Lontar Komputer最新文献

The Optimization of the ARP Poisoning Attack Detection Model Using a Similar Approach Based on NetFlow Analysis 基于NetFlow分析的类似方法优化ARP中毒攻击检测模型

Lontar Komputer Pub Date : 2023-11-06 DOI: 10.24843/lkjiti.2023.v14.i02.p05

Yohanes Priyo Atmojo, Dandy Pramana Hostiadi, I Made Darma Susila, Made Liandana, Gede Angga Pradipta, Putu Desiana Wulaning Ayu

{"title":"The Optimization of the ARP Poisoning Attack Detection Model Using a Similar Approach Based on NetFlow Analysis","authors":"Yohanes Priyo Atmojo, Dandy Pramana Hostiadi, I Made Darma Susila, Made Liandana, Gede Angga Pradipta, Putu Desiana Wulaning Ayu","doi":"10.24843/lkjiti.2023.v14.i02.p05","DOIUrl":"https://doi.org/10.24843/lkjiti.2023.v14.i02.p05","url":null,"abstract":"Information security and threats are a concern in the cyber era. Attacks can be malicious activities. One of them is known as ARP poisoning attack activity, which attacks by falsifying a computer's identity through illegal access to retrieve confidential information in a target computer. Besides, it has also caused service deadlocks in the network. Previous studies have been introduced for the ARP Attack Detection model using rule-based and mining-based. Still, they cannot show optimal detection performance and obtain high false positive results. This paper proposed a detection model for ARP poisoning attacks using a similarity measurement approach adopting cosine similarity. The goal is to obtain measurements of host activities similar to ARP poisoning attacks. The experiment results showed that the model got an accuracy of 97.25%, recall of 96.43%, and precision of 81% with a similarity threshold value of 0.488. Comparison results with previous studies showed higher detection accuracy than previous studies and some classification methods. It shows that the model can improve intrusion detection performance and facilitate network administrators to analyze ARP poisoning attacks in computer networks.","PeriodicalId":31196,"journal":{"name":"Lontar Komputer","volume":"22 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135679164","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}

引用次数: 0

Refining Content-Based Segmentation for Prediction of Coffee Bean Quality 改进基于内容的咖啡豆质量分割预测

Lontar Komputer Pub Date : 2023-11-06 DOI: 10.24843/lkjiti.2023.v14.i02.p04

Suhendro Yusuf Irianto

引用次数: 0

Digital Transformation Of Subak Management In Bali Through GIS Implementation 通过GIS实现巴厘岛苏巴克管理的数字化转型

Lontar Komputer Pub Date : 2023-11-04 DOI: 10.24843/lkjiti.2023.v14.i02.p03

Shilta Inda Qurroti A'yun Achmadi, Anjela Faye M. Basco, Oka Sudana, Ni Kadek Dwi Rusjayanthi

引用次数: 0

Comparing Support Vector Machine and Naïve Bayes Methods with A Selection of Fast Correlation Based Filter Features in Detecting Parkinson's Disease 比较支持向量机和Naïve贝叶斯方法在帕金森病检测中的快速相关特征选择

Lontar Komputer Pub Date : 2023-11-04 DOI: 10.24843/lkjiti.2023.v14.i02.p02

Yuniar Farida, Nurissaidah Ulinnuha, Silvia Kartika Sari, Latifatun Nadya Desinaini

{"title":"Comparing Support Vector Machine and Naïve Bayes Methods with A Selection of Fast Correlation Based Filter Features in Detecting Parkinson's Disease","authors":"Yuniar Farida, Nurissaidah Ulinnuha, Silvia Kartika Sari, Latifatun Nadya Desinaini","doi":"10.24843/lkjiti.2023.v14.i02.p02","DOIUrl":"https://doi.org/10.24843/lkjiti.2023.v14.i02.p02","url":null,"abstract":"Dopamine levels fall due to brain nerve cell destruction, producing Parkinson's symptoms. Humans with this illness experience central nervous system damage, which lowers the quality of life. This disease is not deadly, but when people's quality of life decreases, they cannot perform daily activities as people do. Even in one case, this disease can cause death indirectly. Contrast support vector machines (SVM) and naive Bayesian approaches with and without fast correlation-based filter (FCBF) feature selection, this study attempts to determine the optimum model to detect Parkinson's disease categorization. In this study, datasets from the UCI Machine Learning Repository are used. The results showed that SVM with FCBF achieved the highest accuracy among all the models tested. SVM with FCBF provides an accuracy of 86.1538%, sensitivity of 93.8775%, and specificity of 62.5000%. Both methods, SVM and Naive Bayes, have improved in performance due to FCBF, with SVM showing a more significant increase in accuracy. This research contributed to helping paramedics determine if a patient has Parkinson's disease or not using characteristics obtained from data, such as movement, sound, or other pertinent factors.","PeriodicalId":31196,"journal":{"name":"Lontar Komputer","volume":"29 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135775336","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}

引用次数: 0

Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data 利用谷歌趋势数据预测Ngurah Rai机场的飞机乘客数量

Lontar Komputer Pub Date : 2023-10-30 DOI: 10.24843/lkjiti.2023.v14.i01.p02

I Putu Juni Adi Widianata, Nori Wilantika

{"title":"Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data","authors":"I Putu Juni Adi Widianata, Nori Wilantika","doi":"10.24843/lkjiti.2023.v14.i01.p02","DOIUrl":"https://doi.org/10.24843/lkjiti.2023.v14.i01.p02","url":null,"abstract":"Data on the number of aircraft passengers is essential to airport managers and the government's policies. The policy relates to improving the facilities and capacity of airports and other affected sectors, such as the transportation and tourism industries. A policy taken will be better if the data used is very close to the time of policy decision-making. Therefore, a technique is needed to forecast very close to the current condition of the number of aircraft passengers, namely nowcasting. One of the data sources that can be used for nowcasting is Google Trends data. In this study, the identification of relevant keywords used for nowcasting, the formation of nowcasting models, and the search for the best model for nowcasting the number of aircraft passengers was carried out. The nowcasting methods used are SARIMAX and multilayer perceptron. In this study, five relevant keywords were generated for domestic departures and two for international departures. In the nowcasting modeling, the best model for nowcasting domestic departures is produced, namely the multilayer perceptron with MAPE and MAE values of 11.194% and 28.048 respectively, while for departures Internationally, the best model was produced, namely SARIMAX with MAPE and MAE values of 8,641% and 50,205 respectively.","PeriodicalId":31196,"journal":{"name":"Lontar Komputer","volume":"38 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136106931","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}

引用次数: 0

Real-time Face Recognition System Using Deep Learning Method 基于深度学习方法的实时人脸识别系统

Lontar Komputer Pub Date : 2023-10-30 DOI: 10.24843/lkjiti.2023.v14.i01.p06

Ayu Wirdiani, I Ketut Gede Darma Putra, Made Sudarma, Rukmi Sari Hartati, Lennia Savitri Azzahra Lofiana

引用次数: 0

Business Process Analysis with Business Process Improvement Method Case Study: University Integrated Registration Management System 基于业务流程改进方法的业务流程分析——以高校综合注册管理系统为例

Lontar Komputer Pub Date : 2023-10-30 DOI: 10.24843/lkjiti.2023.v14.i01.p05

Oka Sudana, I Made Suwija Putra, Pradita Dewi

{"title":"Business Process Analysis with Business Process Improvement Method Case Study: University Integrated Registration Management System","authors":"Oka Sudana, I Made Suwija Putra, Pradita Dewi","doi":"10.24843/lkjiti.2023.v14.i01.p05","DOIUrl":"https://doi.org/10.24843/lkjiti.2023.v14.i01.p05","url":null,"abstract":"The university's integrated registration management system is a system to facilitate the registration of prospective new students at University X. A good registration system should be able to provide accurate, and relevant information to improve the quality of the information system. The quality improving can be done with business process analysis. In this research business process analysis is done using business process improvement methods (BPI) up to phase 3, namely streamlining. The data to be analyzed is obtained from the results of questionnaires distributed to stakeholders. Determination of quality factor indicators on questionnaire questions using the McCall framework. The questionnaire results showed a business process that is categorized as critical, namely Study Program Transfer with an average value of 80%, Quality factors categorized as critical are Correctness 80% and Integrity 51% and Scholarship Application Management with an average value of quality factor 78%, quality factors categorized critically are Correctness 80% and Integrity 53%. Recommendations for business process improvement in the form of draft Standard Operating Procedures (SOP) also flowchart using streamlining with bureaucracy elimination and upgrading simplification tools in the process of moving management program and management of waiver submissions.","PeriodicalId":31196,"journal":{"name":"Lontar Komputer","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136106932","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}

引用次数: 0

Associative Classification with Classification Based Association (CBA) Algorithm on Transaction Data with Rshiny 基于Rshiny交易数据的关联分类与基于分类的关联(CBA)算法

Lontar Komputer Pub Date : 2023-10-28 DOI: 10.24843/lkjiti.2023.v14.i01.p03

Alesia Arum Frederika, I Putu Agung Bayupati, Wira Buana

{"title":"Associative Classification with Classification Based Association (CBA) Algorithm on Transaction Data with Rshiny","authors":"Alesia Arum Frederika, I Putu Agung Bayupati, Wira Buana","doi":"10.24843/lkjiti.2023.v14.i01.p03","DOIUrl":"https://doi.org/10.24843/lkjiti.2023.v14.i01.p03","url":null,"abstract":"Data mining can be used for businesses with large amounts of data. One of the data mining techniques is Associative Classification. It is a new strategy in data processing that combines association and classification techniques to build a classification model. This research used an associative classification technique on sales transaction data of Frozen Food Stores, which had sales transaction data on their business activities. It would be used in sales strategies to find items often purchased by class customers, namely, members and general. This research aimed to classify based on association rules using the CBA (Classification based Association) algorithm on sales transaction data. The application used the R programming language that business owners could use. The results of the rules obtained from the trial had the value of support, confidence, coverage, and lift ratio, which were the best value levels of a rule. The results of the rules that had the highest lift ratio value from all the data that have been inputted can be used as a reference to be implemented in sales strategies in knowing consumer needs.","PeriodicalId":31196,"journal":{"name":"Lontar Komputer","volume":"173 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136233379","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}

引用次数: 0

The Use of XGBoost Algorithm to Analyse the Severity of Traffic Accident Victims 利用XGBoost算法分析交通事故受害者的严重程度

Lontar Komputer Pub Date : 2023-10-27 DOI: 10.24843/lkjiti.2023.v14.i01.p04

I Made Sukarsa, Ni Kadek Dwi Rusjayanthi, Made Srinitha Millinia Utami, Ni Wayan Wisswani

{"title":"The Use of XGBoost Algorithm to Analyse the Severity of Traffic Accident Victims","authors":"I Made Sukarsa, Ni Kadek Dwi Rusjayanthi, Made Srinitha Millinia Utami, Ni Wayan Wisswani","doi":"10.24843/lkjiti.2023.v14.i01.p04","DOIUrl":"https://doi.org/10.24843/lkjiti.2023.v14.i01.p04","url":null,"abstract":"Traffic accidents are still significant contributors to a fairly high death. Denpasar’s resort police record every traffic accident in the form of a daily report. The stored data can generate valuable information to improve policies and propagate better traffic practices. This research utilizes the classification technique with the XGBoost, random forest algorithm, and SMOTE method. The study shows that the SMOTE technique can increase the model's accuracy. Using the classification method with the two algorithms produces factors that affect the severity of traffic accident victims with feature importance. The feature importance obtained using the XGBoost model by counting the weight value for testing using the original dataset, the dataset for the type of two-wheeled vehicle, and the dataset of the kind of vehicle other than two-wheeled indicate that the variables influencing the severity of victims in road accidents are the time of accident between 00.00-06.00, the type of vehicle motorcycle, the type of opponent vehicle truck and pickup car, the age of the driver between 16-25, sub-district road status and front – side type of accident.","PeriodicalId":31196,"journal":{"name":"Lontar Komputer","volume":"56 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136319000","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}

引用次数: 0

Detecting Pests and Diseases in Plants Using Efficient Network 利用高效网络检测植物病虫害

Lontar Komputer Pub Date : 2023-08-30 DOI: 10.24843/lkjiti.2023.v14.i02.p01

Mardhiya Hayaty, Timur Haryo Mahissanular

引用次数: 0