Tri Listyorini, Muhamad Khothibul Umam, Aditya Akbar Riadi
Abstract. Monel Craft is a handicraft that is inherited from generation to generation by the people of Jepara. Monel accessories produced can be in the form of bracelets, necklaces, earrings, rings, and many other accessories. For its manufacturer using a drill, hacksaw, and smoothing machine. Monel marketing is still limited around the city of Jepara. Purpose: This research aims to introduce Monel more broadly with a 3D multimedia approach. So, there is an idea of what Monel is. In general, Monel has a shiny shape and is corrosion-resistant. The price is relative and can be ordered according to our wishes.Methods: The method used in this research is the method of multimedia development.Result: This research produces a 3D animation that is packaged attractively, so that it represents Monel craftsmen to introduce it to the whole community.Novelty: This research combines the multimedia method with the work of local wisdom from the city of Jepara, namely Monel. This research, entitled "Monel Craft 3D Animation", can increase knowledge about how to make it. And can be a medium of education and preservation of cultural arts in Jepara.
{"title":"3D Animation Making Crafts Monel Jepara","authors":"Tri Listyorini, Muhamad Khothibul Umam, Aditya Akbar Riadi","doi":"10.15294/sji.v9i1.31686","DOIUrl":"https://doi.org/10.15294/sji.v9i1.31686","url":null,"abstract":"Abstract. Monel Craft is a handicraft that is inherited from generation to generation by the people of Jepara. Monel accessories produced can be in the form of bracelets, necklaces, earrings, rings, and many other accessories. For its manufacturer using a drill, hacksaw, and smoothing machine. Monel marketing is still limited around the city of Jepara. Purpose: This research aims to introduce Monel more broadly with a 3D multimedia approach. So, there is an idea of what Monel is. In general, Monel has a shiny shape and is corrosion-resistant. The price is relative and can be ordered according to our wishes.Methods: The method used in this research is the method of multimedia development.Result: This research produces a 3D animation that is packaged attractively, so that it represents Monel craftsmen to introduce it to the whole community.Novelty: This research combines the multimedia method with the work of local wisdom from the city of Jepara, namely Monel. This research, entitled \"Monel Craft 3D Animation\", can increase knowledge about how to make it. And can be a medium of education and preservation of cultural arts in Jepara. ","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47007652","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}
Purpose: Steganography is the science of writing hidden or hiding messages so that apart from the sender and the recipient, no one can know or realize that a message is hidden. This paper aims to analyze the method of advanced LSB to increase message capacity. Methods/Study design/approach: The steganography technique advanced LSB algorithm develops pre-existing steganographic algorithms such as LSB by utilizing a range of media pixel values cover (images that are used as media to hide messages) with different insertion rules from LSB. Image scaling in digital image processing is known as resampling. Resampling is a mathematical technique used to produce a new image from the previous image with different pixel size, often called interpolation. Increasing the pixel size of the previous image is called upsampling and in this study we will only use twice the image magnification. Result/Findings: The results of each test method using advanced LSB without image scaling and advanced LSB using image scaling were compared to obtain detailed comparison results of each method. Novelty/Originality/Value: Advanced LSB and image scaling in this study can increase the message capacity three times compared to only using the advanced LSB method without image scaling. It depends on the image pixels used.
{"title":"Increasing Message Capacity in Images Using Advanced Least Significant Bit and Image Scaling","authors":"Affan Fadlil, B. Prasetiyo, A. Alamsyah","doi":"10.15294/sji.v8i2.28138","DOIUrl":"https://doi.org/10.15294/sji.v8i2.28138","url":null,"abstract":"Purpose: Steganography is the science of writing hidden or hiding messages so that apart from the sender and the recipient, no one can know or realize that a message is hidden. This paper aims to analyze the method of advanced LSB to increase message capacity. Methods/Study design/approach: The steganography technique advanced LSB algorithm develops pre-existing steganographic algorithms such as LSB by utilizing a range of media pixel values cover (images that are used as media to hide messages) with different insertion rules from LSB. Image scaling in digital image processing is known as resampling. Resampling is a mathematical technique used to produce a new image from the previous image with different pixel size, often called interpolation. Increasing the pixel size of the previous image is called upsampling and in this study we will only use twice the image magnification. Result/Findings: The results of each test method using advanced LSB without image scaling and advanced LSB using image scaling were compared to obtain detailed comparison results of each method. Novelty/Originality/Value: Advanced LSB and image scaling in this study can increase the message capacity three times compared to only using the advanced LSB method without image scaling. It depends on the image pixels used.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49016996","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}
Most people with diabetes in the world are type 2. We can detect diabetes early to prevent things that are not desirable by checking sugar and insulin levels with the doctor. In addition to using this method, people with diabetes can also be grouped based on data from diabetes examination results. However, most of the data on health examination results have several parameters that are difficult for the public to understand. These problems can be done by means of automatic classification. In addition to these problems, there is another problem in the form of an unbalanced amount of data for diabetics and non-diabetics. This problem can be done by balancing the amount of data using the model to increase the ratio of the amount of data that is small or decrease the ratio of the amount of data that is too much. Purpose: This study aims to detect type 2 diabetes mellitus using the SVM classification model and analyze the results of the comparison using the SMOTE and ADASYN data balancing technique which is the best. Methods/Study design/approach: The research method starts from collecting the diabetes dataset, then the dataset cleaning process is carried out whether there is a null value or not. After applying two oversampling methods to analyze which method is the most appropriate. After the oversampling technique was carried out, data classification was carried out using a support vector machine model to see the accuracy results. Result/Findings: The results obtained by the ADASYN-SVM method are superior to SMOTE-SVM. The ADASYNSVM method has an accuracy of 87.3%, while the SMOTE-SVM has an accuracy of 85.4%. Novelty/Originality/Value: The data used in this study came from the Karya Medika clinic, Indonesia which contains parameters related to type 2 diabetes.
{"title":"Comparative Analysis of ADASYN-SVM and SMOTE-SVM Methods on the Detection of Type 2 Diabetes Mellitus","authors":"Nur Ghaniaviyanto Ramadhan","doi":"10.15294/sji.v8i2.32484","DOIUrl":"https://doi.org/10.15294/sji.v8i2.32484","url":null,"abstract":"Most people with diabetes in the world are type 2. We can detect diabetes early to prevent things that are not desirable by checking sugar and insulin levels with the doctor. In addition to using this method, people with diabetes can also be grouped based on data from diabetes examination results. However, most of the data on health examination results have several parameters that are difficult for the public to understand. These problems can be done by means of automatic classification. In addition to these problems, there is another problem in the form of an unbalanced amount of data for diabetics and non-diabetics. This problem can be done by balancing the amount of data using the model to increase the ratio of the amount of data that is small or decrease the ratio of the amount of data that is too much. Purpose: This study aims to detect type 2 diabetes mellitus using the SVM classification model and analyze the results of the comparison using the SMOTE and ADASYN data balancing technique which is the best. Methods/Study design/approach: The research method starts from collecting the diabetes dataset, then the dataset cleaning process is carried out whether there is a null value or not. After applying two oversampling methods to analyze which method is the most appropriate. After the oversampling technique was carried out, data classification was carried out using a support vector machine model to see the accuracy results. Result/Findings: The results obtained by the ADASYN-SVM method are superior to SMOTE-SVM. The ADASYNSVM method has an accuracy of 87.3%, while the SMOTE-SVM has an accuracy of 85.4%. Novelty/Originality/Value: The data used in this study came from the Karya Medika clinic, Indonesia which contains parameters related to type 2 diabetes.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48510521","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}
Proposed: Prayer is compulsory to worship for Muslims around the world. Prayer is a mandatory commandment from Allah SWT. However, the companions and the Madzhab of Islam have a different opinion but remain Saheeh as long as it does not stray away from the teachings of the Prophet and Al-Quran. This prayer movement consists of the prayer movement of the Madzhab, Imam Shafi'i, Imam Hanafi, Imam Hambali, and Imam Maliki. The Marker used 9 pieces with pictures of each movement. One marker has several shapes of the movements that are several object targets are listed in it. Methods: The Brute Force algorithm used is to match the String value. The Brute Force algorithm can recognize well any String value that is matched to the marker and data from the database. This algorithm is applied to Augmented Reality technology. This app is built using Augmented Reality technology that combines real-world and virtual worlds. Results: This technology is well recognized applied from the Brute Force algorithm, which can validate the match result String value between the database and marker. Novelty: This technology uses the camera to find suitable markers in order to display 3D objects if the marker and the database match. So that this built system can facilitate many circles in learning the prayer movements based on the prayer movement version of islamic high priest.
{"title":"Augmented Reality Using Brute Force Algorithm for Introduction to Prayer Movement Based","authors":"M. Furqan, M. Ikhsan, Irma Yunita Nasution","doi":"10.15294/sji.v8i2.29472","DOIUrl":"https://doi.org/10.15294/sji.v8i2.29472","url":null,"abstract":"Proposed: Prayer is compulsory to worship for Muslims around the world. Prayer is a mandatory commandment from Allah SWT. However, the companions and the Madzhab of Islam have a different opinion but remain Saheeh as long as it does not stray away from the teachings of the Prophet and Al-Quran. This prayer movement consists of the prayer movement of the Madzhab, Imam Shafi'i, Imam Hanafi, Imam Hambali, and Imam Maliki. The Marker used 9 pieces with pictures of each movement. One marker has several shapes of the movements that are several object targets are listed in it. Methods: The Brute Force algorithm used is to match the String value. The Brute Force algorithm can recognize well any String value that is matched to the marker and data from the database. This algorithm is applied to Augmented Reality technology. This app is built using Augmented Reality technology that combines real-world and virtual worlds. Results: This technology is well recognized applied from the Brute Force algorithm, which can validate the match result String value between the database and marker. Novelty: This technology uses the camera to find suitable markers in order to display 3D objects if the marker and the database match. So that this built system can facilitate many circles in learning the prayer movements based on the prayer movement version of islamic high priest.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43343138","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}
Purpose: Face recognition is a geometric space recording activity that allows it to be used to distinguish the features of a face. Therefore, facial recognition can be used to identify ID cards, ATM card PINs, search for one’s committed crimes, terrorists, and other criminals whose faces were not caught by Close-Circuit Television (CCTV). Based on the face image database and by applying the Content-Base Image Retrieval method (CBIR), committed crimes can be recognized on his face. Moreover, the image segmentation technique was carried out before CBIR was applied. This work tried to recognize an individual who committed crimes based on his or her face by using sketch facial images as a query. Methods: We used an image sketch as a querybecause CCTV could not have caught the face image. The research used no less than 1,000 facial images were carried out, both normal as well asabnormal faces (with obstacles). Findings:Experiments demonstrated good enough in terms of precision and recall, which are 0,8 and 0,3 respectively, which is better than at least two previous works.The work demonstrates a precision of 80% which means retrieval of effectiveness is good enough. The 75 queries were carried out in this work to compute the precision and recall of image retrieval. Novelty: Most face recognition researchers using CBIR employed an image as a query. Furthermore, previous work still rarely applied image segmentation as well as CBIR.
{"title":"Image Sketch Based Criminal Face Recognition Using Content Based Image Retrieval","authors":"Adimas Adimas, S. Irianto","doi":"10.15294/sji.v8i2.27865","DOIUrl":"https://doi.org/10.15294/sji.v8i2.27865","url":null,"abstract":"Purpose: Face recognition is a geometric space recording activity that allows it to be used to distinguish the features of a face. Therefore, facial recognition can be used to identify ID cards, ATM card PINs, search for one’s committed crimes, terrorists, and other criminals whose faces were not caught by Close-Circuit Television (CCTV). Based on the face image database and by applying the Content-Base Image Retrieval method (CBIR), committed crimes can be recognized on his face. Moreover, the image segmentation technique was carried out before CBIR was applied. This work tried to recognize an individual who committed crimes based on his or her face by using sketch facial images as a query. Methods: We used an image sketch as a querybecause CCTV could not have caught the face image. The research used no less than 1,000 facial images were carried out, both normal as well asabnormal faces (with obstacles). Findings:Experiments demonstrated good enough in terms of precision and recall, which are 0,8 and 0,3 respectively, which is better than at least two previous works.The work demonstrates a precision of 80% which means retrieval of effectiveness is good enough. The 75 queries were carried out in this work to compute the precision and recall of image retrieval. Novelty: Most face recognition researchers using CBIR employed an image as a query. Furthermore, previous work still rarely applied image segmentation as well as CBIR.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42773130","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}
A. Susanto, Christy Atika Sari, I. U. W. Mulyono, Mohamed Doheir
Purpose: The Javanese script generally has a basic script or is commonly referred to as the “carakan” script. The script consists of 20 letters with different levels of difficulty. Some letters have similarities, so research is needed to make it easier to detect the image of Javanese characters. Methods: This study proposes recognizing Hiragana's writing characters using the K-Nearest Neighbor (K-NN) method. In the preprocessing stage, the segmentation process is carried out using the thresholding method to perform segmentation, followed by the Histogram of Gradient (HOG) feature extraction process and noise removal using median filtering. Histogram of Gradient (HoG) is one of the features used in computer vision and image processing in detecting an object in the form of a descriptor feature. There are 1000 data divided into 20 classes. Each class represents one letter of the basic Javanese script. Result: Based on data collection using the writings of 50 respondents where each respondent writes 20 basic Javanese characters, the highest accuracy was obtained at K = 1, namely 98.5%. Novelty: Using several preprocessing such as cropping, median filtering, otsu thresholding and HOG feature extraction before do classification, this experiment yields a good accuracy.
{"title":"Histogram of Gradient in K-Nearest Neighbor for Javanese Alphabet Classification","authors":"A. Susanto, Christy Atika Sari, I. U. W. Mulyono, Mohamed Doheir","doi":"10.15294/sji.v8i2.30788","DOIUrl":"https://doi.org/10.15294/sji.v8i2.30788","url":null,"abstract":"Purpose: The Javanese script generally has a basic script or is commonly referred to as the “carakan” script. The script consists of 20 letters with different levels of difficulty. Some letters have similarities, so research is needed to make it easier to detect the image of Javanese characters. Methods: This study proposes recognizing Hiragana's writing characters using the K-Nearest Neighbor (K-NN) method. In the preprocessing stage, the segmentation process is carried out using the thresholding method to perform segmentation, followed by the Histogram of Gradient (HOG) feature extraction process and noise removal using median filtering. Histogram of Gradient (HoG) is one of the features used in computer vision and image processing in detecting an object in the form of a descriptor feature. There are 1000 data divided into 20 classes. Each class represents one letter of the basic Javanese script. Result: Based on data collection using the writings of 50 respondents where each respondent writes 20 basic Javanese characters, the highest accuracy was obtained at K = 1, namely 98.5%. Novelty: Using several preprocessing such as cropping, median filtering, otsu thresholding and HOG feature extraction before do classification, this experiment yields a good accuracy.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43368512","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}
Purpose: Halal tourism or muslim friendly tourism has big potential for the tourism industry in Indonesia. According to Cresent Rating, the world’s leading authority on halal-friendly travel, one of the indicators for halal tourism is the availability of choices for halal foods. To support halal tourism, unfortunately, not all restaurants around the tourism object or in the city where the tourism object is located have labels or information that makes people know about halal food in the restaurant easily.Methods/Study design/approach: The data in this research was obtained from online media such as Google Maps, TripAdvisor, and Zoomato. The data consists of 870 data with the classification of halal food restaurants and 590 data with the reverse classification. Machine learning methods were chosen as classifiers. Some of them were Naive Bayes, Support Vector Machine, and K-Nearest Neighbor. Result/Findings: The result from this research shows that the proposed method achieved an accuracy of 95,9% for Support Vector Machine, 93,8% for Multinomial Naive Bayes, and 91% for K-Nearest Neighbor. In the future, our result will be to support the halal tourism environment in terms of technology. Novelty/Originality/Value: In this study, we utilize restaurant reviews done by visitors to get information about the classification of halal food restaurants.
{"title":"Halal Food Restaurant Classification Based on Restaurant Review in Indonesian Language Using Machine Learning","authors":"N. Hidayat, M. Hakim, J. Jumanto","doi":"10.15294/sji.v8i2.33395","DOIUrl":"https://doi.org/10.15294/sji.v8i2.33395","url":null,"abstract":"Purpose: Halal tourism or muslim friendly tourism has big potential for the tourism industry in Indonesia. According to Cresent Rating, the world’s leading authority on halal-friendly travel, one of the indicators for halal tourism is the availability of choices for halal foods. To support halal tourism, unfortunately, not all restaurants around the tourism object or in the city where the tourism object is located have labels or information that makes people know about halal food in the restaurant easily.Methods/Study design/approach: The data in this research was obtained from online media such as Google Maps, TripAdvisor, and Zoomato. The data consists of 870 data with the classification of halal food restaurants and 590 data with the reverse classification. Machine learning methods were chosen as classifiers. Some of them were Naive Bayes, Support Vector Machine, and K-Nearest Neighbor. Result/Findings: The result from this research shows that the proposed method achieved an accuracy of 95,9% for Support Vector Machine, 93,8% for Multinomial Naive Bayes, and 91% for K-Nearest Neighbor. In the future, our result will be to support the halal tourism environment in terms of technology. Novelty/Originality/Value: In this study, we utilize restaurant reviews done by visitors to get information about the classification of halal food restaurants.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41769725","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}
Purpose: This paper reports on the development of a low-power fire potential monitoring system for densely populated housing based on IoT Study design: This system consists of sensors integrated with a microcontroller and a Wi-Fi module that can provide data in real-time and can be accessed remotely. In addition, this system has also been simulated to analyze environmental conditions as notification data sent using cloud messenger. The grouping of potential fire hazards based on the legibility of physical parameter values is also displayed. Findings: In performance measurement, the data loss of this system is less than 1% of the total data every day. Value: It shows that this system is feasible and applied more broadly to anticipate fires in densely populated areas.
{"title":"Real-Time Monitoring: Development of Low Power Fire Detection System for Dense Residential Housing Based on Internet of Things (IoT) and Cloud Messenger","authors":"R. Muhendra, Aisyah Amin","doi":"10.15294/sji.v8i2.30811","DOIUrl":"https://doi.org/10.15294/sji.v8i2.30811","url":null,"abstract":"Purpose: This paper reports on the development of a low-power fire potential monitoring system for densely populated housing based on IoT Study design: This system consists of sensors integrated with a microcontroller and a Wi-Fi module that can provide data in real-time and can be accessed remotely. In addition, this system has also been simulated to analyze environmental conditions as notification data sent using cloud messenger. The grouping of potential fire hazards based on the legibility of physical parameter values is also displayed. Findings: In performance measurement, the data loss of this system is less than 1% of the total data every day. Value: It shows that this system is feasible and applied more broadly to anticipate fires in densely populated areas.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42581157","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}
Dwi Marisa Midyanti, Syamsul Bahri, H. I. Midyanti
Purpose: Cervical cancer is one of the most common types of cancer that kills women worldwide. One way for early detection of cervical cancer risk is by looking at human behavior determinants. Detection of cervical cancer based on behavior determinants has been researched before using Naïve Bayes and Logistic Regression but has never using ADALINE Neural Network. Methods: In this paper, ADALINE proposes to detect early cervical cancer based on the behavior on the UCI dataset. The data used are 72 data, consisting of 21 cervical cancer patients and 51 non-cervical cancer patients. The dataset is divided 70% for training data and 30% for testing data. The learning parameters used are maximum epoch, learning rate, and MSE. Result: MSE generated from ADALINE training process is 0.02 using a learning rate of 0.006 with a maximum epoch of 19. Twenty-two test data obtained an accuracy of 95.5%, and overall data got an accuracy value of 97.2%. Novelty: One alternative method for early detection of cervical cancer based on behavior is ADALINE Neural Network.
{"title":"ADALINE Neural Network For Early Detection Of Cervical Cancer Based On Behavior Determinant","authors":"Dwi Marisa Midyanti, Syamsul Bahri, H. I. Midyanti","doi":"10.15294/sji.v8i2.31064","DOIUrl":"https://doi.org/10.15294/sji.v8i2.31064","url":null,"abstract":"Purpose: Cervical cancer is one of the most common types of cancer that kills women worldwide. One way for early detection of cervical cancer risk is by looking at human behavior determinants. Detection of cervical cancer based on behavior determinants has been researched before using Naïve Bayes and Logistic Regression but has never using ADALINE Neural Network. Methods: In this paper, ADALINE proposes to detect early cervical cancer based on the behavior on the UCI dataset. The data used are 72 data, consisting of 21 cervical cancer patients and 51 non-cervical cancer patients. The dataset is divided 70% for training data and 30% for testing data. The learning parameters used are maximum epoch, learning rate, and MSE. Result: MSE generated from ADALINE training process is 0.02 using a learning rate of 0.006 with a maximum epoch of 19. Twenty-two test data obtained an accuracy of 95.5%, and overall data got an accuracy value of 97.2%. Novelty: One alternative method for early detection of cervical cancer based on behavior is ADALINE Neural Network. ","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46000517","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}
Purpose: Micro, Small, and Medium Enterprises (MSME) is an important part of today's Indonesian economy. The times have allowed many people to do their own business. Along with the many existing businesses, many business actors are marketing for the sustainability of their business. A web-based information system that can accommodate information about Micro, Small, and Medium Enterprises management is one of the main needs for MSME actors themselves. Methods/Study design/approach: In addition, the public can use this web-based information system to obtain detailed information on MSME and MSME products through the web. Making the web using the PHP programming language where the approach taken in the design is the Unified Approach used as a method in object-based system development. Result/Findings: From the final results of this study, it can be concluded that the web-based MSME Activity Management Information System can help mass marketing of MSME players and help related agencies to find out the development of existing MSME. Novelty/Originality/Value: The website was built can help and accelerate the marketing process for existing MSMEs and can be used as a medium of communication between MSMEs and visitors.
{"title":"Digital Management of Micro, Small and Medium Enterprises (MSME) Activities Based on the Unified Approach","authors":"R. Astri, Faradika Faradika, M. A., Ahmad Kamal","doi":"10.15294/sji.v8i2.29339","DOIUrl":"https://doi.org/10.15294/sji.v8i2.29339","url":null,"abstract":"Purpose: Micro, Small, and Medium Enterprises (MSME) is an important part of today's Indonesian economy. The times have allowed many people to do their own business. Along with the many existing businesses, many business actors are marketing for the sustainability of their business. A web-based information system that can accommodate information about Micro, Small, and Medium Enterprises management is one of the main needs for MSME actors themselves. Methods/Study design/approach: In addition, the public can use this web-based information system to obtain detailed information on MSME and MSME products through the web. Making the web using the PHP programming language where the approach taken in the design is the Unified Approach used as a method in object-based system development. Result/Findings: From the final results of this study, it can be concluded that the web-based MSME Activity Management Information System can help mass marketing of MSME players and help related agencies to find out the development of existing MSME. Novelty/Originality/Value: The website was built can help and accelerate the marketing process for existing MSMEs and can be used as a medium of communication between MSMEs and visitors.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47284469","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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