Pub Date : 2022-09-29DOI: 10.37385/jaets.v4i1.1015
Aldiga Rienarti Abidin, Yuda Irawan, Yesica Devis
Along with the times, one of the environmental problems faced today is the waste problem. Every day humans will produce waste, both industrial waste and household waste in everyday life. Garbage will become an environmental problem because it can interfere with human health, cause bad smells and even air pollution. Poor waste management causes harmful and unhealthy environmental problems. Sometimes people are reluctant when they want to dispose of garbage by opening and closing the trash can so it is feared that they will get bacteria on their hands. The problem of environmental waste can arise from waste management that unites all types of organic and inorganic waste in the same place, making it difficult to recycle waste. Another problem is that sometimes the cleaners are negligent in emptying the full trash can, so it will cause a bad smell. Based on the above problems, it is necessary to make a smart trash bin which will later be able to sort out the types of organic and inorganic waste. The lid of the trash can will open automatically when someone wants to throw out the trash and it will close automatically when it's finished taking out the trash. With the waste sorting technology, it will automatically reduce environmental pollution by waste, and facilitate waste management so that it can be recycled again. To overcome the bins that are full for too long, if the trash is full, it will automatically notify the cleaners via Telegram messages. From the test results, it can be concluded that the ultrasonic sensor can detect if someone is approaching with a maximum distance of 50 cm so that the cover can be opened automatically for 7 seconds. The servo motor can rotate the waste sorter according to the type of organic or inorganic waste based on the detection results of the capacitive proximity sensor. The telegram message has been successfully sent if the garbage condition has been fully detected through the ultrasonic sensor. LCD can display the type of organic or inorganic waste accurately.
{"title":"Smart Trash Bin for Management of Garbage Problem in Society","authors":"Aldiga Rienarti Abidin, Yuda Irawan, Yesica Devis","doi":"10.37385/jaets.v4i1.1015","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.1015","url":null,"abstract":"Along with the times, one of the environmental problems faced today is the waste problem. Every day humans will produce waste, both industrial waste and household waste in everyday life. Garbage will become an environmental problem because it can interfere with human health, cause bad smells and even air pollution. Poor waste management causes harmful and unhealthy environmental problems. Sometimes people are reluctant when they want to dispose of garbage by opening and closing the trash can so it is feared that they will get bacteria on their hands. The problem of environmental waste can arise from waste management that unites all types of organic and inorganic waste in the same place, making it difficult to recycle waste. Another problem is that sometimes the cleaners are negligent in emptying the full trash can, so it will cause a bad smell. Based on the above problems, it is necessary to make a smart trash bin which will later be able to sort out the types of organic and inorganic waste. The lid of the trash can will open automatically when someone wants to throw out the trash and it will close automatically when it's finished taking out the trash. With the waste sorting technology, it will automatically reduce environmental pollution by waste, and facilitate waste management so that it can be recycled again. To overcome the bins that are full for too long, if the trash is full, it will automatically notify the cleaners via Telegram messages. From the test results, it can be concluded that the ultrasonic sensor can detect if someone is approaching with a maximum distance of 50 cm so that the cover can be opened automatically for 7 seconds. The servo motor can rotate the waste sorter according to the type of organic or inorganic waste based on the detection results of the capacitive proximity sensor. The telegram message has been successfully sent if the garbage condition has been fully detected through the ultrasonic sensor. LCD can display the type of organic or inorganic waste accurately.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47071428","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 : 2022-09-18DOI: 10.37385/jaets.v4i1.1012
I. Nugraha, Falaah Abdussallam
Population or demography is the study of the dynamics of the human population. Demographics includes the size, structure and distribution of a population, and how the population changes over time as a result of births, deaths, migration, and aging. The current population system is still using the manual method, namely using the form provided by the Pajajaran Village, which is deemed less effective and efficient, therefore, there are often miscalculations of the number of residents when reporting to the Cicendo District, Bandung City. This study aims to analyze and design a population system. The design of this population information system uses PHP Native programming and MySQL Database Management System. With the existence of a web-based information system, it is hoped that it will facilitate the making of valid and not fictitious population reports
{"title":"Design of The Population Information System in The Village of Pajajaran","authors":"I. Nugraha, Falaah Abdussallam","doi":"10.37385/jaets.v4i1.1012","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.1012","url":null,"abstract":"Population or demography is the study of the dynamics of the human population. Demographics includes the size, structure and distribution of a population, and how the population changes over time as a result of births, deaths, migration, and aging. The current population system is still using the manual method, namely using the form provided by the Pajajaran Village, which is deemed less effective and efficient, therefore, there are often miscalculations of the number of residents when reporting to the Cicendo District, Bandung City. This study aims to analyze and design a population system. The design of this population information system uses PHP Native programming and MySQL Database Management System. With the existence of a web-based information system, it is hoped that it will facilitate the making of valid and not fictitious population reports","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47138140","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}
Betel leaf is one of the plants that is widely used as a natural or traditional medicine by the community, natural treatment with the use of plants is relatively safer. But there is a problem when we choose healthy betel leaves because of our mistakes in choosing which betel leaves are healthy and which are not. With this research the authors aim to detect healthy and sick betel leaves using data collection. Feature extraction used is the value of Red, Green, and Blue (RGB) and Hue, Saturation, and Value (HSV) to get the characteristics of the color image. Then the results of the feature extraction are used to classify the health of green betel leaves using the Self-Organizing Maps method. The green betel leaf data used is 1500 images for train data and 450 images for testing data are image test data, test data that produces an evaluation value with an accuracy value of 97.20% on the Self-Organizing Maps method.
槟榔叶是被社会广泛用作天然或传统药物的植物之一，用植物进行自然治疗比较安全。但是，当我们选择健康的槟榔叶时，有一个问题，因为我们在选择哪些槟榔叶是健康的，哪些是不健康的时犯了错误。在这项研究中，作者的目的是通过数据收集来检测健康和生病的槟榔叶。特征提取使用的是Red, Green, and Blue (RGB)和Hue, Saturation, and value (HSV)的值来获得彩色图像的特征。然后利用特征提取的结果，利用自组织地图方法对槟榔叶的健康度进行分类。使用的槟榔叶数据为1500张图像，为列车数据，450张图像为测试数据，测试数据在Self-Organizing Maps方法上产生准确率为97.20%的评价值。
{"title":"Health Detection of Betal Leaves Using Self-Organizing Map and Thresholding Algorithm","authors":"Dadang Iskandar Mulyana, Ahmad Saepudin, M. Yel","doi":"10.37385/jaets.v4i1.957","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.957","url":null,"abstract":"Betel leaf is one of the plants that is widely used as a natural or traditional medicine by the community, natural treatment with the use of plants is relatively safer. But there is a problem when we choose healthy betel leaves because of our mistakes in choosing which betel leaves are healthy and which are not. With this research the authors aim to detect healthy and sick betel leaves using data collection. Feature extraction used is the value of Red, Green, and Blue (RGB) and Hue, Saturation, and Value (HSV) to get the characteristics of the color image. Then the results of the feature extraction are used to classify the health of green betel leaves using the Self-Organizing Maps method. The green betel leaf data used is 1500 images for train data and 450 images for testing data are image test data, test data that produces an evaluation value with an accuracy value of 97.20% on the Self-Organizing Maps method.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46196377","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}
Rian Farta Wijaya, Ataya Putri, H. Hermansyah, Nova Mayasari, Rio Septian Hardinata, Mochammad Iswan Perangin-angin
This research is entitled the application of recognizing preparation for earthquakes for elementary school students. The goal is to produce an application that can help students recognize preparation for earthquakes. The resulting application is made using Adobe Flash CS 6, and the Actionscript 3 programming language. This application can run well on Android smartphones, and personal computers/laptops. There were 20 students who were the subjects of this study, and they came from elementary schools Negeri 105270 Pujimulio, Deli Serdang, North Sumatra. Students who are tested beforehand (pre-test) their knowledge about preparation in dealing with earthquakes. After that students are asked to use the resulting application. After that, students are tested again for their knowledge (post test). So from the pre test and post test carried out, get test results that show an increase in students' knowledge in learningknow how to prepare for an earthquake.
{"title":"Applications Know Preparation for Earthquakes for Elementary School Students","authors":"Rian Farta Wijaya, Ataya Putri, H. Hermansyah, Nova Mayasari, Rio Septian Hardinata, Mochammad Iswan Perangin-angin","doi":"10.37385/jaets.v4i1.995","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.995","url":null,"abstract":"This research is entitled the application of recognizing preparation for earthquakes for elementary school students. The goal is to produce an application that can help students recognize preparation for earthquakes. The resulting application is made using Adobe Flash CS 6, and the Actionscript 3 programming language. This application can run well on Android smartphones, and personal computers/laptops. There were 20 students who were the subjects of this study, and they came from elementary schools Negeri 105270 Pujimulio, Deli Serdang, North Sumatra. Students who are tested beforehand (pre-test) their knowledge about preparation in dealing with earthquakes. After that students are asked to use the resulting application. After that, students are tested again for their knowledge (post test). So from the pre test and post test carried out, get test results that show an increase in students' knowledge in learningknow how to prepare for an earthquake.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44009406","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}
Sign language is a language that prioritizes communication with hands, body language, and lip movements to communicate. The deaf are the main group who use this language, often combining hand shape, hand, arm and body orientation and movement, and facial expressions to express their thoughts. The sign language detection system is designed using the Adaptive Neuro Fuzzy Inference System (ANFIS). This study uses data from the kaggle.com dataset, which is a site that provides research data on artificial intelligence. This study was conducted to recognize empty hand signals. Where it will help users naturally without any additional help. The test is carried out using a data set as evidenced by 1 display. In this process, The characteristics of the hand were carried out using the Histogram Oriented Gradient (HOG) method. Meanwhile, to separate it from the background image, it is used with color segmentation. The results of the process are then taken for classification. The classification process uses the Adaptive Neuro Fuzzy Inference System method. The results of the tests carried out for accuracy are as much as
{"title":"Sign Language Detection System Using Adaptive Neuro Fuzzy Inference System (ANFIS) Method","authors":"D. Iskandar, M. Yel, Eka Maheswara","doi":"10.37385/jaets.v4i1.967","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.967","url":null,"abstract":"Sign language is a language that prioritizes communication with hands, body language, and lip movements to communicate. The deaf are the main group who use this language, often combining hand shape, hand, arm and body orientation and movement, and facial expressions to express their thoughts. The sign language detection system is designed using the Adaptive Neuro Fuzzy Inference System (ANFIS). This study uses data from the kaggle.com dataset, which is a site that provides research data on artificial intelligence. This study was conducted to recognize empty hand signals. Where it will help users naturally without any additional help. The test is carried out using a data set as evidenced by 1 display. In this process, The characteristics of the hand were carried out using the Histogram Oriented Gradient (HOG) method. Meanwhile, to separate it from the background image, it is used with color segmentation. The results of the process are then taken for classification. The classification process uses the Adaptive Neuro Fuzzy Inference System method. The results of the tests carried out for accuracy are as much as","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47021734","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}
The purpose of this research is to create a waste burner using raw materials from factory welding waste. The method used in this research is the value engineering method. In Gununggansir Village, there is an increase in waste, one of which is in Kedung Turi Hamlet, which is very significant, causing a buildup of garbage and inadequate waste management in Gununggangsir Village. This is an alternative that is made is an environmentally friendly waste incinerator. The process of making a garbage incinerator has the advantage of being environmentally friendly by using used goods that are not used and can still be used. In this research, what will be done is utilizing used goods that have value and function to achieve a target value. The result of using this used material is that it saves the cost of making Trush Burner which was originally worth Rp. 1,626,000 to Rp. 965,000.
{"title":"Design of Appropriate Technology Based on Waste Treatment Equipment Using Value Engineering Method in Kedung Turi","authors":"Sultan Afli, B. I. Putra","doi":"10.37385/jaets.v4i1.965","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.965","url":null,"abstract":"The purpose of this research is to create a waste burner using raw materials from factory welding waste. The method used in this research is the value engineering method. In Gununggansir Village, there is an increase in waste, one of which is in Kedung Turi Hamlet, which is very significant, causing a buildup of garbage and inadequate waste management in Gununggangsir Village. This is an alternative that is made is an environmentally friendly waste incinerator. The process of making a garbage incinerator has the advantage of being environmentally friendly by using used goods that are not used and can still be used. In this research, what will be done is utilizing used goods that have value and function to achieve a target value. The result of using this used material is that it saves the cost of making Trush Burner which was originally worth Rp. 1,626,000 to Rp. 965,000.\u0000 ","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41515577","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}
Edelweiss is a plant that grows at a height, and is known as a perennial flower because it has beautiful petals and does not wilt easily. Although edelweiss in Indonesia is still in the same family as Leontopodium Alpinum, it turns out that the type of edelweiss found in the mountains of Indonesia is different from edelweiss found abroad. Therefore, in this study, an image processing system was developed that can classify the types of edelweiss flowers based on their image using Linear Discriminant Analysis to classify data into several classes based on the boundary line (straight line) obtained from linear equations. In this study, the types of edelweiss flowers used in this study were Anaphalis Javanica and Leontopodium Alpinum, the two types of edelweiss flowers were distinguished based on their color characteristics using hue and saturation values. The images used are 1500 images for training data and 450 test data images with a training and test data ratio of 70:30, so that the accuracy produced in the testing process is 99.77% in the Linear Discriminant Analysis method.
{"title":"Classification of Edelweiss Flowers Using Data Augmentation and Linear Discriminant Analysis Methods","authors":"Fransiscus Rolanda Malau, Dadang Iskandar Mulyana","doi":"10.37385/jaets.v4i1.960","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.960","url":null,"abstract":"Edelweiss is a plant that grows at a height, and is known as a perennial flower because it has beautiful petals and does not wilt easily. Although edelweiss in Indonesia is still in the same family as Leontopodium Alpinum, it turns out that the type of edelweiss found in the mountains of Indonesia is different from edelweiss found abroad. Therefore, in this study, an image processing system was developed that can classify the types of edelweiss flowers based on their image using Linear Discriminant Analysis to classify data into several classes based on the boundary line (straight line) obtained from linear equations. In this study, the types of edelweiss flowers used in this study were Anaphalis Javanica and Leontopodium Alpinum, the two types of edelweiss flowers were distinguished based on their color characteristics using hue and saturation values. The images used are 1500 images for training data and 450 test data images with a training and test data ratio of 70:30, so that the accuracy produced in the testing process is 99.77% in the Linear Discriminant Analysis method.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49463478","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}
This study aims to detect the ripeness of melinjo fruit using digital image method. Structured identification or division using image processing and computer vision requires the socialization of patterns based on training datasets. Melinjo (Gnetum gnemon L.) is a plant that can grow anywhere, such as yards, gardens, or on the sidelines of residential areas, as a result, produces melinjo into a plant that has relatively large potential to be developed. The process of image processing and pattern socialization is a highly developed research study. Starting based on the process of socializing an object, or a structured division of the object and about detecting the level of fruit maturity. The structured division process regarding ripeness into 3 classes, namely: raw, half-cooked and ripe where the process is carried out using Google Collaboratory which processes the RGB color space to HSV. In this study, the testing method for the system that will be used is a functional test where the test is carried out only by observing the execution results through test data and checking the functionality of the system being developed. The level of accuracy obtained from this study is 98.0% correct.
{"title":"Classification of Melinjo Fruit Levels Using Skin Color Detection With RGB and HSV","authors":"D. Iskandar, M. Marjuki","doi":"10.37385/jaets.v4i1.958","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.958","url":null,"abstract":"This study aims to detect the ripeness of melinjo fruit using digital image method. Structured identification or division using image processing and computer vision requires the socialization of patterns based on training datasets. Melinjo (Gnetum gnemon L.) is a plant that can grow anywhere, such as yards, gardens, or on the sidelines of residential areas, as a result, produces melinjo into a plant that has relatively large potential to be developed. The process of image processing and pattern socialization is a highly developed research study. Starting based on the process of socializing an object, or a structured division of the object and about detecting the level of fruit maturity. The structured division process regarding ripeness into 3 classes, namely: raw, half-cooked and ripe where the process is carried out using Google Collaboratory which processes the RGB color space to HSV. In this study, the testing method for the system that will be used is a functional test where the test is carried out only by observing the execution results through test data and checking the functionality of the system being developed. The level of accuracy obtained from this study is 98.0% correct.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47862766","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}
Covid-19 is a respiratory infection that is transmitted through the air. The first case was reported on March 2, 2020, to be precise in Depok, West Java, Indonesia. To reduce the number of corona virus sufferers, the government has made various efforts including policies to limit activities outside the home, online learning, work from home, and even worship activities. To reduce the number of people infected with the Covid-19 virus, efforts are being made, one of which is the provision of vaccines. In this study, the types of booster vaccines are Pfizer and AstraZeneca. Due to the symptoms caused by the condition of the patient after vaccination, the researchers used the Naive Bayes Algorithm and C4.5 methods with attributes including gender, age, comorbidities (comorbidities), temperature, blood pressure, Covid 19 survivors > 1 month, pregnant condition, type of vaccine. primer and booster vaccine types which aim to get the highest accuracy value between the two algorithm methods which are tested using cross validation on the RapidMiner Studio tool. And obtained the Naive Bayes algorithm method with the highest accuracy value of 78.82%. Keywords: Covid 19, booster, AEFI, Naive Bayes, C4.5, Rapid Miner
{"title":"Classification of Booster Vaccination Symptoms Using Naive Bayes Algorithm and C4.5","authors":"Rudi Tri Jaya, Tri Wahyudi","doi":"10.37385/jaets.v4i1.941","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.941","url":null,"abstract":"Covid-19 is a respiratory infection that is transmitted through the air. The first case was reported on March 2, 2020, to be precise in Depok, West Java, Indonesia. To reduce the number of corona virus sufferers, the government has made various efforts including policies to limit activities outside the home, online learning, work from home, and even worship activities. To reduce the number of people infected with the Covid-19 virus, efforts are being made, one of which is the provision of vaccines. In this study, the types of booster vaccines are Pfizer and AstraZeneca. Due to the symptoms caused by the condition of the patient after vaccination, the researchers used the Naive Bayes Algorithm and C4.5 methods with attributes including gender, age, comorbidities (comorbidities), temperature, blood pressure, Covid 19 survivors > 1 month, pregnant condition, type of vaccine. primer and booster vaccine types which aim to get the highest accuracy value between the two algorithm methods which are tested using cross validation on the RapidMiner Studio tool. And obtained the Naive Bayes algorithm method with the highest accuracy value of 78.82%. \u0000Keywords: Covid 19, booster, AEFI, Naive Bayes, C4.5, Rapid Miner","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44594212","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}
Durian is one of the most popular fruits because it has a delicious taste and distinctive aroma. It has different shapes and types, especially from thorns and different colors and has fruit parts that are also not the same as other parts. In terms of fruit selection, care must be taken because consumers generally still find it difficult to distinguish physically identified types of Durian fruit due to limited knowledge of the types of Durian fruit and require a relatively long time and accuracy in sorting. Therefore, there is a need for a method to sort the types of Durian fruit effectively and efficiently. Namely image segmentation based on the classification of the types of Durian fruit to help consumers. The method used is Gray Level Co-Occurrence Matrices for feature extraction, while to determine the proximity between the test image and the training image using the K-Nearest Neighbor method based on texture based on the color of the Durian fruit obtained. Extraction features using the GLCM method based on angles of 0°, 45°, 90° and 135°. Then the KNN method is used for the classification of characteristic results using K = 3. In this study, 1281 data training was used and 321 data testing was used, resulting in an accuracy of 93%.
{"title":"Classification of Durian Types Using Features Extraction Gray Level Co-Occurrence Matrix (GLCM) AND K-Nearest Neighbors (KNN)","authors":"Frencis Matheos Sarimole, Achmad Syaeful","doi":"10.37385/jaets.v4i1.959","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.959","url":null,"abstract":"Durian is one of the most popular fruits because it has a delicious taste and distinctive aroma. It has different shapes and types, especially from thorns and different colors and has fruit parts that are also not the same as other parts. In terms of fruit selection, care must be taken because consumers generally still find it difficult to distinguish physically identified types of Durian fruit due to limited knowledge of the types of Durian fruit and require a relatively long time and accuracy in sorting. Therefore, there is a need for a method to sort the types of Durian fruit effectively and efficiently. Namely image segmentation based on the classification of the types of Durian fruit to help consumers. The method used is Gray Level Co-Occurrence Matrices for feature extraction, while to determine the proximity between the test image and the training image using the K-Nearest Neighbor method based on texture based on the color of the Durian fruit obtained. Extraction features using the GLCM method based on angles of 0°, 45°, 90° and 135°. Then the KNN method is used for the classification of characteristic results using K = 3. In this study, 1281 data training was used and 321 data testing was used, resulting in an accuracy of 93%.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45570117","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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