Pub Date : 2023-02-01DOI: 10.20895/infotel.v15i1.861
S. Fuada, Muhamad Dzikri Danuarteu, Sarah Agustin, Anindya Afina Carmelya, Iffah Fadhilah, Yee Mei Heong, A. Kaewpukdee
PhET is one of the most powerful and impressive simulator innovations, widely used in the STEM-based learning process. Based on literature reviews, students are allowed to independently practice their skills and understanding of the material concept using this tool. PheT involves students in process competencies comprehensively and also provides a highly interactive virtual environment for STEM materials, including basic electronics, a sub-category of physics. This tool can also be easily accessed online at https://phet.colorado.edu/ or offline with a note that the user should download and install the application on a PC. An interesting question regarding this education tool is, "can PhET support basic electronics learning in Higher Education (HE)?" Numerous preliminary studies have not answered this question, which is associated with the technical aspect of the tool, because they only focused on the pedagogical aspect. Therefore, this research aims to fill this gap by exploring the capability of PhET in simulating basic electronic circuits that were commonly studied by students in HE, including Kirchoff Current Law (Kirchoof I), Kirchoff Voltage Law (Kirchoff II), Voltage Divider, Series/Parallel Resistors, Wheatstone Bridge, and Star – Delta Resistors. These circuits are simulated in two PhET products, namely, online (1.2.7) and offline (3.20) versions, with numerous setups used to compare their performances to the theoretical calculations. Finally, the answers were obtained clearly from the experimental results in the simulation environment.
{"title":"Can PhET simulate basic electronics circuits for undergraduate students?","authors":"S. Fuada, Muhamad Dzikri Danuarteu, Sarah Agustin, Anindya Afina Carmelya, Iffah Fadhilah, Yee Mei Heong, A. Kaewpukdee","doi":"10.20895/infotel.v15i1.861","DOIUrl":"https://doi.org/10.20895/infotel.v15i1.861","url":null,"abstract":"PhET is one of the most powerful and impressive simulator innovations, widely used in the STEM-based learning process. Based on literature reviews, students are allowed to independently practice their skills and understanding of the material concept using this tool. PheT involves students in process competencies comprehensively and also provides a highly interactive virtual environment for STEM materials, including basic electronics, a sub-category of physics. This tool can also be easily accessed online at https://phet.colorado.edu/ or offline with a note that the user should download and install the application on a PC. An interesting question regarding this education tool is, \"can PhET support basic electronics learning in Higher Education (HE)?\" Numerous preliminary studies have not answered this question, which is associated with the technical aspect of the tool, because they only focused on the pedagogical aspect. Therefore, this research aims to fill this gap by exploring the capability of PhET in simulating basic electronic circuits that were commonly studied by students in HE, including Kirchoff Current Law (Kirchoof I), Kirchoff Voltage Law (Kirchoff II), Voltage Divider, Series/Parallel Resistors, Wheatstone Bridge, and Star – Delta Resistors. These circuits are simulated in two PhET products, namely, online (1.2.7) and offline (3.20) versions, with numerous setups used to compare their performances to the theoretical calculations. Finally, the answers were obtained clearly from the experimental results in the simulation environment.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45570249","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 : 2023-02-01DOI: 10.20895/infotel.v15i1.856
Anindita Septiarini, H. Hamdani, E. Winarno
Dayak is one of the tribes in East Kalimantan, Indonesia, which has a lot of cultural wealth. Beads craft is one of the Dayak traditional cultures made using various materials with distinctive motifs. The Dayak beads have many different motifs and color combinations. Hence not everyone can distinguish between the bead motif of Dayak and non-Dayak easily. This study aims to develop a bead detection method to differentiate between the bead types of Dayak and non-Dayak. The main processes required include preprocessing, feature extraction, and classification. The features were extracted based on color and texture. Experiments were carried out using several machine learning approaches. The highest results were achieved using the combination of color and texture features with the implementation of K-Nearest Neighbor (KNN) methods as indicated by the parameters precision, recall, and accuracy achieved of 92%, 92%, and 92.2% using Cross-Validation with a K-Fold value of 10.
{"title":"The combination of color-texture features and machine learning for detecting Dayak beads","authors":"Anindita Septiarini, H. Hamdani, E. Winarno","doi":"10.20895/infotel.v15i1.856","DOIUrl":"https://doi.org/10.20895/infotel.v15i1.856","url":null,"abstract":"Dayak is one of the tribes in East Kalimantan, Indonesia, which has a lot of cultural wealth. Beads craft is one of the Dayak traditional cultures made using various materials with distinctive motifs. The Dayak beads have many different motifs and color combinations. Hence not everyone can distinguish between the bead motif of Dayak and non-Dayak easily. This study aims to develop a bead detection method to differentiate between the bead types of Dayak and non-Dayak. The main processes required include preprocessing, feature extraction, and classification. The features were extracted based on color and texture. Experiments were carried out using several machine learning approaches. The highest results were achieved using the combination of color and texture features with the implementation of K-Nearest Neighbor (KNN) methods as indicated by the parameters precision, recall, and accuracy achieved of 92%, 92%, and 92.2% using Cross-Validation with a K-Fold value of 10.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42067438","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 : 2023-02-01DOI: 10.20895/infotel.v15i1.871
Andri Agustav Wirabudi, Nurwan Reza Fachrurrozi
In Indonesia, Tea is an important economic crop that is widely grown, and in many countries, accurate mapping of tea plantations is essential for the operation, management, and monitoring of the growth and development of the tea industry. We propose a classification of tea plantations using orthomosaics from aerial images based on the Convolutional Neural Network (CNN) which identifies the condition of the tea plantations with the parameters observed, namely the condition of the tea leaves, estimated yields achieved, and monitoring of treeless areas caused by tree death. In this study, we took a sample of 20 hectares. We classify images based on maps generated by drones in previous studies. Image segmentation is performed to maintain image objects, while an enhanced CNN model is used to extract deep image features. To get complete results, this study uses UAV (Unmanned Aerial Vehicle) imagery as the basis for the map, which is then combined or stacked into one image. The results of the images that are used as maps undergo image classification, where the information contained in the map is mapped and divided according to its type. The area of the tea plantations sampled is 20 ha, and the threshold for the image captured by the UAV is 5% of the total area captured, which is around 1 ha. If the image created by the UAV has an error of more than 5%, then the image does not meet the classification requirements. We determine this margin of error based on the performance of the drone camera capture when capturing Fig. 2, and the resolution used is 4096 x 2160 for each image captured by the drone. We conclude that the proposed method for mapping tea plantations using ultra-high resolution remote sensing imagery is effective and has great potential for mapping tea plantations in areas such as the development of drone aerial photography methods for tea plantations based on image classification for forecasting. tea plantations Image stitching can be used to improve the monitoring of tea plantations and predict harvest time using a classification process. The tea garden map has 5 types of information categorized by harvest time, medium leaf tea, milled tea, tea, and old tea. The success of image recognition shows the error matrix data by testing 123 random points spread over the map, of which 113 random points were identified with an average accuracy of 91.87%, this value is of course very good and exceeds the specified threshold of 75%. When using this method, an error occurs that the colors of similar pixels cannot be distinguished, resulting in an incorrect detection. In addition, the image stitching method using the orthomosaics method has succeeded in performing image stitching and can be well applied to classification using the CNN approach.
在印度尼西亚，茶叶是一种广泛种植的重要经济作物，在许多国家，准确绘制茶园地图对于茶叶行业的运营、管理和监测增长和发展至关重要。我们提出了一种基于卷积神经网络（CNN）的茶园分类方法，该方法利用观测到的参数来识别茶园的状况，即茶叶的状况、估计的产量以及对树木死亡造成的无树区域的监测。在这项研究中，我们抽取了20公顷的样本。我们根据之前研究中无人机生成的地图对图像进行分类。执行图像分割以维护图像对象，同时使用增强的CNN模型来提取深度图像特征。为了获得完整的结果，本研究使用无人机图像作为地图的基础，然后将其组合或堆叠成一张图像。用作地图的图像的结果经过图像分类，其中包含在地图中的信息被映射并根据其类型进行划分。的面积采样的茶园面积为20公顷，无人机拍摄的图像的阈值为拍摄总面积的5%，约为1公顷。如果无人机创建的图像误差超过5%，则该图像不符合分类要求。我们根据无人机相机拍摄图时的性能来确定这个误差幅度。2，无人机拍摄的每个图像使用的分辨率为4096 x 2160。我们得出的结论是，所提出的使用超高分辨率遥感图像绘制茶园地图的方法是有效的，并且在绘制地区茶园地图方面具有巨大的潜力，例如开发基于图像分类的茶园无人机航空摄影方法进行预测。茶园图像拼接可以用于改进对茶园的监控，并使用分类过程预测收获时间。茶园地图有5种类型的信息，按收获时间、中叶茶、碾磨茶、茶和老茶分类。图像识别的成功通过测试分布在地图上的123个随机点显示了误差矩阵数据，其中113个随机点被识别，平均准确率为91.87%，这个值当然非常好，超过了75%的指定阈值。使用此方法时，会出现无法区分相似像素的颜色的错误，从而导致错误检测。此外，使用正交马赛克方法的图像拼接方法已经成功地执行了图像拼接，并且可以很好地应用于使用CNN方法的分类。
{"title":"Classification of tea plantation using orthomosaics stitching maps from aerial images based on CNN","authors":"Andri Agustav Wirabudi, Nurwan Reza Fachrurrozi","doi":"10.20895/infotel.v15i1.871","DOIUrl":"https://doi.org/10.20895/infotel.v15i1.871","url":null,"abstract":"In Indonesia, Tea is an important economic crop that is widely grown, and in many countries, accurate mapping of tea plantations is essential for the operation, management, and monitoring of the growth and development of the tea industry. We propose a classification of tea plantations using orthomosaics from aerial images based on the Convolutional Neural Network (CNN) which identifies the condition of the tea plantations with the parameters observed, namely the condition of the tea leaves, estimated yields achieved, and monitoring of treeless areas caused by tree death. In this study, we took a sample of 20 hectares. We classify images based on maps generated by drones in previous studies. Image segmentation is performed to maintain image objects, while an enhanced CNN model is used to extract deep image features. To get complete results, this study uses UAV (Unmanned Aerial Vehicle) imagery as the basis for the map, which is then combined or stacked into one image. The results of the images that are used as maps undergo image classification, where the information contained in the map is mapped and divided according to its type. The area of the tea plantations sampled is 20 ha, and the threshold for the image captured by the UAV is 5% of the total area captured, which is around 1 ha. If the image created by the UAV has an error of more than 5%, then the image does not meet the classification requirements. We determine this margin of error based on the performance of the drone camera capture when capturing Fig. 2, and the resolution used is 4096 x 2160 for each image captured by the drone. We conclude that the proposed method for mapping tea plantations using ultra-high resolution remote sensing imagery is effective and has great potential for mapping tea plantations in areas such as the development of drone aerial photography methods for tea plantations based on image classification for forecasting. tea plantations Image stitching can be used to improve the monitoring of tea plantations and predict harvest time using a classification process. The tea garden map has 5 types of information categorized by harvest time, medium leaf tea, milled tea, tea, and old tea. The success of image recognition shows the error matrix data by testing 123 random points spread over the map, of which 113 random points were identified with an average accuracy of 91.87%, this value is of course very good and exceeds the specified threshold of 75%. When using this method, an error occurs that the colors of similar pixels cannot be distinguished, resulting in an incorrect detection. In addition, the image stitching method using the orthomosaics method has succeeded in performing image stitching and can be well applied to classification using the CNN approach.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49080562","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 : 2022-11-26DOI: 10.20895/infotel.v14i4.836
Putu Wiweka Prasetyananda, S. Sudiro, B. A. Wardijono
This paper proposes a prototype fire monitoring system with Wireless Sensor Network (WSN) in order to detect fires in several places at once and facilitate the placement of the detection. WSN is a technology where several sensors work together to establish communication over a wireless network. This prototype fire monitoring system can be monitored through the website in real time and the detection data is stored on the cloud server. This prototype fire monitoring system uses 4 sensor nodes, each of which is placed in several places to detect fires and sends the detection results to the master node. The master node receives and processes the data sent by the sensor node to generate 16 different conditions concurrently, in the event of a fire it will send a telegram message and the condition data to the cloud server. Several attempts to send data from the sensor node to the master node were completely successful and sending data from the master node to the cloud server as well as sending notification messages have been sent properly.
{"title":"Concurrently wireless sensor network using microcontroller for home monitoring against fire","authors":"Putu Wiweka Prasetyananda, S. Sudiro, B. A. Wardijono","doi":"10.20895/infotel.v14i4.836","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.836","url":null,"abstract":"This paper proposes a prototype fire monitoring system with Wireless Sensor Network (WSN) in order to detect fires in several places at once and facilitate the placement of the detection. WSN is a technology where several sensors work together to establish communication over a wireless network. This prototype fire monitoring system can be monitored through the website in real time and the detection data is stored on the cloud server. This prototype fire monitoring system uses 4 sensor nodes, each of which is placed in several places to detect fires and sends the detection results to the master node. The master node receives and processes the data sent by the sensor node to generate 16 different conditions concurrently, in the event of a fire it will send a telegram message and the condition data to the cloud server. Several attempts to send data from the sensor node to the master node were completely successful and sending data from the master node to the cloud server as well as sending notification messages have been sent properly.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48643687","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 : 2022-11-26DOI: 10.20895/infotel.v14i4.822
R. Ainul
Location information of the object based on wireless communication will play crucial role in several Wireless Sensor Network (WSN) applications. Some applications need to know the exact position of the object. The advantages of Zigbee as the part of Radio Frequency (RF) technology such as low cost, high scalability, high availability, and supporting topology for Indoor positioning system (IPS). In this paper, we propose IPS using Received Signal Strength Indicator (RSSI) based Zigbee protocol. The proposed approach is based on the enhancement of Trilateration algorithm. Basically, the main concept of the conventional trilateration is using three strongest RSSI from references node. However, the instability from measured RSSI influenced to its estimation result. Therefore quadratic weighted is adding to this proposed scheme as the enhanced trilateration algorithm. The estimated distance output from conventional trilateration algorithm will be used for calculating the weighted value and multiplying to each the reference node which produced lower estimation error. The simulation result show that using enhanced trilateration algorithm has capability to improve accuracy of estimated position up to 90.55 % with mean square error (MSE) 2.03 meters compared with only using conventional trilateration reached high estimated error up to 4.31 meters.
在无线传感器网络(WSN)的应用中，基于无线通信的物体位置信息将起着至关重要的作用。一些应用程序需要知道对象的确切位置。Zigbee作为射频(Radio Frequency)技术的一部分，具有低成本、高可扩展性、高可用性、支持室内定位系统(IPS)拓扑结构等优势。在本文中，我们提出了基于RSSI (Received Signal Strength Indicator)的Zigbee协议的IPS。该方法是基于对三边检测算法的改进。基本上，传统三边测量的主要概念是使用来自参考节点的三个最强RSSI。然而，实测RSSI的不稳定性影响了其估计结果。因此，在该方案中加入二次加权算法作为增强的三边检测算法。将传统三边算法的估计距离输出用于计算加权值，并将产生较小估计误差的参考节点乘到每个节点上。仿真结果表明，与传统三边测量相比，采用改进的三边测量可将位置估计精度提高到90.55%，均方误差(MSE)为2.03 m，估计误差高达4.31 m。
{"title":"An enhanced trilateration algorithm for indoor RSSI based positioning system using zigbee protocol","authors":"R. Ainul","doi":"10.20895/infotel.v14i4.822","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.822","url":null,"abstract":"Location information of the object based on wireless communication will play crucial role in several Wireless Sensor Network (WSN) applications. Some applications need to know the exact position of the object. The advantages of Zigbee as the part of Radio Frequency (RF) technology such as low cost, high scalability, high availability, and supporting topology for Indoor positioning system (IPS). In this paper, we propose IPS using Received Signal Strength Indicator (RSSI) based Zigbee protocol. The proposed approach is based on the enhancement of Trilateration algorithm. Basically, the main concept of the conventional trilateration is using three strongest RSSI from references node. However, the instability from measured RSSI influenced to its estimation result. Therefore quadratic weighted is adding to this proposed scheme as the enhanced trilateration algorithm. The estimated distance output from conventional trilateration algorithm will be used for calculating the weighted value and multiplying to each the reference node which produced lower estimation error. The simulation result show that using enhanced trilateration algorithm has capability to improve accuracy of estimated position up to 90.55 % with mean square error (MSE) 2.03 meters compared with only using conventional trilateration reached high estimated error up to 4.31 meters.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44188029","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 : 2022-11-10DOI: 10.20895/infotel.v14i4.846
Parman Sukarno, R. Utomo, Rahmat Yasirandi, N. Suwastika
This study evaluates the customer satisfaction model in adopting the Web 2.0-based e-Buruan Sae application. The e-Buruan Sae application is an interactive Web 2.0-based application used by the government and the people of Bandung City to manage urban farming activities. This research is quantitative correlational research and applies a research method based on Design Research Methodology (DRM). The stages of this research are the literature review stage with the output of research objectives, the initial empirical analysis stage with the outputs of the hypothesis and research model, the experimental stage for data collection, and the final empirical analysis stage with the output of the data analysis results. This study uses six variables to measure customer satisfaction: ease of use, service quality, interactivity, trust, customer satisfaction, and IT development. The results of empirical testing show that the ease of use and IT development variables do not affect the customer satisfaction variable. In contrast, the remaining variables have a positive effect on customer satisfaction. This research produces measurements to evaluate customer satisfaction on the Web 2.0-based urban farming application.
{"title":"Customer satisfaction of urban farming application services: “e-Buruan Sae”","authors":"Parman Sukarno, R. Utomo, Rahmat Yasirandi, N. Suwastika","doi":"10.20895/infotel.v14i4.846","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.846","url":null,"abstract":"This study evaluates the customer satisfaction model in adopting the Web 2.0-based e-Buruan Sae application. The e-Buruan Sae application is an interactive Web 2.0-based application used by the government and the people of Bandung City to manage urban farming activities. This research is quantitative correlational research and applies a research method based on Design Research Methodology (DRM). The stages of this research are the literature review stage with the output of research objectives, the initial empirical analysis stage with the outputs of the hypothesis and research model, the experimental stage for data collection, and the final empirical analysis stage with the output of the data analysis results. This study uses six variables to measure customer satisfaction: ease of use, service quality, interactivity, trust, customer satisfaction, and IT development. The results of empirical testing show that the ease of use and IT development variables do not affect the customer satisfaction variable. In contrast, the remaining variables have a positive effect on customer satisfaction. This research produces measurements to evaluate customer satisfaction on the Web 2.0-based urban farming application. ","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48102314","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 : 2022-11-04DOI: 10.20895/infotel.v14i4.833
Yuliarman Saragih, Ridwan Satrio Hadikusuma, Agatha Elisabet S
In the 4G Network on the cellular system, the possibility of high traffic increase is a big problem for users, the proposed solution is to reduce the possibility of full traffic and decrease the quality of the cellular system by dividing the frequency channel into several parts. The purpose of this paper is to study the effect of network optimization on the value of Key Performance Indicator (KPI) in the LTE 1800 and LTE 2100 bands. KPI values, In the LTE 1800 and LTE 2100 bands tested using the drive test method using the Telkomsel sim card provider, the results show that the LTE 2100 band on the TML 013 site has a very high CSSR number compared to the band LTE 1800 which is 99.73% after optimization. The results showed that the LTE band 2100 is better than the LTE band 1800 in terms of KPI Summary.
{"title":"Evaluation of cellular network performance involving the LTE 1800 band and LTE 2100 band using the drive test method","authors":"Yuliarman Saragih, Ridwan Satrio Hadikusuma, Agatha Elisabet S","doi":"10.20895/infotel.v14i4.833","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.833","url":null,"abstract":"In the 4G Network on the cellular system, the possibility of high traffic increase is a big problem for users, the proposed solution is to reduce the possibility of full traffic and decrease the quality of the cellular system by dividing the frequency channel into several parts. The purpose of this paper is to study the effect of network optimization on the value of Key Performance Indicator (KPI) in the LTE 1800 and LTE 2100 bands. KPI values, In the LTE 1800 and LTE 2100 bands tested using the drive test method using the Telkomsel sim card provider, the results show that the LTE 2100 band on the TML 013 site has a very high CSSR number compared to the band LTE 1800 which is 99.73% after optimization. The results showed that the LTE band 2100 is better than the LTE band 1800 in terms of KPI Summary.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67609589","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 : 2022-11-01DOI: 10.20895/infotel.v14i4.840
Ikke Dian Oktaviani, Aji Gautama Putrada
The prediction of rain duration based on data from the Meteorology, Climatology, and Geophysics Agency (BMKG) is an important issue but remains an open problem. At the same time, several studies have shown that missing values can cause a decrease in the performance of the model in making predictions. This study proposes k-nearest neighbors (KNN) imputation to overcome the problem of missing values in predicting rain duration. The source of the rain duration prediction dataset is the BMKG data. We compared gradient boosting regression (GBR), adaptive boosting regression (ABR), and linear regression (LR) for the regression model for predicting rain duration. We compared the KNN imputation method with several benchmark methods, including zero imputation, mean imputation, and iterative imputation. Parameters r2, mean squared error (MSE) and mean bias error (MBE) measure the performance of these imputation methods. The test results show that for rain duration prediction using the regression method, GBR shows the best performance, both for train data and test data with r2 = 0.915 and 0.776, respectively. Then our proposed KNN imputation has the best performance for missing value imputation compared to the benchmark imputation method. The prediction values of r2 and MSE when using KNN imputation at Missing Percentage = 90% are 0.71 and 0.36, respectively.
{"title":"KNN imputation to missing values of regression-based rain duration prediction on BMKG data","authors":"Ikke Dian Oktaviani, Aji Gautama Putrada","doi":"10.20895/infotel.v14i4.840","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.840","url":null,"abstract":"The prediction of rain duration based on data from the Meteorology, Climatology, and Geophysics Agency (BMKG) is an important issue but remains an open problem. At the same time, several studies have shown that missing values can cause a decrease in the performance of the model in making predictions. This study proposes k-nearest neighbors (KNN) imputation to overcome the problem of missing values in predicting rain duration. The source of the rain duration prediction dataset is the BMKG data. We compared gradient boosting regression (GBR), adaptive boosting regression (ABR), and linear regression (LR) for the regression model for predicting rain duration. We compared the KNN imputation method with several benchmark methods, including zero imputation, mean imputation, and iterative imputation. Parameters r2, mean squared error (MSE) and mean bias error (MBE) measure the performance of these imputation methods. The test results show that for rain duration prediction using the regression method, GBR shows the best performance, both for train data and test data with r2 = 0.915 and 0.776, respectively. Then our proposed KNN imputation has the best performance for missing value imputation compared to the benchmark imputation method. The prediction values of r2 and MSE when using KNN imputation at Missing Percentage = 90% are 0.71 and 0.36, respectively.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46409358","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 : 2022-11-01DOI: 10.20895/infotel.v14i4.801
F. B. Setiawan, Eric Pratama Putra, L. Pratomo, S. Riyadi
With the development of technology, especially in the field of robotics, daily human activities can be carried out with artificial intelligence. One of the artificial intelligence technologies that help ease the burden on humans, especially in terms of driving, is self-driving cars. In this case, self-driving cars have several methods with GPS systems, radar, lidar, or cameras. In this study, a self-driving car system was designed on a navigation path model using a street mark detector with an intermediary sensor, namely a camera as a vision sensor. This self-driving car system uses a prototype called an autonomous car to walk on a path which is a self-driving car navigation direction based on the detected line to be able to detect camera sensors that process line images from the camera using HSV. method. In this study, a self-driving car system has been successfully designed using a microcontroller, namely Raspberry Pi 4 as a programmer and L298n motor driver, BTS7960 as a driver for a self-driving car. The Raspberry Pi 4 sends real-time images through the camera as a vision sensor which then detects a line to navigate the movement of this self-driving car. By using image processing, the resulting level of precision can reach the average value according to the direction of the self-driving car.
随着技术的发展，特别是在机器人领域，人类的日常活动可以用人工智能进行。自动驾驶汽车是有助于减轻人类负担的人工智能技术之一，尤其是在驾驶方面。在这种情况下，自动驾驶汽车有几种带有GPS系统、雷达、激光雷达或摄像头的方法。在本研究中，在导航路径模型上设计了一个自动驾驶汽车系统，该系统使用带有中间传感器的路标检测器，即作为视觉传感器的摄像头。该自动驾驶汽车系统使用称为自动驾驶汽车的原型在作为基于检测到的线路的自动驾驶汽车导航方向的路径上行走，从而能够检测使用HSV处理来自摄像机的线路图像的摄像机传感器。方法在本研究中，使用微控制器，即Raspberry Pi 4作为程序员和L298n电机驱动器，BTS7960作为自动驾驶汽车的驱动器，成功地设计了一个自动驾驶汽车系统。Raspberry Pi 4通过摄像头作为视觉传感器发送实时图像，然后检测一条线来导航这款自动驾驶汽车的运动。通过使用图像处理，所得到的精度水平可以根据自动驾驶汽车的方向达到平均值。
{"title":"Implementation of line detection self-driving car using HSV method based on raspberry pi 4","authors":"F. B. Setiawan, Eric Pratama Putra, L. Pratomo, S. Riyadi","doi":"10.20895/infotel.v14i4.801","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.801","url":null,"abstract":"With the development of technology, especially in the field of robotics, daily human activities can be carried out with artificial intelligence. One of the artificial intelligence technologies that help ease the burden on humans, especially in terms of driving, is self-driving cars. In this case, self-driving cars have several methods with GPS systems, radar, lidar, or cameras. In this study, a self-driving car system was designed on a navigation path model using a street mark detector with an intermediary sensor, namely a camera as a vision sensor. This self-driving car system uses a prototype called an autonomous car to walk on a path which is a self-driving car navigation direction based on the detected line to be able to detect camera sensors that process line images from the camera using HSV. method. In this study, a self-driving car system has been successfully designed using a microcontroller, namely Raspberry Pi 4 as a programmer and L298n motor driver, BTS7960 as a driver for a self-driving car. The Raspberry Pi 4 sends real-time images through the camera as a vision sensor which then detects a line to navigate the movement of this self-driving car. By using image processing, the resulting level of precision can reach the average value according to the direction of the self-driving car.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43018778","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 : 2022-11-01DOI: 10.20895/infotel.v14i4.807
Favian Dewanta
The Internet of Things (IoT) technology requires low latency communications. One of the lightweight protocols in the IoT is the MQTT protocol. However, the MQTT protocol is not equipped with the appropriate security mechanism. As a consequence, the MQTT messages are easily eavesdropped and modified by the attackers. This research studies the use of AES cryptography-based communication scheme against the TLS-based communication scheme, which can be used to create end-to-end secure communication channels from the MQTT publishers to the MQTT subscribers. Experimental results show that the TLS-based communication scheme possess the highest cost in terms of communication delay and network cost among all schemes in the experiment. Eventually, the AES-based MQTT communication scheme is more appropriate for IoT environments because of its communication delay and network cost, which are considerably equal to the plaintext-based MQTT communications.
{"title":"A study of secure communication scheme in MQTT: TLS vs AES cryptography","authors":"Favian Dewanta","doi":"10.20895/infotel.v14i4.807","DOIUrl":"https://doi.org/10.20895/infotel.v14i4.807","url":null,"abstract":"The Internet of Things (IoT) technology requires low latency communications. One of the lightweight protocols in the IoT is the MQTT protocol. However, the MQTT protocol is not equipped with the appropriate security mechanism. As a consequence, the MQTT messages are easily eavesdropped and modified by the attackers. This research studies the use of AES cryptography-based communication scheme against the TLS-based communication scheme, which can be used to create end-to-end secure communication channels from the MQTT publishers to the MQTT subscribers. Experimental results show that the TLS-based communication scheme possess the highest cost in terms of communication delay and network cost among all schemes in the experiment. Eventually, the AES-based MQTT communication scheme is more appropriate for IoT environments because of its communication delay and network cost, which are considerably equal to the plaintext-based MQTT communications. ","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46758353","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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