy. This system can be implemented as a personal device for monitoring the hemoglobin level and the oxygen saturation in daily used.

THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019, 2020

It has been developed successfully of multi-frequency bio-impedance devices using the AD9850 modu... more It has been developed successfully of multi-frequency bio-impedance devices using the AD9850 module. The devices are composed of AD9850 sin-wave generator module, High Pass Filter, VCCS, AD620A Instrument amplifier, AC to DC AD536A and Arduino Nano. The performance of the devices was tested with 10 variations of the load containing elements R and C. The results of the measurements were compared with the theoretical at frequencies less than 110 kHz resulting error less than 10%. The device can be used to calculate electrical impedance accurately from 10 Hz to 100 kHz.

Ship needs satellite communications systems accurately. Ship’s dynamics cause communications syst... more Ship needs satellite communications systems accurately. Ship’s dynamics cause communications system getting worse. These ship’s dynamic include rolling, pitching, and heading movement. This research made control systems using fuzzy logic to control antenna moving on ship become smooth and fast tracking to the satellite. The result showed that fuzzy logic had performace better than conventional controller (proposional integrad). Proposional integral controller showed setting time 5.84 seconds, rise time 12.96 seconds, maximum overshoot 1.3167%, error steady state 0.0023407 radians, but fuzzy logic controller that already designed had settling time 3.52 seconds, rise time 3.52 seconds, maximum overshoot 1.1768%, and error steady state 2.2204x10-16 radians.

2020 6th Information Technology International Seminar (ITIS), 2020

Image classification is one of the fundamental steps in digital image processing. Research in thi... more Image classification is one of the fundamental steps in digital image processing. Research in this area has received considerable attention, with photos shared on social media which are sometimes similar but have different identities. There are various classification methods proposed in the literature to improve accuracy. One important strategy is Convolutional Neural Networks (CNN). Although CNN is superior in pattern recognition, it has limitations inaccuracy. It requires additional training time, especially when dealing with variants in data generated from a large number of images but of similar properties. Therefore, this study aims to overcome this problem by proposing a modification of the CNN layer to increase the accuracy of the multi-class image classification. This research used four different flower species with similar patterns added from a public database. Each category consists of 400 colour images with different angles, backgrounds, and lighting conditions that provid...

A novel technique to identification of autoregressive moving average (ARMA)systems is proposed to... more A novel technique to identification of autoregressive moving average (ARMA)systems is proposed to increase the accuracy and speed of convergence for the system identification. The convergence speed of recursive least square algorithm (RLS) is solved under differential equations that needs all necessary information about the asymptotic behavior. Using RLS estimation, the convergence of parameters is able to the true values if the data of information vector growing to infinite. Therefore, the convergence of the parameters of the RLS algorithm takes time or needs a large number of sampling. In order to improve the accuracy and convergence speed of the estimated parameters, we propose a technique that modifies the QARXNN model by running two steps to identify the system hierarchically. The proposed method performs two steps: first, the system is identified by least square error (LSE) algorithm. Second, performs multiinput multi-output feedforward neural networks (MIMO-NN) to refine the ...

Darmabakti Cendekia: Journal of Community Service and Engagements, 2020

Background: Posyandu is one of the Indonesian government’s attempt in order to monitor and improv... more Background: Posyandu is one of the Indonesian government’s attempt in order to monitor and improve the health and life quality of the community, especially infant. However, the implementation of Posyandu is facing some issues such as low effectiveness and low accuracy during the data collecting process of the infant’s growth and development. Purpose: This study aims to develop an automatic telehealth care product in order to help to increase the effectivity and accuracy in the implementation of Posyandu. Methods: (1) Development of the Telehealth Care Posyandu Application, (2) Implementation of the application in the form of social service program. Result: (1) “Toddler” Telehealth Care Application based in Android and ICT was buith with artificial intelligence of Decision Tree and Random Forest method. Program testing was done with 97.89% accuration score from total 85 infant’s growth data. While from 47 questionnaire data of infant’s development, accuracy score of 83.33% was obtain...

Indonesian Applied Physics Letters, 2020

This research was conducted to design an autofocus microscope with a histogram method that can ob... more This research was conducted to design an autofocus microscope with a histogram method that can observe Tuberculosis (TB) bacteria. The bacteria observed were preparations or phlegm preparations which had been stained with Ziehl Neelsen. The microscope is designed to be equipped with a program to control the focus motor that moves the microscope tube and the program to digitally display the image and histogram of TB bacteria. Histograms are analyzed based on intensity values spread between 0-255 and the entropy value is sought. The measurement results that have been carried out as many as 20 times the field of view of the TB bacteria show that the most focused areas have the highest entropy value with an accuracy level ranging from 81.90476% to 100% at 1000 times the magnification.

International Journal on Advanced Science, Engineering and Information Technology, 2018

In a well-received and widely cited pamphlet, Leonard Read (1946) elaborated on the simple recogn... more In a well-received and widely cited pamphlet, Leonard Read (1946) elaborated on the simple recognition that no person has the ability to list in detail all of the instructions someone would have to follow from start to finish to produce a pencil. Yet pencils are universally available, and we take for granted our ability to obtain a pencil whenever we wish. It is impossible for anyone truly to describe all of the myriad actions scattered over decades and even centuries that must fit together for pencils to be produced. The production of pencils is a systemic quality of particular patterns of interaction among people planting trees, harvesting and milling wood, mining graphite, manufacturing glue and building ships, among countless other activities that are necessary for pencils to appear in retail stores. What enables all of those activities distributed over centuries is what economists denote as a market system of economic interaction. By market system, economists do not mean some kind of inanimate object that operates in clockwork fashion. Rather, they mean that human interactions are governed by some system of institutionally governed rules that tend to promote coordination among the economizing activities of individuals scattered across time and place. Primacy among those rules belong to private property and freedom of contract. For instance, someone might plant land with oak trees that will mature in 50 years, intending to harvest those trees upon their reaching maturity. Before those trees reach maturity, the person contracts a fatal disease. Without private property and freedom of contract, a person in that condition might be tempted to harvest those trees prematurely to make some use of the wealth represented by those trees. In the presence of private property and freedom of contract, however, the owner can improve his situation by selling the trees to someone else. Hence, the institution we know as private property can promote coordination over a duration of time that extends beyond the lifetime of people who initiated the particular action in question. So economics is the study of how locally initiated economic activities can generate global networks of economic interaction when those interactions

Annals of the Institute of Statistical Mathematics, 2000

THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019, 2020

INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020, 2021

Range of Motion (ROM) is one of the movement parameters for evaluating physical rehabilitation. A... more Range of Motion (ROM) is one of the movement parameters for evaluating physical rehabilitation. Articulatio cubiti or elbow is one of the most important organs in the human body that is most commonly injured in some accidents happens. A physical test is needed using ROM measurement to see the severity of the injury and the effectiveness of rehabilitation. Therefore, accurate and precise ROM measurements are needed to decrease error value while diagnosing injury severity and can represent the actual condition of the joints, so the effectiveness of rehabilitation can be evaluated properly. So far, ROM measurement is still using manual devices, named goniometer. However, this device has several disadvantages: it requires human intervention, requires high clinical experience from a therapist or doctor, and goniometer cannot be used for ROM measurement in certain joints. Therefore, we need a device to do ROM measurement automatically, precise, and flexible. In this research, ROM measurements were taken on Articulatio cubiti dextra using Hough transformation method based on kinect sensors and Python programming language. There are three variations of the distance between human subject and kinect sensor; 140 cm (first distance), 220 cm (second distance), and 300 cm (third distance), and there are 10 variations of ROM values from 4° to 120°. The obtained results showed that the best ROM measurement at a first distance with a linearity of 99.59%, a sensitivity of 97.38%, an accuracy of 96.64%, and a relative standard deviation of 1.65%, followed by ROM measurement result at the second distance with a linearity of 99.46%, a sensitivity of 92.28%, an accuracy of 92.51%, and a relative standard deviation of 5.92%, and the lowest ROM measurement results are at a third distance with a linearity of 99.27%, a sensitivity of 91.68%, an accuracy of 90.25%, and a relative standard deviation of 7.28%.

Proceedings of the 1st International Multidisciplinary Conference on Education, Technology, and Engineering (IMCETE 2019), 2020

INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020, 2021

Mycobacterium Tuberculosis is acid-resistant bacteria found in the sputum. This bacterium has a s... more Mycobacterium Tuberculosis is acid-resistant bacteria found in the sputum. This bacterium has a special color like red to purple. It is from this color that doctors specialist clinical pathology can find out that the Tuberculosis (TB) bacteria is in the sputum and counts the number of TB bacteria. In this study, we used the Adaptive Boosting (Adaboost) method to identify TB bacteria. Before identification, filtering is carried out using the median filter and extraction of color features using HSV (Hue Saturation Value) and Adaboost with the decision tree classifier for identification. The target of this study was to determine the effect of color features in identifying TB bacteria. The results of this study indicate that the results of identification of TB bacteria that the Hue value can affect the value of accuracy. In this study, we obtained the best accuracy value of the TB bacterial classification in testing process by using Adaboost method that was 81.7% when the hue in the color histogram was 64

AIP Conference Proceedings

Maize is the second most important agricultural commodity after rice. In Indonesia, maize is an a... more Maize is the second most important agricultural commodity after rice. In Indonesia, maize is an alternative complimentary food, even in some areas it is used as the main food. The future prospect, maize production was increased for national sufficient. However, there are obstacles for achieving it. One of them is the attack of pests and diseases. In this article, image classification on maize leaf diseases is presented. Image classification is a common task when performing image mining. However, classification without a visual explanation certainly makes it difficult for the user to understand the results. This article aims to classify as well as visually explanation the abnormality or emergence of maize leaf diseases. The research is divided into 2 steps: classification and visual explanation. Classification uses Convolutional Neural Network (CNN) Squeezenet while visual explanation uses Gradient-Weighted Class Activation Map (Grad-CAM). The data experiment used from PlantVillage dataset with 4 classes: healthy, blight, spots, and rust. The percentage of training , validation, and testing data was 60:20:20. Validation using 10 fold cross-validation. The novelty was apply the visual explanation using GradCAM on maize leaf diseases. Performance Measure for classification are 95.2%, 94.03%, and 94.28% for accuracy, precision and recall, respectively.

2021 International Conference on Instrumentation, Control, and Automation (ICA), 2021

Bio-impedance measurement of the test object is carried out by inserting an electric current and ... more Bio-impedance measurement of the test object is carried out by inserting an electric current and measuring its voltage using an electrode. The amount of bio-impedance is based on the assumption that the cell network is a conductor with extracellular and intracellular functions as resistors and capacitors. This principle is the basic for measuring the quality of meat using the bio-impedance spectroscopy method. In this research, bio-impedance spectroscopy has been built from the programable function generator AD9850, DC block which is composed of R and C components, each with a value of 1 kΩ and 100µF, Buffer and Voltage/current source (VCCS) which are composed of OPA 2134 Ammeters and The voltmeter are built from the AD620 differential amplifier, as well as the phase-gain detector from the AD8302. This device has been tried to determine the impedance and phase of objects of mutton, chicken, and beef. This device can distinguish the three types of meat and also provides information on changes in the characteristics of meat from day to day from the impedance value.

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2020

ABSTRACT Cervical cancer is a malignant tumour that attacks the female genital area originating f... more ABSTRACT Cervical cancer is a malignant tumour that attacks the female genital area originating from epithelial metaplasia in the squamous protocol junction area. One method of diagnosis of cervical cancer is to do a Pap smear examination by taking a cervical cell smear from the woman’s cervix and observing its cell development. However, examination of cervical cancer from Pap smear results usually takes a long time. This is because medical practitioners still rely on visual observations in the analysis of the results of Pap smear so that the results are subjective. Therefore, we need a programme that can help the classification process in establishing a diagnosis of cervical cancer with high accuracy results. In this study, a cervical cancer classification program was developed using a combination of the Grey Level Co-occurrence Matrix (GLCM) and Extreme Learning Machine (ELM) methods. There are three classes of cervical cell images classified, namely adenocarcinoma, High Squamous Intraepithelial Lesion (HSIL) and Squamous Cell Carcinoma (SCC). From the results of the training program obtained an accuracy 100% and from the testing program obtained an accuracy of 80%.

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 2021

Maize productivity growth is expected to increase by the year. However, there are obstacles to ac... more Maize productivity growth is expected to increase by the year. However, there are obstacles to achieving it. One of the causes is diseases attack. Generally, maize plant diseases are easily detected through the leaves. This article discusses maize leaf disease classification using computer vision with a convolutional neural network (CNN). It aims to compare the deep convolutional neural network (CNN) AlexNet and Squeezenet. The network also used optimization, stochastic gradient descent with momentum (SGDM). The dataset for this experiment was taken from PlantVillage with 3852 images with 4 classes i.e healthy, blight, spot, and rust. The data is divided into 3 parts: training, validation, and testing. Training and validation are 80%, the rest for testing. The results of training with cross-validation produce the best accuracy of 100% for AlexNet and Squeezenet. Furthermore, the best weights and biases are stored in the model for testing data classification. The recognition results ...

2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM), 2020

The process of identifying bacteria is an essential factor in the medical field. One of the germs... more The process of identifying bacteria is an essential factor in the medical field. One of the germs that cause lung damage in pneumonia is gram-negative bacteria. The convolutional neural network method is the newest approach to machine learning because it has a high degree of accuracy. But the drawback is due to his in-depth knowledge, the computation time for the training process takes a long time. The method offered in this research is automatic contrast addition in the preprocessing stage and the use of custom layers. Also, augmentation data added to increase the variation in the amount of data in the training process. In using custom layers, the objective is to obtain minimal computational training time while maintaining maximum accuracy values. The results show that an average accuracy around 98.59% with average training time around 01 minutes 56 seconds, average MSE 0.0274, RMSE 0.1693, and MAE 0.0185.

THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019, 2020

Hemoglobin is the protein molecule that binds oxygen in the blood. Hemoglobin level can be used a... more Hemoglobin is the protein molecule that binds oxygen in the blood. Hemoglobin level can be used as a benchmark of the human physiological condition, such as anemia, hypoxia, and postoperative bleeding. Generally, measurement of hemoglobin levels is performed by an invasive method that takes blood samples to be tested. This study offers a tele-monitoring system for measuring the hemoglobin level non-invasively, so it could reduce the possibility of infection or contamination to the body and can be monitored anywhere by using a website. This tele-monitoring device of non-invasive hemoglobin and oxygen saturation levels were designed by integrating the pulse oximetry sensor with signal conditioning circuit, Arduino Uno as a microcontroller, Ethernet module, an internet network, cloud server, and website. Pulse oximetry measured the oxygen saturation in the blood that indicate the vital state of human and became essential to determine the amount of hemoglobin level. The system performance in this study was tested on participants who had a good daily exercise and participants who never had daily activities to discover the correlation between hemoglobin levels with human physical activity and obtained 89% of accuracy. This system can be implemented as a personal device for monitoring the hemoglobin level and the oxygen saturation in daily used.

THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019, 2020

It has been developed successfully of multi-frequency bio-impedance devices using the AD9850 modu... more It has been developed successfully of multi-frequency bio-impedance devices using the AD9850 module. The devices are composed of AD9850 sin-wave generator module, High Pass Filter, VCCS, AD620A Instrument amplifier, AC to DC AD536A and Arduino Nano. The performance of the devices was tested with 10 variations of the load containing elements R and C. The results of the measurements were compared with the theoretical at frequencies less than 110 kHz resulting error less than 10%. The device can be used to calculate electrical impedance accurately from 10 Hz to 100 kHz.

Ship needs satellite communications systems accurately. Ship’s dynamics cause communications syst... more Ship needs satellite communications systems accurately. Ship’s dynamics cause communications system getting worse. These ship’s dynamic include rolling, pitching, and heading movement. This research made control systems using fuzzy logic to control antenna moving on ship become smooth and fast tracking to the satellite. The result showed that fuzzy logic had performace better than conventional controller (proposional integrad). Proposional integral controller showed setting time 5.84 seconds, rise time 12.96 seconds, maximum overshoot 1.3167%, error steady state 0.0023407 radians, but fuzzy logic controller that already designed had settling time 3.52 seconds, rise time 3.52 seconds, maximum overshoot 1.1768%, and error steady state 2.2204x10-16 radians.

2020 6th Information Technology International Seminar (ITIS), 2020

Image classification is one of the fundamental steps in digital image processing. Research in thi... more Image classification is one of the fundamental steps in digital image processing. Research in this area has received considerable attention, with photos shared on social media which are sometimes similar but have different identities. There are various classification methods proposed in the literature to improve accuracy. One important strategy is Convolutional Neural Networks (CNN). Although CNN is superior in pattern recognition, it has limitations inaccuracy. It requires additional training time, especially when dealing with variants in data generated from a large number of images but of similar properties. Therefore, this study aims to overcome this problem by proposing a modification of the CNN layer to increase the accuracy of the multi-class image classification. This research used four different flower species with similar patterns added from a public database. Each category consists of 400 colour images with different angles, backgrounds, and lighting conditions that provid...

A novel technique to identification of autoregressive moving average (ARMA)systems is proposed to... more A novel technique to identification of autoregressive moving average (ARMA)systems is proposed to increase the accuracy and speed of convergence for the system identification. The convergence speed of recursive least square algorithm (RLS) is solved under differential equations that needs all necessary information about the asymptotic behavior. Using RLS estimation, the convergence of parameters is able to the true values if the data of information vector growing to infinite. Therefore, the convergence of the parameters of the RLS algorithm takes time or needs a large number of sampling. In order to improve the accuracy and convergence speed of the estimated parameters, we propose a technique that modifies the QARXNN model by running two steps to identify the system hierarchically. The proposed method performs two steps: first, the system is identified by least square error (LSE) algorithm. Second, performs multiinput multi-output feedforward neural networks (MIMO-NN) to refine the ...

Darmabakti Cendekia: Journal of Community Service and Engagements, 2020

Background: Posyandu is one of the Indonesian government’s attempt in order to monitor and improv... more Background: Posyandu is one of the Indonesian government’s attempt in order to monitor and improve the health and life quality of the community, especially infant. However, the implementation of Posyandu is facing some issues such as low effectiveness and low accuracy during the data collecting process of the infant’s growth and development. Purpose: This study aims to develop an automatic telehealth care product in order to help to increase the effectivity and accuracy in the implementation of Posyandu. Methods: (1) Development of the Telehealth Care Posyandu Application, (2) Implementation of the application in the form of social service program. Result: (1) “Toddler” Telehealth Care Application based in Android and ICT was buith with artificial intelligence of Decision Tree and Random Forest method. Program testing was done with 97.89% accuration score from total 85 infant’s growth data. While from 47 questionnaire data of infant’s development, accuracy score of 83.33% was obtain...

Indonesian Applied Physics Letters, 2020

This research was conducted to design an autofocus microscope with a histogram method that can ob... more This research was conducted to design an autofocus microscope with a histogram method that can observe Tuberculosis (TB) bacteria. The bacteria observed were preparations or phlegm preparations which had been stained with Ziehl Neelsen. The microscope is designed to be equipped with a program to control the focus motor that moves the microscope tube and the program to digitally display the image and histogram of TB bacteria. Histograms are analyzed based on intensity values spread between 0-255 and the entropy value is sought. The measurement results that have been carried out as many as 20 times the field of view of the TB bacteria show that the most focused areas have the highest entropy value with an accuracy level ranging from 81.90476% to 100% at 1000 times the magnification.

International Journal on Advanced Science, Engineering and Information Technology, 2018

In a well-received and widely cited pamphlet, Leonard Read (1946) elaborated on the simple recogn... more In a well-received and widely cited pamphlet, Leonard Read (1946) elaborated on the simple recognition that no person has the ability to list in detail all of the instructions someone would have to follow from start to finish to produce a pencil. Yet pencils are universally available, and we take for granted our ability to obtain a pencil whenever we wish. It is impossible for anyone truly to describe all of the myriad actions scattered over decades and even centuries that must fit together for pencils to be produced. The production of pencils is a systemic quality of particular patterns of interaction among people planting trees, harvesting and milling wood, mining graphite, manufacturing glue and building ships, among countless other activities that are necessary for pencils to appear in retail stores. What enables all of those activities distributed over centuries is what economists denote as a market system of economic interaction. By market system, economists do not mean some kind of inanimate object that operates in clockwork fashion. Rather, they mean that human interactions are governed by some system of institutionally governed rules that tend to promote coordination among the economizing activities of individuals scattered across time and place. Primacy among those rules belong to private property and freedom of contract. For instance, someone might plant land with oak trees that will mature in 50 years, intending to harvest those trees upon their reaching maturity. Before those trees reach maturity, the person contracts a fatal disease. Without private property and freedom of contract, a person in that condition might be tempted to harvest those trees prematurely to make some use of the wealth represented by those trees. In the presence of private property and freedom of contract, however, the owner can improve his situation by selling the trees to someone else. Hence, the institution we know as private property can promote coordination over a duration of time that extends beyond the lifetime of people who initiated the particular action in question. So economics is the study of how locally initiated economic activities can generate global networks of economic interaction when those interactions

Annals of the Institute of Statistical Mathematics, 2000

THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019, 2020

INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020, 2021

Range of Motion (ROM) is one of the movement parameters for evaluating physical rehabilitation. A... more Range of Motion (ROM) is one of the movement parameters for evaluating physical rehabilitation. Articulatio cubiti or elbow is one of the most important organs in the human body that is most commonly injured in some accidents happens. A physical test is needed using ROM measurement to see the severity of the injury and the effectiveness of rehabilitation. Therefore, accurate and precise ROM measurements are needed to decrease error value while diagnosing injury severity and can represent the actual condition of the joints, so the effectiveness of rehabilitation can be evaluated properly. So far, ROM measurement is still using manual devices, named goniometer. However, this device has several disadvantages: it requires human intervention, requires high clinical experience from a therapist or doctor, and goniometer cannot be used for ROM measurement in certain joints. Therefore, we need a device to do ROM measurement automatically, precise, and flexible. In this research, ROM measurements were taken on Articulatio cubiti dextra using Hough transformation method based on kinect sensors and Python programming language. There are three variations of the distance between human subject and kinect sensor; 140 cm (first distance), 220 cm (second distance), and 300 cm (third distance), and there are 10 variations of ROM values from 4° to 120°. The obtained results showed that the best ROM measurement at a first distance with a linearity of 99.59%, a sensitivity of 97.38%, an accuracy of 96.64%, and a relative standard deviation of 1.65%, followed by ROM measurement result at the second distance with a linearity of 99.46%, a sensitivity of 92.28%, an accuracy of 92.51%, and a relative standard deviation of 5.92%, and the lowest ROM measurement results are at a third distance with a linearity of 99.27%, a sensitivity of 91.68%, an accuracy of 90.25%, and a relative standard deviation of 7.28%.

Proceedings of the 1st International Multidisciplinary Conference on Education, Technology, and Engineering (IMCETE 2019), 2020

INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020, 2021

Mycobacterium Tuberculosis is acid-resistant bacteria found in the sputum. This bacterium has a s... more Mycobacterium Tuberculosis is acid-resistant bacteria found in the sputum. This bacterium has a special color like red to purple. It is from this color that doctors specialist clinical pathology can find out that the Tuberculosis (TB) bacteria is in the sputum and counts the number of TB bacteria. In this study, we used the Adaptive Boosting (Adaboost) method to identify TB bacteria. Before identification, filtering is carried out using the median filter and extraction of color features using HSV (Hue Saturation Value) and Adaboost with the decision tree classifier for identification. The target of this study was to determine the effect of color features in identifying TB bacteria. The results of this study indicate that the results of identification of TB bacteria that the Hue value can affect the value of accuracy. In this study, we obtained the best accuracy value of the TB bacterial classification in testing process by using Adaboost method that was 81.7% when the hue in the color histogram was 64