Jurnal Teknologi dan Sistem Komputer最新文献_第3页

An authentication alternative using histogram shifting steganography method 使用直方图移位隐写方法的认证替代方案

Jurnal Teknologi dan Sistem Komputer Pub Date : 2021-01-01 DOI: 10.14710/jtsiskom.2021.13931

Irsandy Maulana Satya Viddin, Antonius Cahya Prihandoko, D. M. Firmansyah

引用次数: 0

Erratum: Optimization of k value and lag parameter of k-nearest neighbor algorithm on the prediction of hotel occupancy rates 勘误:优化k-最近邻算法的k值和滞后参数对酒店入住率的预测

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-12-09 DOI: 10.14710/jtsiskom.2021.14007

Agus Subhan Akbar, R. H. Kusumodestoni

引用次数: 0

Comparison analysis of Euclidean and Gower distance measures on k-medoids cluster k-medoids簇上欧氏距离测度与Gower距离测度的比较分析

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-12-08 DOI: 10.14710/JTSISKOM.2020.13747

Agil Aditya, B. Sari, T. N. Padilah

{"title":"Comparison analysis of Euclidean and Gower distance measures on k-medoids cluster","authors":"Agil Aditya, B. Sari, T. N. Padilah","doi":"10.14710/JTSISKOM.2020.13747","DOIUrl":"https://doi.org/10.14710/JTSISKOM.2020.13747","url":null,"abstract":"K-medoids is a clustering method that uses the distance method to find and classify data that have similarities and inequalities between data. This shows that the determination of the distance measurement method is important because it affects the performance of the k-medoids cluster results. From several studies, it is stated that the Euclidean and Gower methods can be used as measurement methods in clustering with numerical data. This study aims to compare the performance of the k-medoids clustering results on a numerical dataset using the Euclidean and Gower methods. The method used is the Knowledge Discovery in Database (KDD) method. In this study, seven numerical datasets were used and the evaluation of clustering results used silhouette, Dunn, and connectivity values. The Euclidean distance method is superior to the two values of silhouette evaluation and connectivity, it shows that Euclidean has a good data grouping structure, while the Gower is superior to the Dunn value, which shows that the Gower has good cluster separation compared to Euclidean. This study shows that the Euclidean method is superior to the Gower method in the application of the k-medoids algorithm with a numeric dataset.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"9 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48411754","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: 3

Landslide monitoring system based on water adsorption rate utilizing humidity, accelerometer, and temperature sensors 基于水分吸附率的滑坡监测系统，利用湿度、加速度计和温度传感器

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-31 DOI: 10.14710/jtsiskom.2020.13591

F. Budiman, E. Susanto, D. Perdana, Husneni Mukhtar, Yulius Anggoro Pamungkas, Yakobus Yulyanto Kevin

{"title":"Landslide monitoring system based on water adsorption rate utilizing humidity, accelerometer, and temperature sensors","authors":"F. Budiman, E. Susanto, D. Perdana, Husneni Mukhtar, Yulius Anggoro Pamungkas, Yakobus Yulyanto Kevin","doi":"10.14710/jtsiskom.2020.13591","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13591","url":null,"abstract":"This study examines the application of a landslide disaster monitoring system based on soil activity information that utilizes humidity, temperature, and accelerometer sensors. An artificial highland was built as the research object, and the landslide process was triggered by supplying the system with continuous artificial rainfall. The soil activities were observed through its slope movement, temperature, and moisture content, utilizing an accelerometer, temperature, and humidity sensors both in dry and wet conditions. The system could well observe the soil activities, and the obtained data could be accessed in real-time and online mode on a website. The time delay in sending the data to the server was 2 seconds. Moreover, the characteristics of soil porosity and its relevance to soil saturation level due to water pressure were studied as well. Kinetic study showed that the water adsorption to soil followed the intraparticle diffusion model with a coefficient of determination R 2 0.99043. The system prototype should be used to build the information center of disaster mitigation, particularly in Indonesia.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"255-262"},"PeriodicalIF":0.0,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42472514","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: 1

A proposed method for handling an imbalance data in classification of blood type based on Myers-Briggs type indicator 提出了一种基于Myers-Briggs型指标的血型分类数据不平衡处理方法

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-31 DOI: 10.14710/JTSISKOM.2020.13625

Ahmad Taufiq Akbar, Rochmat Husaini, Bagus Muhammad Akbar, S. Saifullah

引用次数: 5

Comparative analysis of classification algorithms for critical land prediction in agricultural cultivation areas 农用地临界土地预测分类算法的比较分析

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-31 DOI: 10.14710/jtsiskom.2020.13668

Deden Istiawan

引用次数: 0

Watermelon ripeness detector using near infrared spectroscopy 西瓜熟度检测器的近红外光谱

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-31 DOI: 10.14710/jtsiskom.2020.13744

Edwin R. Arboleda, Kimberly M. Parazo, C. Pareja

{"title":"Watermelon ripeness detector using near infrared spectroscopy","authors":"Edwin R. Arboleda, Kimberly M. Parazo, C. Pareja","doi":"10.14710/jtsiskom.2020.13744","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13744","url":null,"abstract":"This study aimed to design and develop a watermelon ripeness detector using Near-Infrared Spectroscopy (NIRS). The research problem being solved in this study is developing a prototype wherein the watermelon ripeness can be detected without the need to open it. This detector will save customers from buying unripe watermelon and the farmers from harvesting an unripe watermelon. The researchers attempted to use the NIRS technique in determining the ripeness level of watermelon as it is widely used in the agricultural sector with high-speed analysis. The project was composed of Raspberry Pi Zero W as the microprocessor unit connected to input and output devices, such as the NIR spectral sensor and the OLED display. It was programmed by Python 3 IDLE. The detector scanned a total of 200 watermelon samples. These samples were grouped as 60 % for the training dataset, 20 % for testing, and another 20 % for evaluation. The data sets were collected and are subjected to the Support Vector Machine (SVM) algorithm. Overall, experimental results showed that the detector could correctly classify both unripe and ripe watermelons with 92.5 % accuracy.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"317-322"},"PeriodicalIF":0.0,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48832363","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: 4

Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction 基于树的特征选择齐次集成模型在糖尿病视网膜病变预测中的应用

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-31 DOI: 10.14710/jtsiskom.2020.13669

Tamunopriye Ene Dagogo-George, H. A. Mojeed, A. Balogun, M. Mabayoje, S. A. Salihu

{"title":"Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction","authors":"Tamunopriye Ene Dagogo-George, H. A. Mojeed, A. Balogun, M. Mabayoje, S. A. Salihu","doi":"10.14710/jtsiskom.2020.13669","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13669","url":null,"abstract":"Diabetic Retinopathy (DR) is a condition that emerges from prolonged diabetes, causing severe damages to the eyes. Early diagnosis of this disease is highly imperative as late diagnosis may be fatal. Existing studies employed machine learning approaches with Support Vector Machines (SVM) having the highest performance on most analyses and Decision Trees (DT) having the lowest. However, SVM has been known to suffer from parameter and kernel selection problems, which undermine its predictive capability. Hence, this study presents homogenous ensemble classification methods with DT as the base classifier to optimize predictive performance. Boosting and Bagging ensemble methods with feature selection were employed, and experiments were carried out using Python Scikit Learn libraries on DR datasets extracted from UCI Machine Learning repository. Experimental results showed that Bagged and Boosted DT were better than SVM. Specifically, Bagged DT performed best with accuracy 65.38 %, f-score 0.664, and AUC 0.731, followed by Boosted DT with accuracy 65.42 %, f-score 0.655, and AUC 0.724 when compared to SVM (accuracy 65.16 %, f-score 0.652, and AUC 0.721). These results indicate that DT's predictive performance can be optimized by employing the homogeneous ensemble methods to outperform SVM in predicting DR.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"297-303"},"PeriodicalIF":0.0,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46421531","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: 2

Preprocessing kNN algorithm classification using K-means and distance matrix with students’ academic performance dataset 利用K-means和距离矩阵对学生学习成绩数据集进行kNN算法分类预处理

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-21 DOI: 10.14710/jtsiskom.2020.13874

Sugriyono Sugriyono, M. U. Siregar

引用次数: 7

Sand temperature and moisture monitoring system for turtle nests using Arduino Uno 基于Arduino Uno的海龟巢沙温湿度监测系统

Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-13 DOI: 10.14710/jtsiskom.2020.13725

Hendi Santoso, T. Hestirianoto, I. Jaya

引用次数: 1