Journal of Information Technology Education-Innovations in Practice最新文献_第6页

Network Device Monitoring System based on Geographic Information System dan Simple Network Management Protocol 基于地理信息系统和简单网络管理协议的网络设备监控系统

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3187

A. Hizriadi, Radea Shiddiq, Ivan Jaya, S. Prayudani

{"title":"Network Device Monitoring System based on Geographic Information System dan Simple Network Management Protocol","authors":"A. Hizriadi, Radea Shiddiq, Ivan Jaya, S. Prayudani","doi":"10.31289/jite.v3i2.3187","DOIUrl":"https://doi.org/10.31289/jite.v3i2.3187","url":null,"abstract":"Network infrastructure monitoring is an important part of an institute to maintain the stability of computer network devices. One of the functions of computer network monitoring is to find out the data traffic generated in network application. Simple Network Management Protocol is one of protocols for monitoring the data traffic in network device. However, network device administrators still have problems when they want to monitor their network infrastructure, such as device location and data traffic information of network device that is only temporarily stored in the monitoring system, and physical location of network device is not contained in the monitoring system. In order to make it easier for them how to monitor network devices, the Researcher intends to combine Geographic Information Systems (GIS) and SNMP into a web-based monitoring application. Geographic Information System application can display the physical location of network devices, whilethe SNMP application using for monitoring the data traffic in network device,finding out the data traffic that can be generated in real time, and displaying data traffic of network device that has been monitored in to graphical form based on the time and network device used.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81741813","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

Comparative Compression of Wavelet Haar Transformation with Discrete Wavelet Transform on Colored Image Compression 小波变换与离散小波变换在彩色图像压缩中的比较

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3154

Christnatalis Christnatalis, B. Bachtiar, Rony Rony

{"title":"Comparative Compression of Wavelet Haar Transformation with Discrete Wavelet Transform on Colored Image Compression","authors":"Christnatalis Christnatalis, B. Bachtiar, Rony Rony","doi":"10.31289/jite.v3i2.3154","DOIUrl":"https://doi.org/10.31289/jite.v3i2.3154","url":null,"abstract":"In this research, the algorithm used to compress images is using the haar wavelet transformation method and the discrete wavelet transform algorithm. The image compression based on Wavelet Wavelet transform uses a calculation system with decomposition with row direction and decomposition with column direction. While discrete wavelet transform-based image compression, the size of the compressed image produced will be more optimal because some information that is not so useful, not so felt, and not so seen by humans will be eliminated so that humans still assume that the data can still be used even though it is compressed. The data used are data taken directly, so the test results are obtained that digital image compression based on Wavelet Wavelet Transformation gets a compression ratio of 41%, while the discrete wavelet transform reaches 29.5%. Based on research problems regarding the efficiency of storage media, it can be concluded that the right algorithm to choose is the Haar Wavelet transformation algorithm. To improve compression results it is recommended to use wavelet transforms other than haar, such as daubechies, symlets, and so on.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80660881","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

Initial Centroid Optimization of K-Means Algorithm Using Cosine Similarity 基于余弦相似度的k -均值算法初始质心优化

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3211

F. Azmi, Kevin Utama, Oki Thomas Gurning, Syukurman Ndraha

引用次数: 2

Indonesian Text Dataset for Determining Sentiment Classification Using Mechine Learning Approach 使用机器学习方法确定情感分类的印度尼西亚文本数据集

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3153

I. Syahputra, Tulus Tulus, S. Efendi

{"title":"Indonesian Text Dataset for Determining Sentiment Classification Using Mechine Learning Approach","authors":"I. Syahputra, Tulus Tulus, S. Efendi","doi":"10.31289/jite.v3i2.3153","DOIUrl":"https://doi.org/10.31289/jite.v3i2.3153","url":null,"abstract":"Advances in information technology encourage the emergence of unlimited textual information with the use of online media developing so rapidly that the emergence of the need for information presentation without reducing the value of the information presented. Basicaly the concept of the dataset is a general form of almost every discipline, where the dataset provides empirical basic information for research activities. Sentiment analysis is done to see opinions or feelings about a problem or identify and classify information trends from the problem. The dataset analysis in determining sentiment classification is a model of sentiment classification that has relevance to the dataset with the use of machine learning techniques with supervision that learns from experience to predict output from labeled input data and output from machine learning. The results of experiments and tests that have been carried out on machine learning techniques with supervision can classify sentiments in the tweet text properly and the level of accuracy can still be improved to a better direction with data namely baseline 100 (days) and 83 (weeks), naivebayes 100 (days) and 82 (weeks), maxent 100 (days) and 83 (weeks), and SVM 100 (days) and 83 (weeks).","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91333639","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 Implementation of the RAD model in the Development of Tender Selection Programs Using the AHP Method 应用层次分析法制定招投标方案的RAD模型的实现

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3232

R. Rudianto

{"title":"The Implementation of the RAD model in the Development of Tender Selection Programs Using the AHP Method","authors":"R. Rudianto","doi":"10.31289/jite.v3i2.3232","DOIUrl":"https://doi.org/10.31289/jite.v3i2.3232","url":null,"abstract":"The activity of selecting bidders is one of the most important activities carried out by companies to order goods or services for bidders, but at meetings of the company leadership it is difficult to select bidders to make business partners because there are only a few things that are not in accordance with who agree to end the shipment of goods, prices do not match and end the company that receives losses. That is caused by the lack of competence of selected tender partners. From the problems mentioned above, the tender selection process that has been conducted so far is still lacking and inaccurate. The purpose of this study is to create an application program using the Rapid Application Development Model (RAD Model) that can assist leaders in selecting business partners through a tender process by giving weights according to the criteria specified requirements. It is expected that the tender selection process is objective and accurate. Assessment method Decision making (SPK) Analytichal Hierarchy Process (AHP) method is one method in the process of resolution by completing each case by completing it first by using weighting criteria. In the end the selection application program can help lead in making objective, fast and accurate decisions.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75065135","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

Classification of facial expressions using SVM and HOG 基于SVM和HOG的面部表情分类

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3182

J. Tanjung, Muhathir Muhathir

引用次数: 11

Face Recognition based Feature Extraction using Principal Component Analysis (PCA) 基于主成分分析的人脸识别特征提取

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3132

M. Z. Nasution

引用次数: 6

The Application of Fuzzy-Analytical Hierarchy Process Method for Majors Selection at Public Universities 模糊层次分析法在公立大学专业选择中的应用

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-20 DOI: 10.31289/jite.v3i2.3245

Addin Aditya, Febry Eka Purwiantono

{"title":"The Application of Fuzzy-Analytical Hierarchy Process Method for Majors Selection at Public Universities","authors":"Addin Aditya, Febry Eka Purwiantono","doi":"10.31289/jite.v3i2.3245","DOIUrl":"https://doi.org/10.31289/jite.v3i2.3245","url":null,"abstract":"The purpose of this research is to build a decision support model for prospective students in choosing undergraduate programs at state universities after they accomplished their high school. There are more than 800 undergraduate programs from science and technology departments from 40 state universities in Indonesia. In this research, we use the Fuzzy Analytical Hierarchy Process (F-AHP) to model a decision. This method is chosen because able to make comparisons between criteria more complex than other DSS (Decision Support System) methods. For the criteria used in this research is computer-based test result, student capacity in 2019 and the people who interest in those majors in 2018. The main result of this research is a ranking of science and technology departments at 40 state universities in Indonesia. The results of this research are expected to be able to assist students in choosing majors that will be taken after graduation in their school. In addition, the method of this research can also be continued in subsequent researches that are similar (theoretically). Whereas practically, this method can be implemented every year using different data.","PeriodicalId":43632,"journal":{"name":"Journal of Information Technology Education-Innovations in Practice","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89616686","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

The relation between the first and second multipliers of a semivalue 半值的第一乘子和第二乘子之间的关系

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2020-01-01 DOI: 10.12988/jite.2020.996

D. Pombo

引用次数: 0

Pengenalan Pola Logo Merk Mobil dengan Menggunakan Algoritma Deteksi Tepi Prewitt dan Jaringan Saraf Tiruan Backpropagation

IF 1.2

Journal of Information Technology Education-Innovations in Practice Pub Date : 2018-02-14 DOI: 10.31289/JITE.V1I2.1404

Sudirman M.Kom.

引用次数: 1