Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.25735
A. Permana, Luigi Ajeng Pratiwi
Nowadays, technological advances have made it increasingly easy to obtain information, especially image data (digital images). Digital image is an interesting thing to look for information. So that misuse of data can be done for personal or public interests. Misuse of data can be avoided by adding data security systems. Cryptography is the science of securing data. Cryptography can be done using the AES (Advanced Encryption Standard) algorithm, which is an algorithm that utilizes symmetric keys. Testing is done by entering the same key in the encryption and decryption process. Encryption is the process of encoding plaintext (original text) into ciphertext (text that has been encoded). While decryption is the process of recovering the plaintext from the ciphertext. Therefore, data security is an important thing to do. This study aims to find out how encryption and decryption on the AES algorithm can be used to secure digital data. The results of this study indicate that the encryption and decryption process on the AES algorithm was successfully carried out so that it can be used to secure data on digital images.
{"title":"Implementation of The Advanced Encryption Standard (AES) Algorithm for Digital Image Security","authors":"A. Permana, Luigi Ajeng Pratiwi","doi":"10.15408/jti.v15i1.25735","DOIUrl":"https://doi.org/10.15408/jti.v15i1.25735","url":null,"abstract":"Nowadays, technological advances have made it increasingly easy to obtain information, especially image data (digital images). Digital image is an interesting thing to look for information. So that misuse of data can be done for personal or public interests. Misuse of data can be avoided by adding data security systems. Cryptography is the science of securing data. Cryptography can be done using the AES (Advanced Encryption Standard) algorithm, which is an algorithm that utilizes symmetric keys. Testing is done by entering the same key in the encryption and decryption process. Encryption is the process of encoding plaintext (original text) into ciphertext (text that has been encoded). While decryption is the process of recovering the plaintext from the ciphertext. Therefore, data security is an important thing to do. This study aims to find out how encryption and decryption on the AES algorithm can be used to secure digital data. The results of this study indicate that the encryption and decryption process on the AES algorithm was successfully carried out so that it can be used to secure data on digital images.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"102 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75456708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.25254
Iis Afrianty, D. Nasien, H. Haron
Sex classification is part of forensic anthropological identification aimed at determining whether the skeleton belongs to a male or a female. This paper exhibits the performance of the Support Vector Machine (SVM) in classifying the sex of the sacrum in forensic anthropology. Bone data was measured by the metric method based on six variables, namely superior breadth, anterior length, mid ventral breadth, real height, diameter the base, and max-transverse diameter of the base. This study shows performance analysis of SVM using the library libSVM with linear, polynomial, and RBF kernel to observe the results of the comparison of the accuracy of the kernel used. According to the results of the trials, the best accuracy was attained in each kernel function, i.e., the RBF kernel is 83.33% with g = 1 and C = 1, the polynomial is 85.56% at γ = 2, C = 2 and d =1, and the linear kernel obtained best accuracy is 84.44 % with C = 2 and C = 3. In conformity with the experimental result, polynomial attained the highest accuracy of 85.56% at γ = 2, C = 2, and d =1.
性别分类是法医人类学鉴定的一部分，目的是确定骨骼属于男性还是女性。本文展示了支持向量机(SVM)在法医人类学中骶骨性别分类中的性能。骨数据采用基于六个变量的度量法测量，即上宽、前长、中腹宽、实际高度、基部直径和基部最大横向直径。本研究使用libSVM库对支持向量机进行性能分析，并与线性、多项式和RBF核进行对比，观察所使用核的精度结果。实验结果表明，各核函数的准确率最高，当g =1、C =1时，RBF核函数的准确率为83.33%;当γ = 2、C = 2、d =1时，多项式的准确率为85.56%;当C = 2、C = 3时，线性核函数的准确率为84.44%。实验结果表明，当γ = 2, C = 2, d =1时，多项式的准确率最高，达到85.56%。
{"title":"Performance Analysis of Support Vector Machine in Sex Classification of The Sacrum Bone in Forensic Anthropology","authors":"Iis Afrianty, D. Nasien, H. Haron","doi":"10.15408/jti.v15i1.25254","DOIUrl":"https://doi.org/10.15408/jti.v15i1.25254","url":null,"abstract":"Sex classification is part of forensic anthropological identification aimed at determining whether the skeleton belongs to a male or a female. This paper exhibits the performance of the Support Vector Machine (SVM) in classifying the sex of the sacrum in forensic anthropology. Bone data was measured by the metric method based on six variables, namely superior breadth, anterior length, mid ventral breadth, real height, diameter the base, and max-transverse diameter of the base. This study shows performance analysis of SVM using the library libSVM with linear, polynomial, and RBF kernel to observe the results of the comparison of the accuracy of the kernel used. According to the results of the trials, the best accuracy was attained in each kernel function, i.e., the RBF kernel is 83.33% with g = 1 and C = 1, the polynomial is 85.56% at γ = 2, C = 2 and d =1, and the linear kernel obtained best accuracy is 84.44 % with C = 2 and C = 3. In conformity with the experimental result, polynomial attained the highest accuracy of 85.56% at γ = 2, C = 2, and d =1.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75984109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.24869
A. Setianingrum, Arifa Fauzia, Dzul Fadli Rahman
Sign language is a non-verbal language that Deaf persons exclusively count on to connect with their social environment.The problem that occurs in two-way communication using sign language is a misunderstanding when learning new terms that need to be taught to deaf and mute people. To minimize these misunderstandings, a system is needed that can assist in correcting hand gestures so that there is no misinterpretation in teaching new terms. Several optimality properties of PCA have been identified namely: variance of extracted features is maximized; the extracted features are uncorrelated; finds best linear approximation in the mean-square sense and maximizes information contained in the extracted feature. The classification uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. From the results of experiments with different image size variables, the largest accuracy was obtained with an image size of 449x449 of 76.20%. While the lowest accuracy of 52.38% is obtained through scenarios with image sizes of 57x57 and 45x45. Therefore, differences in the use of image sizes have an influence on the accuracy of hand signal prediction. The smaller the size given, the smaller the accuracy obtained. This is indicated by the decreasing accuracy value when given a smaller size in the four scenarios that have been studied.
{"title":"Hand-Gesture Detection Using Principal Component Analysis (PCA) and Adaptive Neuro-Fuzzy Inference System (ANFIS)","authors":"A. Setianingrum, Arifa Fauzia, Dzul Fadli Rahman","doi":"10.15408/jti.v15i1.24869","DOIUrl":"https://doi.org/10.15408/jti.v15i1.24869","url":null,"abstract":"Sign language is a non-verbal language that Deaf persons exclusively count on to connect with their social environment.The problem that occurs in two-way communication using sign language is a misunderstanding when learning new terms that need to be taught to deaf and mute people. To minimize these misunderstandings, a system is needed that can assist in correcting hand gestures so that there is no misinterpretation in teaching new terms. Several optimality properties of PCA have been identified namely: variance of extracted features is maximized; the extracted features are uncorrelated; finds best linear approximation in the mean-square sense and maximizes information contained in the extracted feature. The classification uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. From the results of experiments with different image size variables, the largest accuracy was obtained with an image size of 449x449 of 76.20%. While the lowest accuracy of 52.38% is obtained through scenarios with image sizes of 57x57 and 45x45. Therefore, differences in the use of image sizes have an influence on the accuracy of hand signal prediction. The smaller the size given, the smaller the accuracy obtained. This is indicated by the decreasing accuracy value when given a smaller size in the four scenarios that have been studied.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"119 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79407491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.24683
A. Setyorini, T. Listyorini, Endang Supriyati
The existence of the Covid-19 virus has an impact on almost all fields, one of which is in the field of education. With the Covid-19 virus, the learning process has changed to distance learning or online. Online learning requires parents to be able to accompany their children in learning. However, not all parents can accompany their children to study because of their busy schedule at work, or the parents' low level of education. Therefore, the existence of tutoring or tutoring places is sought to assist parents in educating their children in the midst of a pandemic. Les Baca Anak Hebat (AHE) is a special community tutoring for reading and writing. Its development in Indonesia is increasing from village to village. In Kudus City itself there are many villages that have units. With this significant number of students, the number of existing students also affects the continuation of the unit. To avoid a spike in the number of students, we need a system that can monitor or predict the number of students in the future so that no units are closed. To estimate the number of students can use one of the fields of science such as forecasting. One of the forecasting methods is the Straight Line Method. In developing the system the author uses the waterfall method with the PHP programming language and MySQL database. This web-based system is used to monitor AHE units in Kudus.
新冠病毒的存在几乎影响到所有领域，其中之一就是教育领域。由于新冠肺炎疫情，学习过程已改为远程学习或在线学习。在线学习要求家长能够陪伴孩子学习。然而，并不是所有的父母都能陪伴他们的孩子学习，因为他们的工作繁忙，或者父母的教育水平低。因此，为了在大流行期间帮助父母教育子女，需要开设辅导班或辅导班。Les Baca Anak Hebat (AHE)是一个特殊的社区阅读和写作辅导。它在印尼的发展是逐村递增的。在库德斯市，很多村庄都有住房。有了这个显著的学生数量，现有学生的数量也影响到该单元的延续。为了避免学生人数激增，我们需要一个可以监控或预测未来学生人数的系统，这样就不会有任何单位关闭。要估计学生的数量，可以使用预测等科学领域之一。其中一种预测方法是直线法。在系统的开发中，作者采用了瀑布法，使用PHP编程语言和MySQL数据库。这个基于网络的系统用于监测库德斯的AHE单元。
{"title":"Forecasting Straight Line Methodin The Les Monitoring System Read The Great Children (AHE) in Kudus","authors":"A. Setyorini, T. Listyorini, Endang Supriyati","doi":"10.15408/jti.v15i1.24683","DOIUrl":"https://doi.org/10.15408/jti.v15i1.24683","url":null,"abstract":"The existence of the Covid-19 virus has an impact on almost all fields, one of which is in the field of education. With the Covid-19 virus, the learning process has changed to distance learning or online. Online learning requires parents to be able to accompany their children in learning. However, not all parents can accompany their children to study because of their busy schedule at work, or the parents' low level of education. Therefore, the existence of tutoring or tutoring places is sought to assist parents in educating their children in the midst of a pandemic. Les Baca Anak Hebat (AHE) is a special community tutoring for reading and writing. Its development in Indonesia is increasing from village to village. In Kudus City itself there are many villages that have units. With this significant number of students, the number of existing students also affects the continuation of the unit. To avoid a spike in the number of students, we need a system that can monitor or predict the number of students in the future so that no units are closed. To estimate the number of students can use one of the fields of science such as forecasting. One of the forecasting methods is the Straight Line Method. In developing the system the author uses the waterfall method with the PHP programming language and MySQL database. This web-based system is used to monitor AHE units in Kudus.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89949471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.24780
Asafalex Asafalex, M. Firmansyah, M. Darwis, I. Sw
The National University administers several scholarships for new students each year. The problem is, the University does not yet have a standard method for determining beneficiaries. They have difficulty in determining prospective scholarship recipients with the same criteria. In fact, sometimes it only relies on people's instincts, which can be subjective. The University should implement a DSS system to overcome this problem. Therefore, in this study, the AHP method is applied and used to weight the criteria and test the level of consistency so that the criteria are in accordance with the type of scholarship. In addition, the SAW method is also used for determining scholarship recipients according to the quota. The results of this study are the priority weights of the importance of each criterion, namely the average value of report cards (0.35), parents' income (0.23), certificates (0.05), affidavits of not working and receiving scholarships (0.15), year of graduation (0.11) and number of certificates (0.10). The consistency ratio value is 0.03741 indicating the weight is consistent. This study also resulted in the best ranking of candidates for academic scholarships, with a result of 0.93. The average value of the application test results using the TAM method is 80.5%.
{"title":"Selection of Candidates for Academic Scholarships Using Analytical Hierarchy Process (Ahp) and Simple Additive Weighting (SAW) Methods at National University","authors":"Asafalex Asafalex, M. Firmansyah, M. Darwis, I. Sw","doi":"10.15408/jti.v15i1.24780","DOIUrl":"https://doi.org/10.15408/jti.v15i1.24780","url":null,"abstract":"The National University administers several scholarships for new students each year. The problem is, the University does not yet have a standard method for determining beneficiaries. They have difficulty in determining prospective scholarship recipients with the same criteria. In fact, sometimes it only relies on people's instincts, which can be subjective. The University should implement a DSS system to overcome this problem. Therefore, in this study, the AHP method is applied and used to weight the criteria and test the level of consistency so that the criteria are in accordance with the type of scholarship. In addition, the SAW method is also used for determining scholarship recipients according to the quota. The results of this study are the priority weights of the importance of each criterion, namely the average value of report cards (0.35), parents' income (0.23), certificates (0.05), affidavits of not working and receiving scholarships (0.15), year of graduation (0.11) and number of certificates (0.10). The consistency ratio value is 0.03741 indicating the weight is consistent. This study also resulted in the best ranking of candidates for academic scholarships, with a result of 0.93. The average value of the application test results using the TAM method is 80.5%.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79066753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.24847
Ines Sholekha, A. Faqīh, Agus Bahtiar
The emergence of COVID-19 or 2019 coronavirus disease has been reported as a problem with a new type of disease caused by SARS-Voc 2. It has spread to 223 countries and 25 areas around the world, including Indonesia. COVID-19 has deeply affected many aspects of our lives, the environment, mental health and the economy. Twitter is one of the media outlets that is busy discussing news regarding the COVID-19 vaccine. Covid-19 has been a major impact. The Government has implemented policies such as large-scale social restrictions to address the spread of COVID-19. The elevated spread of COVID-19 has prompted the Government of Indonesia to encourage the production of a COVID-19 vaccine. The provision of the COVID-19 vaccine has become a boon and a boon to the people of Indonesia. A lot of people don't want to be vaccinated because the news of the impact of vaccination is spreading on social media, even if the news isn't necessarily real. The Government is looking for ways to continue vaccinating the community, including by collaborating with community leaders, influencers and others. The purpose of this study is to identify the community response to the vaccine so that the right strategy can be used. The results of this study yielded 89.79% for Naïve Bayes and 84.62% for Random Forest. Indonesians are giving positive responses to the administration of the COVID-19 vaccine.
{"title":"Sentiment Analysis of Public Opinion Covid-19 Vaccine Using Naïve Bayes and Random Forest Methods","authors":"Ines Sholekha, A. Faqīh, Agus Bahtiar","doi":"10.15408/jti.v15i1.24847","DOIUrl":"https://doi.org/10.15408/jti.v15i1.24847","url":null,"abstract":"The emergence of COVID-19 or 2019 coronavirus disease has been reported as a problem with a new type of disease caused by SARS-Voc 2. It has spread to 223 countries and 25 areas around the world, including Indonesia. COVID-19 has deeply affected many aspects of our lives, the environment, mental health and the economy. Twitter is one of the media outlets that is busy discussing news regarding the COVID-19 vaccine. Covid-19 has been a major impact. The Government has implemented policies such as large-scale social restrictions to address the spread of COVID-19. The elevated spread of COVID-19 has prompted the Government of Indonesia to encourage the production of a COVID-19 vaccine. The provision of the COVID-19 vaccine has become a boon and a boon to the people of Indonesia. A lot of people don't want to be vaccinated because the news of the impact of vaccination is spreading on social media, even if the news isn't necessarily real. The Government is looking for ways to continue vaccinating the community, including by collaborating with community leaders, influencers and others. The purpose of this study is to identify the community response to the vaccine so that the right strategy can be used. The results of this study yielded 89.79% for Naïve Bayes and 84.62% for Random Forest. Indonesians are giving positive responses to the administration of the COVID-19 vaccine.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85883177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.25682
Panca Oktavia Candra Sari, Suharjito Suharjito
Health insurance helps people to obtain quality and affordable health services. The claim billing process is manually input code to the system, this can lack of errors and be suspected of being fraudulent. Claims suspected of fraud are traced manually to find incorrect inputs. The increasing volume of claims causes a decrease in the accuracy of tracing claims suspected of fraud and consumes time and energy. As an effort to prevent and reduce the occurrence of fraud, this study aims to determine the pattern of data on the occurrence of fraud based on the formation of data groupings. Data was prepared by combining claims for inpatient bills and patient bills from hospitals in 2020. Two methods were used in this study to form clusters, DBSCAN and KMeans. To find out the outliers in the cluster, Local Outlier Factor (LOF) was added. The results from experiments show that both methods can detect outlier data and distribute outlier data in the formed cluster. Variable that high effect becomes data outlier is the length of stay, claims code, and condition of patient when discharged from the hospital. Accuracy K-Means is 0.391, 0.003 higher than DBSCAN, which is 0.389.
{"title":"Outlier Detection in Inpatient Claims Using DBSCAN and K-Means","authors":"Panca Oktavia Candra Sari, Suharjito Suharjito","doi":"10.15408/jti.v15i1.25682","DOIUrl":"https://doi.org/10.15408/jti.v15i1.25682","url":null,"abstract":"Health insurance helps people to obtain quality and affordable health services. The claim billing process is manually input code to the system, this can lack of errors and be suspected of being fraudulent. Claims suspected of fraud are traced manually to find incorrect inputs. The increasing volume of claims causes a decrease in the accuracy of tracing claims suspected of fraud and consumes time and energy. As an effort to prevent and reduce the occurrence of fraud, this study aims to determine the pattern of data on the occurrence of fraud based on the formation of data groupings. Data was prepared by combining claims for inpatient bills and patient bills from hospitals in 2020. Two methods were used in this study to form clusters, DBSCAN and KMeans. To find out the outliers in the cluster, Local Outlier Factor (LOF) was added. The results from experiments show that both methods can detect outlier data and distribute outlier data in the formed cluster. Variable that high effect becomes data outlier is the length of stay, claims code, and condition of patient when discharged from the hospital. Accuracy K-Means is 0.391, 0.003 higher than DBSCAN, which is 0.389.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83902608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.24968
Muhammad Wahyu Ilahi, Chairu Nisa Apriyani, Anita Desiani, N. Gofar, Yuli Andriani, Muhammat Rio Halim
Batik is a world heritage from Indonesia which is a characteristic of Indonesian culture. On October 2, 2009 batik has been awarded as a cultural heritage from UNESCO. Indonesia has 5.849 batik patterns from Aceh to Papua. The ability to recognize batik cloth patterns is certainly quite difficult and only owned by certain people who have expertise. One way to identify batik patterns is by using a pattern recognition classification method based on quantitative measurements of the main features or characteristics of an object. Deep Learning is one solution to detect batik patterns automatically. One of deep learning methods that can classify patterns of batik patterns is Convolutional Neural Network (CNN). CNN is able to group and detect objects in the image automatically by accepting input data with a size of m×n. CNN uses image input through a convolution layer and be processed according to the specified filter. Each layer produces a pattern from several parts of the image that facilitates the classification process. This study uses the CNN method and obtains the average value of 96% accuracy, 96,78% precision, 96,74% recall, and 96,74%.
{"title":"Classification of Geometric Batik Motif Typical of Indonesian Using Convolutional Neural Network","authors":"Muhammad Wahyu Ilahi, Chairu Nisa Apriyani, Anita Desiani, N. Gofar, Yuli Andriani, Muhammat Rio Halim","doi":"10.15408/jti.v15i1.24968","DOIUrl":"https://doi.org/10.15408/jti.v15i1.24968","url":null,"abstract":"Batik is a world heritage from Indonesia which is a characteristic of Indonesian culture. On October 2, 2009 batik has been awarded as a cultural heritage from UNESCO. Indonesia has 5.849 batik patterns from Aceh to Papua. The ability to recognize batik cloth patterns is certainly quite difficult and only owned by certain people who have expertise. One way to identify batik patterns is by using a pattern recognition classification method based on quantitative measurements of the main features or characteristics of an object. Deep Learning is one solution to detect batik patterns automatically. One of deep learning methods that can classify patterns of batik patterns is Convolutional Neural Network (CNN). CNN is able to group and detect objects in the image automatically by accepting input data with a size of m×n. CNN uses image input through a convolution layer and be processed according to the specified filter. Each layer produces a pattern from several parts of the image that facilitates the classification process. This study uses the CNN method and obtains the average value of 96% accuracy, 96,78% precision, 96,74% recall, and 96,74%.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74268057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.15408/jti.v15i1.24915
William Santoso, Wilda Nurjannah, Mahgrisya Shudhuashar, Asyifa Tasya Fadilah, Muhammad Destamal Junas, D. Handayani
Information technology is developing quickly in this era as if the world is in our hands. All forms of information can be accessed quickly, including Islamic information by utilizing internet technology. One of well-known medium to spread information is social media. Telegram, as one of the social media that has various beneficial features and widely used by people, has the potential to be a medium for disseminating Islamic knowledge. To improve the dissemination process of Islamic knowledge, we used one of the services found on Telegram namely chatbot. By utilizing Telegram Bot API, we make a bot that can automatically provide output according to the command given by the user in this case, giving various Islamic knowledges that users need such as Tafsir, hadith, daily prayer, and even Islamic history with a reliable source. Based on the testing result, the bot is showing a good result because it’s displaying the expected output and all features are working fine as they should be. We hoped that this bot can maximize the dissemination process of Islamic knowledge in Indonesia and reach wider audience coverage.
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This research addresses the problem of color blindness testing at Puskesmas Rumbai which serves color blindness checks using printed books. The colors in the book became less clear as time went on. Therefore, this research makes a digital color blindness examination as part of the application for obtaining a certificate of health. The resulting application is named SIP SEHAT which stands for Aplikasi Pelayanan Surat Keterangan Kesehatan. This application was developed using prototyping method approach. There are 3 categories of users of this application, namely the registration section, doctor or nurse, and administration section. The registration section inputs the identity of the patient who will perform the examination. Meanwhile, doctors or nurses carry out examinations and medical examinations of patients who come. Color blindness test is one of the features found in doctors or nurses. Patients independently answer 24 Ishihara templates that appear on the application. Based on the answers from the patient, the application will display the color blindness test results, whether including total color blindness, partial color blindness, or not color blindness. The administration section prints a certificate of a patient who has performed an examination and gets a recapitulation of health examination reports per month. The application has been tested with 3 types of testing, namely accuracy testing, correctness testing, and usability testing. Based on these three tests, it can be concluded that this application is ready for use by the Puskesmas Rumbai to serve the processing of certificates of health. Based on service process analysis, this application makes the process of managing a health certificate making more efficient by 42.86%.
本研究解决了Puskesmas Rumbai的色盲测试问题，该测试使用印刷书籍进行色盲检查。随着时间的推移，书中的颜色变得不那么清晰了。因此，本研究将数字色盲检查作为申请健康证书的一部分。由此产生的应用程序被命名为SIP SEHAT，它代表applikasi Pelayanan Surat Keterangan Kesehatan。本应用程序是使用原型方法开发的。该应用程序的用户有3个类别，即注册部分，医生或护士和管理部分。注册部分输入将进行检查的患者的身份。同时，医生或护士对前来就诊的病人进行检查和体格检查。色盲测试是在医生或护士中发现的特征之一。患者独立回答出现在应用程序上的24个石原模板。根据患者的回答，应用程序将显示色盲测试结果，包括完全色盲、部分色盲或非色盲。管理部门打印进行检查的病人的证明，并每月获得健康检查报告的摘要。该应用程序进行了三种类型的测试，即准确性测试、正确性测试和可用性测试。根据这三项测试，可以得出结论，该应用程序已准备好供Puskesmas Rumbai用于处理卫生证书。通过对业务流程的分析，本应用程序使卫生证书管理流程的效率提高了42.86%。
{"title":"Development of Color Blindness Test Application Using Ishihara Template at Rumbai Public Health Center","authors":"Memen Akbar, Warnia Nengsih Sikumbang, Wiwin Styorini","doi":"10.15408/jti.v15i1.24889","DOIUrl":"https://doi.org/10.15408/jti.v15i1.24889","url":null,"abstract":"This research addresses the problem of color blindness testing at Puskesmas Rumbai which serves color blindness checks using printed books. The colors in the book became less clear as time went on. Therefore, this research makes a digital color blindness examination as part of the application for obtaining a certificate of health. The resulting application is named SIP SEHAT which stands for Aplikasi Pelayanan Surat Keterangan Kesehatan. This application was developed using prototyping method approach. There are 3 categories of users of this application, namely the registration section, doctor or nurse, and administration section. The registration section inputs the identity of the patient who will perform the examination. Meanwhile, doctors or nurses carry out examinations and medical examinations of patients who come. Color blindness test is one of the features found in doctors or nurses. Patients independently answer 24 Ishihara templates that appear on the application. Based on the answers from the patient, the application will display the color blindness test results, whether including total color blindness, partial color blindness, or not color blindness. The administration section prints a certificate of a patient who has performed an examination and gets a recapitulation of health examination reports per month. The application has been tested with 3 types of testing, namely accuracy testing, correctness testing, and usability testing. Based on these three tests, it can be concluded that this application is ready for use by the Puskesmas Rumbai to serve the processing of certificates of health. Based on service process analysis, this application makes the process of managing a health certificate making more efficient by 42.86%.","PeriodicalId":52586,"journal":{"name":"Jurnal Sarjana Teknik Informatika","volume":"218 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79719801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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