This study aims to measure the level of air pollution determined by pollutant gases contained in the air. Pollutants that measure air pollution are PM10 (Special Material), SO2 (Sulfur), NO2 (Nitrogen Oxide), CO (Carbon Monoxide, O3 (Ozone), and NO2 (Nitrogen Oxide), which are related to vehicle use and, according to the choice this pollutant threshold, we will discuss the level of air pollution with the fuzzy mamdani inference method. The results of the pollutant threshold study will then be applied to the rules / rules that are applied using the if-then rules and then the input variables are arranged using weighted averages, variable averages weighted will be determined higher into three levels: low, medium and high. Keywords Decision Tree, Feature Selection, Optimization of Lecturer Assistant Performance, Particle Swarm Optimization.
{"title":"Analysis of Air Pollution Levels in DKI Jakarta Province Using the Mamdani Fuzzy Inference System Method","authors":"Akmal Dirgantara, A. Fauzi, Ginabila Ginabila","doi":"10.31289/jite.v4i1.3804","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3804","url":null,"abstract":"This study aims to measure the level of air pollution determined by pollutant gases contained in the air. Pollutants that measure air pollution are PM10 (Special Material), SO2 (Sulfur), NO2 (Nitrogen Oxide), CO (Carbon Monoxide, O3 (Ozone), and NO2 (Nitrogen Oxide), which are related to vehicle use and, according to the choice this pollutant threshold, we will discuss the level of air pollution with the fuzzy mamdani inference method. The results of the pollutant threshold study will then be applied to the rules / rules that are applied using the if-then rules and then the input variables are arranged using weighted averages, variable averages weighted will be determined higher into three levels: low, medium and high. Keywords Decision Tree, Feature Selection, Optimization of Lecturer Assistant Performance, Particle Swarm Optimization.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"10 1","pages":"97-104"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87928790","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}
Liver disease is an inflammatory disease of the liver and can cause the liver to be unable to function as usual and even cause death. According to WHO (World Health Organization) data, almost 1.2 million people per year, especially in Southeast Asia and Africa, have died from liver disease. The problem that usually occurs is the difficulty of recognizing liver disease early on, even when the disease has spread. This study aims to compare and evaluate Naive Bayes algorithm as a selected algorithm and Naive Bayes algorithm based on Genetic Algorithm (GA) and Bagging to find out which algorithm has a higher accuracy in predicting liver disease by processing a dataset taken from the UCI Machine Learning Repository database (GA). University of California Invene). From the results of testing by evaluating both the confusion matrix and the ROC curve, it was proven that the testing carried out by the Naive Bayes Optimization algorithm using Algortima Genetics and Bagging has a higher accuracy value than only using the Naive Bayes algorithm. The accuracy value for the Naive Bayes algorithm model is 66.66% and the accuracy value for the Naive Bayes model with attribute selection using Genetic Algorithms and Bagging is 72.02%. Based on this value, the difference in accuracy is 5.36%. Keywords: Liver Disease, Naive Bayes, Genetic Agorithms, Bagging.
{"title":"Attribute Selection in Naive Bayes Algorithm Using Genetic Algorithms and Bagging for Prediction of Liver Disease","authors":"Dwi Yuni Utami, Elah Nurlelah, Noer Hikmah","doi":"10.31289/jite.v4i1.3793","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3793","url":null,"abstract":"Liver disease is an inflammatory disease of the liver and can cause the liver to be unable to function as usual and even cause death. According to WHO (World Health Organization) data, almost 1.2 million people per year, especially in Southeast Asia and Africa, have died from liver disease. The problem that usually occurs is the difficulty of recognizing liver disease early on, even when the disease has spread. This study aims to compare and evaluate Naive Bayes algorithm as a selected algorithm and Naive Bayes algorithm based on Genetic Algorithm (GA) and Bagging to find out which algorithm has a higher accuracy in predicting liver disease by processing a dataset taken from the UCI Machine Learning Repository database (GA). University of California Invene). From the results of testing by evaluating both the confusion matrix and the ROC curve, it was proven that the testing carried out by the Naive Bayes Optimization algorithm using Algortima Genetics and Bagging has a higher accuracy value than only using the Naive Bayes algorithm. The accuracy value for the Naive Bayes algorithm model is 66.66% and the accuracy value for the Naive Bayes model with attribute selection using Genetic Algorithms and Bagging is 72.02%. Based on this value, the difference in accuracy is 5.36%. Keywords: Liver Disease, Naive Bayes, Genetic Agorithms, Bagging.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"1 1","pages":"76-85"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79611738","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}
Taufik Rahman, M. U. Nuha, H. Kuswanto, Felix Wuryo Handono
Advances in technology in the field of Android-based applications are expected to bring changes in the world of education intended for English language education. At present the method of searching institute courses that are present in a variety of applications offered, but the existing applications are not yet complete on this matter related to the applications offered do not meet the specific needs of the course institution search applications that are provided in the English village pare. LBS and algotima dijkstra can be used in the analysis and design of android-based applications, it is required an application to search for locations such as applications needed by user in addition to places of study can also find a place to spend the night while studying, where traveling provides the facilities that have been provided. The results of the Go-Course application can conclude that it must meet the needs of users to carry out the process of finding a chair, boarding house, boarding house and travel package from a smartphone by providing a fairly accurate position. By applying the Djikstra algorithm to the Go-Course Application, you can set the shortest route to the boarding house and boarding house with the user's position and current distance in the form of a map. All functions in the Go-Cource application for finding seats, boarding, boarding and tour packages can run correctly through Blackbox Testing and in accordance with manufacturing recommendations. Keywords: LBS, Dijkstra, Android, GPS, Go-Course.
{"title":"Android-based GO-COURSE Application with Location Based Services Method","authors":"Taufik Rahman, M. U. Nuha, H. Kuswanto, Felix Wuryo Handono","doi":"10.31289/jite.v4i1.3765","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3765","url":null,"abstract":"Advances in technology in the field of Android-based applications are expected to bring changes in the world of education intended for English language education. At present the method of searching institute courses that are present in a variety of applications offered, but the existing applications are not yet complete on this matter related to the applications offered do not meet the specific needs of the course institution search applications that are provided in the English village pare. LBS and algotima dijkstra can be used in the analysis and design of android-based applications, it is required an application to search for locations such as applications needed by user in addition to places of study can also find a place to spend the night while studying, where traveling provides the facilities that have been provided. The results of the Go-Course application can conclude that it must meet the needs of users to carry out the process of finding a chair, boarding house, boarding house and travel package from a smartphone by providing a fairly accurate position. By applying the Djikstra algorithm to the Go-Course Application, you can set the shortest route to the boarding house and boarding house with the user's position and current distance in the form of a map. All functions in the Go-Cource application for finding seats, boarding, boarding and tour packages can run correctly through Blackbox Testing and in accordance with manufacturing recommendations. Keywords: LBS, Dijkstra, Android, GPS, Go-Course.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"1 1","pages":"23-32"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79861538","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 definite integral is one of the subjects that is difficult for students to understand because the process of calculating definite integral of functions is quite complicated and long because it requires mastery of some integrating rules so an interactive learning simulation application is needed to make it easier for students to calculate definite integral of functions and the depiction of the area the curve. One method for calculating definite integrals is the trapezoid method. The trapezoid method works by dividing the boundary into 2 intervals namely x = x0 to x = x1. Simulation media application learning will be designed with the VB.Net programming language. This simulation media learning starts with reading and checking data input. The process is continued by displaying the depiction of the input curve and ending with calculating the area of the curve. Simulation media learning provides a facility to store the input data, the results of the calculation of the area and the image of the curve function in the image format of * .bmp. In this media, the media and material expert’s the results of the average are produced by 88.68% included into media category is very valid media and the results of pre-test and post-test trials showed an increase with an average value of 48.3 for pre-test and 87 for the post-test of the passing grade requirement of 70. Keywords: Definite Integral, Trapezoid Method,VB.Net, Media Validation.
{"title":"Design of Simulation Definite Integral Application learning Using Trapezoid Method based on VB.Net","authors":"N. Dharshinni, A. Saleh, F. Azmi, I. Fawwaz","doi":"10.31289/jite.v4i1.3880","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3880","url":null,"abstract":"The definite integral is one of the subjects that is difficult for students to understand because the process of calculating definite integral of functions is quite complicated and long because it requires mastery of some integrating rules so an interactive learning simulation application is needed to make it easier for students to calculate definite integral of functions and the depiction of the area the curve. One method for calculating definite integrals is the trapezoid method. The trapezoid method works by dividing the boundary into 2 intervals namely x = x0 to x = x1. Simulation media application learning will be designed with the VB.Net programming language. This simulation media learning starts with reading and checking data input. The process is continued by displaying the depiction of the input curve and ending with calculating the area of the curve. Simulation media learning provides a facility to store the input data, the results of the calculation of the area and the image of the curve function in the image format of * .bmp. In this media, the media and material expert’s the results of the average are produced by 88.68% included into media category is very valid media and the results of pre-test and post-test trials showed an increase with an average value of 48.3 for pre-test and 87 for the post-test of the passing grade requirement of 70. Keywords: Definite Integral, Trapezoid Method,VB.Net, Media Validation.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"22 1","pages":"193-202"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81464502","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}
Corona virus outbreaks that occur in almost all countries in the world have an impact not only in the health sector, but also in other sectors such as tourism, finance, transportation, etc. This raises a variety of sentiments from the public with the emergence of corona virus as a trending topic on Twitter social media. Twitter was chosen by the public because it can disseminate information in real time and can see market reactions quickly. This research uses "tweet" data or public tweet related to "Corona Virus" to see how the sentiment polarity arises. Text mining techniques and three machine learning classification algorithms are used, including Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) to build a tweet classification model of sentiments whether they have positive, negative, or neutral polarity. The highest test results are generated by the Support Vector Machine (SVM) algorithm with an accuracy value of 76.21%, a precision value of 78.04%, and a recall value of 71.42%. Keywords: Machine Learning, Corona Virus, Twitter, Sentiment Analysis.
在世界上几乎所有国家都发生的冠状病毒疫情不仅对卫生部门产生影响，而且对旅游、金融、交通等其他部门也产生影响。随着冠状病毒在推特(Twitter)上成为热门话题，引发了国民的各种情绪。公众之所以选择Twitter，是因为它可以实时传播信息，并且可以快速看到市场的反应。该研究利用“推特”数据或与“冠状病毒”相关的公开推文，观察情绪极性是如何产生的。使用文本挖掘技术和三种机器学习分类算法，包括朴素贝叶斯，支持向量机(SVM)， k -近邻(K-NN)，构建tweet情绪分类模型，无论它们是积极的，消极的还是中性的极性。支持向量机(SVM)算法生成的测试结果最高，准确率为76.21%，精密度为78.04%，召回率为71.42%。关键词:机器学习，冠状病毒，Twitter，情感分析。
{"title":"Sentiment Analysis on Corona Virus Pandemic Using Machine Learning Algorithm","authors":"Ricky Risnantoyo, A. Nugroho, Kresna Mandara","doi":"10.31289/jite.v4i1.3798","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3798","url":null,"abstract":"Corona virus outbreaks that occur in almost all countries in the world have an impact not only in the health sector, but also in other sectors such as tourism, finance, transportation, etc. This raises a variety of sentiments from the public with the emergence of corona virus as a trending topic on Twitter social media. Twitter was chosen by the public because it can disseminate information in real time and can see market reactions quickly. This research uses \"tweet\" data or public tweet related to \"Corona Virus\" to see how the sentiment polarity arises. Text mining techniques and three machine learning classification algorithms are used, including Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) to build a tweet classification model of sentiments whether they have positive, negative, or neutral polarity. The highest test results are generated by the Support Vector Machine (SVM) algorithm with an accuracy value of 76.21%, a precision value of 78.04%, and a recall value of 71.42%. Keywords: Machine Learning, Corona Virus, Twitter, Sentiment Analysis.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"20 1","pages":"86-96"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81852051","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 growth of device user is always increasing and the costs are not expensive. Users already have several sophisticated end user networking tools for daily use, including laptops, smartphones and tablets. For internet access users use LAN and WLAN network services in several public areas such as restaurants, schools / campuses, hotels and offices. Activities done by the users are data and banking transactions. These activities relate to crucial data such as user data including usernames, passwords, accounts, emails and other sensitive data. Mikrotik Router is a router with an affordable price and complete features for both LAN and WLAN networks so that many administrators use this device. The most common attack used on the network is Man in the Middle Attack, which is actively tapping on the user's network connection, where traffic from the user before reaching the destination or when going through a Mikrotik router will be diverted through the attacker's network without the user's knowledge so that user communication can be read. Therefore a network security system on a Mikrotik router is needed to avoid such attacks. In testing the security system that has been made, it needs the right method, one of which is penetration testing. From the results of testing using the penetration testing method, results and solutions will be obtained to maintain network security. Keywords: Penetration Testing, Man in The Middle Attack, Wireless Security, Router dan Wireless Mikrotik.
设备用户的增长一直在增加，成本并不昂贵。用户已经拥有了几种复杂的终端用户日常使用的网络工具，包括笔记本电脑、智能手机和平板电脑。对于互联网接入用户使用局域网和无线局域网网络服务在几个公共区域，如餐馆，学校/校园，酒店和办公室。用户完成的活动是数据和银行事务。这些活动涉及关键数据，如用户数据，包括用户名、密码、帐户、电子邮件和其他敏感数据。Mikrotik Router是一款价格合理、功能齐全的路由器，适用于LAN和WLAN网络，因此许多管理员都使用该设备。在网络上使用的最常见的攻击是中间人攻击(Man in The Middle attack)，它是主动利用用户的网络连接，在用户到达目的地之前或经过microtik路由器时，流量将在用户不知情的情况下通过攻击者的网络被转移，从而可以读取用户的通信。因此，需要在microtik路由器上安装网络安全系统来避免此类攻击。在对已制成的安全系统进行测试时，需要采用正确的方法，其中一种方法就是渗透测试。通过使用渗透测试方法进行测试，得到维护网络安全的结果和解决方案。关键词:渗透测试;中间人攻击;无线安全;
{"title":"Security Design And Testing of Lan and Wlan Network in Mikrotik Router Using Penetration Testing Method FROM Mitm Attack","authors":"H. .","doi":"10.31289/jite.v4i1.3832","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3832","url":null,"abstract":"The growth of device user is always increasing and the costs are not expensive. Users already have several sophisticated end user networking tools for daily use, including laptops, smartphones and tablets. For internet access users use LAN and WLAN network services in several public areas such as restaurants, schools / campuses, hotels and offices. Activities done by the users are data and banking transactions. These activities relate to crucial data such as user data including usernames, passwords, accounts, emails and other sensitive data. Mikrotik Router is a router with an affordable price and complete features for both LAN and WLAN networks so that many administrators use this device. The most common attack used on the network is Man in the Middle Attack, which is actively tapping on the user's network connection, where traffic from the user before reaching the destination or when going through a Mikrotik router will be diverted through the attacker's network without the user's knowledge so that user communication can be read. Therefore a network security system on a Mikrotik router is needed to avoid such attacks. In testing the security system that has been made, it needs the right method, one of which is penetration testing. From the results of testing using the penetration testing method, results and solutions will be obtained to maintain network security. Keywords: Penetration Testing, Man in The Middle Attack, Wireless Security, Router dan Wireless Mikrotik.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"37 1","pages":"119-127"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90926717","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}
Nowadays Students often use social media as a tool to communicate and search for a lot of information, social media can also influence changes in the self-image of students shared on social media. This study aims to determine the large social media users of Instagram among students, to analyze Instagram social media as a tool used by students in self-development and self-image, to know the importance of digital marketing in shaping student self-image, analyzing the development of students' Self Presentations, knowing how large students in showing self-image using Instagram social media, knowing the importance of Self Presentation within the university. This study uses variables namely digital marketing, and Self Image as independent variables, Self Presentation as the dependent variable. The target respondents of this study were all university students in the city of Batam by using a sample of 392 students. This research concluded that self image plays a role in shaping student self-appearance because students try to look neat and attractive when uploading videos on Instagram Stories about themselves, wanting to look good in photos or videos, so users can display a good image and other Instagram users who see can give good comments as well. Keywords: Social Media, Instagram, Digital Marketing, Self Image, Self Presentation.
{"title":"Analysis Role of Digital Marketing and Self Image Improving Student Self Presentation in Batam Using Instagram","authors":"M. Ardiansyah","doi":"10.31289/jite.v4i1.3849","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3849","url":null,"abstract":"Nowadays Students often use social media as a tool to communicate and search for a lot of information, social media can also influence changes in the self-image of students shared on social media. This study aims to determine the large social media users of Instagram among students, to analyze Instagram social media as a tool used by students in self-development and self-image, to know the importance of digital marketing in shaping student self-image, analyzing the development of students' Self Presentations, knowing how large students in showing self-image using Instagram social media, knowing the importance of Self Presentation within the university. This study uses variables namely digital marketing, and Self Image as independent variables, Self Presentation as the dependent variable. The target respondents of this study were all university students in the city of Batam by using a sample of 392 students. This research concluded that self image plays a role in shaping student self-appearance because students try to look neat and attractive when uploading videos on Instagram Stories about themselves, wanting to look good in photos or videos, so users can display a good image and other Instagram users who see can give good comments as well. Keywords: Social Media, Instagram, Digital Marketing, Self Image, Self Presentation.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"1 1","pages":"128-141"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89344288","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}
Calculation of subnetting IP Address manually is quite time consuming and difficult for people who are just learning. With current smartphone technology, especially those using the Android operating system. There are many things that can be done with smartphones nowadays, including studying subnetting IP address calculations. The purpose of this study is to design and build a mobile application to facilitate the study of subnetting IP Address calculations with the Android operating system. The research method used is a waterfall with stages of requirements, design, implementation, and testing. This research resulted in a mobile application for calculating IP Address subnetting that will facilitate studying and accelerating the calculation of IP Address subnetting. This application is able to search for subnet masks, number of subnets, number of hosts per subnet, IP broadcast, IP range, network ID, and there is a theoretical explanation of the IP Address, prefix, and range of each class of IP Address. The results of the study are indicated by the level of eligibility of this application based on a questionnaire from users with results, 41% strongly agree, 44% agree, 13% neutral, and 2% disagree. Keywords: IP Address, Subneting, Application, Android.
{"title":"Calculation Application for Subnetting IPv4 Address on Android","authors":"S. Hidayatulloh, Prawira Maulana Ilham, M. Lase","doi":"10.31289/jite.v4i1.3827","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3827","url":null,"abstract":"Calculation of subnetting IP Address manually is quite time consuming and difficult for people who are just learning. With current smartphone technology, especially those using the Android operating system. There are many things that can be done with smartphones nowadays, including studying subnetting IP address calculations. The purpose of this study is to design and build a mobile application to facilitate the study of subnetting IP Address calculations with the Android operating system. The research method used is a waterfall with stages of requirements, design, implementation, and testing. This research resulted in a mobile application for calculating IP Address subnetting that will facilitate studying and accelerating the calculation of IP Address subnetting. This application is able to search for subnet masks, number of subnets, number of hosts per subnet, IP broadcast, IP range, network ID, and there is a theoretical explanation of the IP Address, prefix, and range of each class of IP Address. The results of the study are indicated by the level of eligibility of this application based on a questionnaire from users with results, 41% strongly agree, 44% agree, 13% neutral, and 2% disagree. Keywords: IP Address, Subneting, Application, Android.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"38 1","pages":"112-118"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80312391","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}
Mufid Junaedi, Ahmad Fachrurozi, Mochammad Rizky Kusumayudha, W. Gata
Terrorist attacks are now being global issue both in developing and developed countries. There are more than 180,000 terrorist attacks in 1970-2017. Indonesia is one of the countries attacked by terorist. Bombings and firearms cause fatalities. Classification of terorist attacks can be performed based on either the attack succed or not. Succed attack is defined as an unavoided action that caused fatalities. There are seven attributes studied in this paper: year, month, attack type, terorist name, target attack, city, and weapon type uses to attack. Evaluations shows that k-NN classiefier exerts the highest accuracy of 90.79%, followed by naive bayes 80.45%, and C4.5 of 88.825%. Keywords: Indonesia Terrorist, Classification Algorithm, Terorist Algorithm Classification.
{"title":"Analysis of the classification of terrorist attacks in Indonesia","authors":"Mufid Junaedi, Ahmad Fachrurozi, Mochammad Rizky Kusumayudha, W. Gata","doi":"10.31289/jite.v4i1.3788","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3788","url":null,"abstract":"Terrorist attacks are now being global issue both in developing and developed countries. There are more than 180,000 terrorist attacks in 1970-2017. Indonesia is one of the countries attacked by terorist. Bombings and firearms cause fatalities. Classification of terorist attacks can be performed based on either the attack succed or not. Succed attack is defined as an unavoided action that caused fatalities. There are seven attributes studied in this paper: year, month, attack type, terorist name, target attack, city, and weapon type uses to attack. Evaluations shows that k-NN classiefier exerts the highest accuracy of 90.79%, followed by naive bayes 80.45%, and C4.5 of 88.825%. Keywords: Indonesia Terrorist, Classification Algorithm, Terorist Algorithm Classification.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"26 1","pages":"57-66"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73872477","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}
Indonesia has abundant natural resources, especially the results of its plantations. Lots of local fruit that can be used starting from the root to the skin of the fruit. Local fruit can be consumed as fresh fruit and can also be processed into drinks and food. This is reflected in the diversity of tropical fruits found in Indonesia. Fruits that are rich in benefits and can be used as medicines such as Apples, Avocados, Apricots, and Bananas. These fruits are often found around us. In Indonesia these fruits are produced and also exported abroad. However, the limited methods and technology used to classify this fruit are interesting things to discuss and become the main focus in this research. This study analyzed using the Naive Bayes algorithm and feature extraction of HOG (Oriented Gradient Histogram) to obtain more effective classification results. The results showed that the collection of fruit using the Naive Bayes method and HOG feature extraction had not yet obtained maximum classification results, only with an accuracy of 56.52%. Keywords – Apple, Avocado, Apricot, Banana, Naive Bayes, HOG.
{"title":"Analysis Naïve Bayes In Classifying Fruit by Utilizing Hog Feature Extraction","authors":"Muhathir Muhathir, M. H. Santoso","doi":"10.31289/jite.v4i1.3860","DOIUrl":"https://doi.org/10.31289/jite.v4i1.3860","url":null,"abstract":"Indonesia has abundant natural resources, especially the results of its plantations. Lots of local fruit that can be used starting from the root to the skin of the fruit. Local fruit can be consumed as fresh fruit and can also be processed into drinks and food. This is reflected in the diversity of tropical fruits found in Indonesia. Fruits that are rich in benefits and can be used as medicines such as Apples, Avocados, Apricots, and Bananas. These fruits are often found around us. In Indonesia these fruits are produced and also exported abroad. However, the limited methods and technology used to classify this fruit are interesting things to discuss and become the main focus in this research. This study analyzed using the Naive Bayes algorithm and feature extraction of HOG (Oriented Gradient Histogram) to obtain more effective classification results. The results showed that the collection of fruit using the Naive Bayes method and HOG feature extraction had not yet obtained maximum classification results, only with an accuracy of 56.52%. Keywords – Apple, Avocado, Apricot, Banana, Naive Bayes, HOG.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":"43 1","pages":"151-160"},"PeriodicalIF":1.2,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81500609","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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