Pub Date : 2023-08-31DOI: 10.20895/infotel.v15i3.961
Dyah Lestari, S. Sendari, I. Zaeni
In conducting their work in the industry quickly, precisely, and safely, mobile robots must be able to determine the position and direction of movement in their work environment. Several algorithms have been developed to solve maze rooms, however, when the room is huge with several obstacles which could be re-placed in other parts of the room, determining the path for a mobile robot will be difficult. This can be done by mapping the work environment and determining the position of the robot so that the robot has good path planning to get the optimal path. In this research, a Genetic Algorithm (GA) will be used to determine the fastest route that a robot may take when moving from one location to another. The method used is to design a mobile robot work environment, design genetic algorithm steps, create software for simulation, test the algorithm in 6 variations of the work environment, and analyze the test results. The genetic algorithm can determine the shortest path with 93% completeness among the 6 possible combinations of the start point, target point, and position of obstacles. The proposed GA, it can be argued, can be used to locate the shortest path in a warehouse with different start and end points.
{"title":"Genetic algorithm for finding shortest path of mobile robot in various static environments","authors":"Dyah Lestari, S. Sendari, I. Zaeni","doi":"10.20895/infotel.v15i3.961","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.961","url":null,"abstract":"In conducting their work in the industry quickly, precisely, and safely, mobile robots must be able to determine the position and direction of movement in their work environment. Several algorithms have been developed to solve maze rooms, however, when the room is huge with several obstacles which could be re-placed in other parts of the room, determining the path for a mobile robot will be difficult. This can be done by mapping the work environment and determining the position of the robot so that the robot has good path planning to get the optimal path. In this research, a Genetic Algorithm (GA) will be used to determine the fastest route that a robot may take when moving from one location to another. The method used is to design a mobile robot work environment, design genetic algorithm steps, create software for simulation, test the algorithm in 6 variations of the work environment, and analyze the test results. The genetic algorithm can determine the shortest path with 93% completeness among the 6 possible combinations of the start point, target point, and position of obstacles. The proposed GA, it can be argued, can be used to locate the shortest path in a warehouse with different start and end points.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139347240","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 : 2023-08-31DOI: 10.20895/infotel.v15i3.964
Alwas Muis, Sunardi Sunardi, Anton Yudhana
Brain tumor is a disease that is very dangerous for humans where this disease really needs faster and more accurate treatment. This disease requires early detection because it requires fast and accurate medical treatment. Machine learning helps solve problems by leveraging deep learning technology in the branch of machine learning. Deep learning is a technology that can detect, classify, and segment various problems in machine learning. One of the methods used in deep learning is the Convolutional Neural Network. This method is most often used in performing image processing where this method has various types of feature extraction. The purpose of this study was to test the accuracy of using the Convolutional Neural Network method in classifying brain images. The brain image used in this study is an image scanned by Magnetic Resonance Imaging. The dataset in this study was downloaded from the Kaggle website as many as 7023 data consisting of four classes of brain image data, namely glioma, notumor, meningioma, and pituitary classes. The results of this study obtained an accuracy value of 84% so that this research can be used by medical personnel to diagnose brain tumors easily, quickly, precisely, and accurately.
{"title":"Medical image classification of brain tumor using convolutional neural network algorithm","authors":"Alwas Muis, Sunardi Sunardi, Anton Yudhana","doi":"10.20895/infotel.v15i3.964","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.964","url":null,"abstract":"Brain tumor is a disease that is very dangerous for humans where this disease really needs faster and more accurate treatment. This disease requires early detection because it requires fast and accurate medical treatment. Machine learning helps solve problems by leveraging deep learning technology in the branch of machine learning. Deep learning is a technology that can detect, classify, and segment various problems in machine learning. One of the methods used in deep learning is the Convolutional Neural Network. This method is most often used in performing image processing where this method has various types of feature extraction. The purpose of this study was to test the accuracy of using the Convolutional Neural Network method in classifying brain images. The brain image used in this study is an image scanned by Magnetic Resonance Imaging. The dataset in this study was downloaded from the Kaggle website as many as 7023 data consisting of four classes of brain image data, namely glioma, notumor, meningioma, and pituitary classes. The results of this study obtained an accuracy value of 84% so that this research can be used by medical personnel to diagnose brain tumors easily, quickly, precisely, and accurately.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136035041","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 : 2023-08-28DOI: 10.20895/infotel.v15i3.962
Salwa Salsabila, Rina Pudjiastuti, Levy Olivia Nur, H. H. Ryanu, Bambang Setia Nugroho
Massive MIMO Antenna Design results in a very large antenna size that hinders the design process. The arrangement of Massive MIMO Antennas which consists of many antenna elements is a challenge in the design process due to the limited capability of the simulation software and the complicated process. Thus, a scalability technique is used to predict the specification results produced by a Massive MIMO Antenna array with a certain configuration based on a simple MIMO Antenna array with a 2x2, 4x4, 8x8, 16x16 MIMO element configuration scheme, etc. exponential increments. This research will discuss the scaling process to predict the specifications of a Massive MIMO Antenna array. The designed MIMO antenna arrangement is based on the design of a rectangular antenna with a truncated corner and a circular antenna with an X slot for further design with various types of configurations that work at a frequency of 3.5 GHz.
大规模多输入多输出天线设计导致天线尺寸非常大，从而阻碍了设计过程。由于仿真软件的能力有限且过程复杂，由许多天线元件组成的 Massive MIMO 天线的排列是设计过程中的一项挑战。因此，在简单 MIMO 天线阵列的基础上，采用 2x2、4x4、8x8、16x16 MIMO 元件配置方案等指数级增量，使用可扩展性技术来预测具有特定配置的 Massive MIMO 天线阵列产生的规格结果。本研究将讨论预测大规模 MIMO 天线阵列规格的缩放过程。所设计的多输入多输出天线阵列以带截角的矩形天线和带 X 形槽的圆形天线为基础，进一步设计了各种类型的配置，工作频率为 3.5 GHz。
{"title":"Scalable modular massive MIMO antenna of rectangular truncated corner patch antenna and circular slotted X patch antenna for 5G antenna communication","authors":"Salwa Salsabila, Rina Pudjiastuti, Levy Olivia Nur, H. H. Ryanu, Bambang Setia Nugroho","doi":"10.20895/infotel.v15i3.962","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.962","url":null,"abstract":"Massive MIMO Antenna Design results in a very large antenna size that hinders the design process. The arrangement of Massive MIMO Antennas which consists of many antenna elements is a challenge in the design process due to the limited capability of the simulation software and the complicated process. Thus, a scalability technique is used to predict the specification results produced by a Massive MIMO Antenna array with a certain configuration based on a simple MIMO Antenna array with a 2x2, 4x4, 8x8, 16x16 MIMO element configuration scheme, etc. exponential increments. This research will discuss the scaling process to predict the specifications of a Massive MIMO Antenna array. The designed MIMO antenna arrangement is based on the design of a rectangular antenna with a truncated corner and a circular antenna with an X slot for further design with various types of configurations that work at a frequency of 3.5 GHz.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139348591","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 : 2023-08-25DOI: 10.20895/infotel.v15i3.943
Kholidiyah Masykuroh
Developments in telecommunications technology today, such as cellular with the fifth generation (5G), the development of IoT prototypes, and the migration of analog TV to digital TV starting in 2022. The development of various research using machine learning. The problem with video format information is that the video file size is quite large, so the transmission process requires a large bandwidth. In addition, sharing services such as Video on Demand (VoD) and Video Broadcasting are sensitive to delay. In comparison, the transmission media has limited capacity, such as terrestrial TV, Ethernet/Fast Ethernet, and wireless cellular data such as 2G, 3G HSPA, 4G, etc. Based on reports from Cisco, the development of internet users has increased by 10% per year, with 80% of total traffic using video. Developments in various video compression standards, such as the most recent H.264 and H.265, produce high-quality, low-bitrate video. Much research has been carried out with various proposed compression methods based on machine learning. Either uses singular block learning based or end-to-end. This research focuses on the literature study of video compression with machine learning.
{"title":"Literature Study of Learning-Based Video Compression","authors":"Kholidiyah Masykuroh","doi":"10.20895/infotel.v15i3.943","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.943","url":null,"abstract":"Developments in telecommunications technology today, such as cellular with the fifth generation (5G), the development of IoT prototypes, and the migration of analog TV to digital TV starting in 2022. The development of various research using machine learning. The problem with video format information is that the video file size is quite large, so the transmission process requires a large bandwidth. In addition, sharing services such as Video on Demand (VoD) and Video Broadcasting are sensitive to delay. In comparison, the transmission media has limited capacity, such as terrestrial TV, Ethernet/Fast Ethernet, and wireless cellular data such as 2G, 3G HSPA, 4G, etc. Based on reports from Cisco, the development of internet users has increased by 10% per year, with 80% of total traffic using video. Developments in various video compression standards, such as the most recent H.264 and H.265, produce high-quality, low-bitrate video. Much research has been carried out with various proposed compression methods based on machine learning. Either uses singular block learning based or end-to-end. This research focuses on the literature study of video compression with machine learning.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49022533","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 : 2023-08-25DOI: 10.20895/infotel.v15i3.950
Mutia Rahmi Dewi, Indra Kharisma Raharjana, Daniel Siahaan, Nurul Jannah
Currently, there are not many studies that assess software requirements extraction from non-software artifacts. Most of the research in these related areas are focuses on software artifacts such as project descriptions or user reviews as a source of requirements extraction. This research aims to identify relevant information to the software requirements from online news using the vector space model. This software requirements-related information can assist systems analysts in discovering the problem domain based on the lesson learned presented by stakeholders in online news. This research proposes DomText-WMDS to extract requirements-related information from online news. We used online news and public software requirements specification dataset to develop software-specific vocabulary using domain specificity technique. Then we expanded the specific vocabulary software to obtain more comprehensive results by building vector space model from online news documents. This updated version of software-specific vocabulary can be used for basic filtering of software requirements-related information that previously extracted using the part-of-speech (POS) chunking. This study improved the performance for extracting software requirements-related information, with precision and recall 61.09% and 60.66% compared to domain specificity approach that only manages to obtain 43.34% and 40.78%.
{"title":"Extracting Software Requirements-Related Information from Online News using DomText-WMDS","authors":"Mutia Rahmi Dewi, Indra Kharisma Raharjana, Daniel Siahaan, Nurul Jannah","doi":"10.20895/infotel.v15i3.950","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.950","url":null,"abstract":"Currently, there are not many studies that assess software requirements extraction from non-software artifacts. Most of the research in these related areas are focuses on software artifacts such as project descriptions or user reviews as a source of requirements extraction. This research aims to identify relevant information to the software requirements from online news using the vector space model. This software requirements-related information can assist systems analysts in discovering the problem domain based on the lesson learned presented by stakeholders in online news. This research proposes DomText-WMDS to extract requirements-related information from online news. We used online news and public software requirements specification dataset to develop software-specific vocabulary using domain specificity technique. Then we expanded the specific vocabulary software to obtain more comprehensive results by building vector space model from online news documents. This updated version of software-specific vocabulary can be used for basic filtering of software requirements-related information that previously extracted using the part-of-speech (POS) chunking. This study improved the performance for extracting software requirements-related information, with precision and recall 61.09% and 60.66% compared to domain specificity approach that only manages to obtain 43.34% and 40.78%.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134931773","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 : 2023-08-11DOI: 10.20895/infotel.v15i3.959
A. Hikmaturokhman
This study evaluates the types of regulation models for The Indonesia Spectrum Usage Fee—the so-called Biaya Hak Pengguna (BHP) Frequency in 5G private network technology that are most suitable for implementation in Indonesia by implementing the Fuzzy Analytical Hierarchy Process (F-AHP) method. This method accommodates the opinions of telecommunications experts from mobile network operators (MNOs), regulators, vertical industries, and telecommunications consultants through a series of scientific steps to produce weights for each type of alternative solution offered. The results obtained show that the proposed model most suitable for implementation in Indonesia, taking into account the given criteria, is the one that uses unlicensed 5G frequencies. This model involves vertical industries not using licensed frequencies established by the government but rather choosing to use unlicensed frequencies to develop 5G technology for their own use. The implementation of this model is expected to encourage the optimization of regulation for Spectrum Usage Fee in 5G private network technology owned by the government, providing opportunities for vertical industries to develop 5G technology on private networks independently without relying on existing MNOs. This can stimulate innovation and technological progress in Indonesia to support Industry 4.0.
本研究通过实施模糊层次分析法（F-AHP）评估了最适合在印度尼西亚实施的5G专用网络技术中的印度尼西亚频谱使用费（即所谓的Biaya Hak Pengguna（BHP）频率）的监管模型类型。该方法通过一系列科学步骤，为所提供的每种类型的替代解决方案生成权重，从而听取了来自移动网络运营商（MNO）、监管机构、垂直行业和电信顾问的电信专家的意见。所获得的结果表明，考虑到给定的标准，最适合在印度尼西亚实施的拟议模型是使用未经许可的5G频率的模型。这种模式涉及垂直行业，它们不使用政府建立的许可频率，而是选择使用未经许可的频率来开发自己使用的5G技术。该模式的实施有望鼓励优化政府拥有的5G专用网络技术中的频谱使用费监管，为垂直行业在不依赖现有MNO的情况下在专用网络上独立开发5G技术提供机会。这可以刺激印尼的创新和技术进步，以支持工业4.0。
{"title":"A Proposal for Regulation of The Spectrum Usage Fee in 5G Private Network","authors":"A. Hikmaturokhman","doi":"10.20895/infotel.v15i3.959","DOIUrl":"https://doi.org/10.20895/infotel.v15i3.959","url":null,"abstract":"This study evaluates the types of regulation models for The Indonesia Spectrum Usage Fee—the so-called Biaya Hak Pengguna (BHP) Frequency in 5G private network technology that are most suitable for implementation in Indonesia by implementing the Fuzzy Analytical Hierarchy Process (F-AHP) method. This method accommodates the opinions of telecommunications experts from mobile network operators (MNOs), regulators, vertical industries, and telecommunications consultants through a series of scientific steps to produce weights for each type of alternative solution offered. The results obtained show that the proposed model most suitable for implementation in Indonesia, taking into account the given criteria, is the one that uses unlicensed 5G frequencies. This model involves vertical industries not using licensed frequencies established by the government but rather choosing to use unlicensed frequencies to develop 5G technology for their own use. The implementation of this model is expected to encourage the optimization of regulation for Spectrum Usage Fee in 5G private network technology owned by the government, providing opportunities for vertical industries to develop 5G technology on private networks independently without relying on existing MNOs. This can stimulate innovation and technological progress in Indonesia to support Industry 4.0.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47180549","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 : 2023-06-07DOI: 10.20895/infotel.v15i2.934
K. Khairul, Asyahri Hadi Nasyuha, A. Ikhwan, Moustafa H. Aly, Ahyanuardi Ahyanuardi
Traditional marketing strategies are no longer practical to implement because the process requires more costs and time to disseminate information which is much longer. Data Mining is a science that discusses knowledge from previous data to estimate the amount of production in the future. Data mining is a term used to find hidden knowledge in databases. “Data mining is a semi-automatic process using statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify valuable and helpful information in large databases. It is necessary to solve the problem by using one of the five methods in the field of Data Mining, namely the Multiple Linear Regression method, where this method will analyze the variables that have an influence and can make estimates. Multiple Linear Regression Is a method that can be used to analyze data and obtain meaningful conclusions about a relationship between one variable and another. This relationship is generally expressed by a mathematical equation expressing the relationship between the independent and dependent variables in the form of a simple equation
{"title":"Implementation of Multiple Linear Regression to Estimate Profit on Sales of Screen Printing Equipment","authors":"K. Khairul, Asyahri Hadi Nasyuha, A. Ikhwan, Moustafa H. Aly, Ahyanuardi Ahyanuardi","doi":"10.20895/infotel.v15i2.934","DOIUrl":"https://doi.org/10.20895/infotel.v15i2.934","url":null,"abstract":"Traditional marketing strategies are no longer practical to implement because the process requires more costs and time to disseminate information which is much longer. Data Mining is a science that discusses knowledge from previous data to estimate the amount of production in the future. Data mining is a term used to find hidden knowledge in databases. “Data mining is a semi-automatic process using statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify valuable and helpful information in large databases. It is necessary to solve the problem by using one of the five methods in the field of Data Mining, namely the Multiple Linear Regression method, where this method will analyze the variables that have an influence and can make estimates. Multiple Linear Regression Is a method that can be used to analyze data and obtain meaningful conclusions about a relationship between one variable and another. This relationship is generally expressed by a mathematical equation expressing the relationship between the independent and dependent variables in the form of a simple equation","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47640127","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 great livestock potential. The semi-intensive grazing system is one of the efforts to increase the production of healthy and superior dairy or beef livestock. This grazing system has many advantages. However, it has several weaknesses that can prejudice farmers, including lost or stolen livestock due to a lack of control and monitoring. Therefore, tracking livestock’s position in the WSN-based grasslands monitoring will be implemented to overcome these weaknesses. Thus, it will provide benefits as a support for a modern and controlled livestock system. The built WSN consists of several nodes installed on livestock consisting of Arduino nano, GPS Neo Module, LoRa S-1278, DS3231 clock module, and MCU node. Tracking is visible through the application by displaying the map and livestock’s GPS position. In addition, the system is notified if the livestock’s position is located more than in the permitted radius of the farm. The system was examined and analyzed using the Haversine method with various scenarios to find the maximum range transmission and perform system toughness. The results stated that the system could track the livestock’s position up to 11 Km and the location error calculation obtained by Haversine is only 11.7% of the actual location.
印度尼西亚拥有巨大的畜牧业潜力。半集约放牧系统是提高健康优质奶牛或肉牛产量的努力之一。这种放牧制度有许多优点。然而，它有几个弱点，可能对农民造成损害，包括由于缺乏控制和监测而导致牲畜丢失或被盗。因此，在基于wsn的草原监测中实施家畜位置跟踪将克服这些弱点。因此，它将为现代和受控的牲畜系统提供支持。搭建的WSN由安装在牲畜上的多个节点组成，包括Arduino nano、GPS Neo Module、LoRa S-1278、DS3231时钟模块和MCU节点。通过显示地图和牲畜的GPS位置，跟踪在应用程序中是可见的。此外，如果牲畜的位置超出了农场允许的半径范围，系统就会收到通知。采用Haversine方法对系统进行了各种场景的测试和分析，以确定最大距离传输并执行系统韧性。结果表明，该系统可以跟踪牲畜的位置长达11 Km, Haversine计算的位置误差仅为实际位置的11.7%。
{"title":"A virtual cage for monitoring system semi-intensive livestock’s using wireless sensor network and Haversine method","authors":"Fahmi Danah Pratama, Giva Andriana Mutiara, Lisda Meisaroh","doi":"10.20895/infotel.v15i2.944","DOIUrl":"https://doi.org/10.20895/infotel.v15i2.944","url":null,"abstract":"Indonesia has great livestock potential. The semi-intensive grazing system is one of the efforts to increase the production of healthy and superior dairy or beef livestock. This grazing system has many advantages. However, it has several weaknesses that can prejudice farmers, including lost or stolen livestock due to a lack of control and monitoring. Therefore, tracking livestock’s position in the WSN-based grasslands monitoring will be implemented to overcome these weaknesses. Thus, it will provide benefits as a support for a modern and controlled livestock system. The built WSN consists of several nodes installed on livestock consisting of Arduino nano, GPS Neo Module, LoRa S-1278, DS3231 clock module, and MCU node. Tracking is visible through the application by displaying the map and livestock’s GPS position. In addition, the system is notified if the livestock’s position is located more than in the permitted radius of the farm. The system was examined and analyzed using the Haversine method with various scenarios to find the maximum range transmission and perform system toughness. The results stated that the system could track the livestock’s position up to 11 Km and the location error calculation obtained by Haversine is only 11.7% of the actual location.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45439773","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 : 2023-05-30DOI: 10.20895/infotel.v15i2.940
I. Ketut, Agung Enriko, Angela Niarapika Nababan, A. F. Rochim, Sri Kuntadi, Institut Teknologi, Telkom Purwokerto
A fire suppression system (FSS) monitoring system is a system to monitor the FSS devices’ status since FSS is a critical system to respond to fire disasters. The monitoring system collects data on important parameters which are water pressure, main power status, and backup power status. The FSS monitoring system is built with an IoT capability where data are collected from the FSS module and sent to the IoT platform through Wi-Fi based Internet connection. Then the data will be displayed in a dashboard application. A QoS assessment framework is referred to and performed to check the performance of the FSS monitoring system, namely the TIPHON framework, which consists of five parameters: bandwidth, throughput, packet loss, delay, and jitter. The overall score for the FSS system using the TIPHON standard is 3.2 or categorized as “good”.
{"title":"A Fire suppression monitoring system for smart building","authors":"I. Ketut, Agung Enriko, Angela Niarapika Nababan, A. F. Rochim, Sri Kuntadi, Institut Teknologi, Telkom Purwokerto","doi":"10.20895/infotel.v15i2.940","DOIUrl":"https://doi.org/10.20895/infotel.v15i2.940","url":null,"abstract":"A fire suppression system (FSS) monitoring system is a system to monitor the FSS devices’ status since FSS is a critical system to respond to fire disasters. The monitoring system collects data on important parameters which are water pressure, main power status, and backup power status. The FSS monitoring system is built with an IoT capability where data are collected from the FSS module and sent to the IoT platform through Wi-Fi based Internet connection. Then the data will be displayed in a dashboard application. A QoS assessment framework is referred to and performed to check the performance of the FSS monitoring system, namely the TIPHON framework, which consists of five parameters: bandwidth, throughput, packet loss, delay, and jitter. The overall score for the FSS system using the TIPHON standard is 3.2 or categorized as “good”.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46662598","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 : 2023-05-24DOI: 10.20895/infotel.v15i2.916
M. Harahap, Valentino Damar, Sallyana Yek, Michael Michael, M. R. Putra
Human Activity Recognition has been widely studied using the Convolutional Neural Network (CNN) algorithm to classify a person's movements by utilizing data from devices that record movements such as cameras. The benefits generated by this technology are useful for modern devices such as Virtual Reality and Smart Home technology with CCTV cameras. The VGG-16 (Visual Geometric Group with 16 Layers) pre-trained model is one of the models used for transfer learning and has won the Image Net competition. In this study, the authors tested the performance of the VGG-16 model to identify two types of human activity, namely Static and Dynamic. This study uses 1,680 public datasets which are divided into 80% Data Train, 10% Data Validation, and 10% Data Test I. In addition, there are also 100 local datasets as Data Test II. There is no overfitting issue in the training and testing process. The accuracy of the Testing process with public and local images dataset produces a high accuracy of 98.8% and 97% respectively.
人类活动识别已经被广泛研究，使用卷积神经网络(CNN)算法，利用记录运动的设备(如摄像头)的数据对人的运动进行分类。这项技术所产生的好处是有用的现代设备，如虚拟现实和智能家居技术与闭路电视摄像机。VGG-16 (Visual Geometric Group with 16 Layers)预训练模型是用于迁移学习的模型之一，曾在Image Net竞赛中获奖。在这项研究中，作者测试了VGG-16模型的性能，以识别两种类型的人类活动，即静态和动态。本研究使用1680个公共数据集，分为80%的数据训练、10%的数据验证和10%的数据测试i。此外，还有100个本地数据集作为数据测试II。在培训和测试过程中不存在过拟合问题。使用公共和本地图像数据集的测试过程的准确率分别达到98.8%和97%。
{"title":"Static and dynamic human activity recognition with VGG-16 pre-trained CNN model","authors":"M. Harahap, Valentino Damar, Sallyana Yek, Michael Michael, M. R. Putra","doi":"10.20895/infotel.v15i2.916","DOIUrl":"https://doi.org/10.20895/infotel.v15i2.916","url":null,"abstract":"Human Activity Recognition has been widely studied using the Convolutional Neural Network (CNN) algorithm to classify a person's movements by utilizing data from devices that record movements such as cameras. The benefits generated by this technology are useful for modern devices such as Virtual Reality and Smart Home technology with CCTV cameras. The VGG-16 (Visual Geometric Group with 16 Layers) pre-trained model is one of the models used for transfer learning and has won the Image Net competition. In this study, the authors tested the performance of the VGG-16 model to identify two types of human activity, namely Static and Dynamic. This study uses 1,680 public datasets which are divided into 80% Data Train, 10% Data Validation, and 10% Data Test I. In addition, there are also 100 local datasets as Data Test II. There is no overfitting issue in the training and testing process. The accuracy of the Testing process with public and local images dataset produces a high accuracy of 98.8% and 97% respectively.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44136671","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：