Pub Date : 2022-09-28DOI: 10.1142/s0219265922990018
{"title":"Author Index Volume 22 (2022)","authors":"","doi":"10.1142/s0219265922990018","DOIUrl":"https://doi.org/10.1142/s0219265922990018","url":null,"abstract":"","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79141598","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 : 2022-08-30DOI: 10.1142/s0219265922420014
Chen Ying, Liao Xianjing, Wang Wei, Wang Jiahao, Zhang Wencheng, Shi Yanjiao, Zhang Qi
Aiming at the problems of insufficient feature extraction ability, many mismatching points and low registration accuracy of some remote sensing image registration algorithms, this study proposes a remote sensing image registration algorithm via cyclic parameter synthesis spatial transformation network. (1) We propose a feature extraction network framework combined with the improved spatial transformation network and improved Densely Connected Networks (DenseNet), which can focus on important areas of images for feature extraction.This framework can effectively improve the feature extraction ability of the model, so as to improve the model accuracy. (2) In the matching stage, we design the coarse filter and fine filter double filter architecture. Thus, the false matching points are effectively filtered out, which not only improves the robustness of the model but also improves the registration accuracy. Compared with the two traditional methods and two deep learning methods, the experimental results of this model are better in many indexes.
{"title":"Remote Sensing Image Registration Via Cyclic Parameter Synthesis and Spatial Transformation Network","authors":"Chen Ying, Liao Xianjing, Wang Wei, Wang Jiahao, Zhang Wencheng, Shi Yanjiao, Zhang Qi","doi":"10.1142/s0219265922420014","DOIUrl":"https://doi.org/10.1142/s0219265922420014","url":null,"abstract":"Aiming at the problems of insufficient feature extraction ability, many mismatching points and low registration accuracy of some remote sensing image registration algorithms, this study proposes a remote sensing image registration algorithm via cyclic parameter synthesis spatial transformation network. (1) We propose a feature extraction network framework combined with the improved spatial transformation network and improved Densely Connected Networks (DenseNet), which can focus on important areas of images for feature extraction.This framework can effectively improve the feature extraction ability of the model, so as to improve the model accuracy. (2) In the matching stage, we design the coarse filter and fine filter double filter architecture. Thus, the false matching points are effectively filtered out, which not only improves the robustness of the model but also improves the registration accuracy. Compared with the two traditional methods and two deep learning methods, the experimental results of this model are better in many indexes.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78934535","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 : 2022-05-31DOI: 10.1142/s0219265921490013
R. Amutha, G. Sivasankari, K. Venugopal, Thompson Stephan
Owing to uncertainties associated with energy and maintenance of large Wireless Sensor Networks (WSN) during transmission, energy-efficient routing strategies are gaining popularity. A Dynamic Threshold Adaptive Routing Algorithm (DTAR) is proposed for determining the most appropriate node to become a Cluster Head (CH) using adaptive participation criteria. For determining the next Forwarder Node (FN), an adaptive ranking scheme depends on distance ([Formula: see text]) and Residual Energy ([Formula: see text]). However, additional parameters such as Delivery Ratio (DR), End-to-End delay ([Formula: see text] delay), and Message Success Rate (MSR) should be considered to achieve the most optimal approach to achieve energy efficiency. The proposed DTAR algorithm is validated on variable clustered networks in order to investigate the effect of opportunistic routing with increasing network size and energy resources. The proposed algorithm shows a substantial decrease in energy consumption during transmission. Energy Consumption (EC), Packet Delivery Ratio (PDR), End-to-End delay ([Formula: see text] delay), and Message Success Rate (MSR) are used to illustrate the effectiveness of the proposed algorithm for energy efficiency.
{"title":"DTAR: A Dynamic Threshold Adaptive Ranking-Based Energy-Efficient Routing Algorithm for WSNs","authors":"R. Amutha, G. Sivasankari, K. Venugopal, Thompson Stephan","doi":"10.1142/s0219265921490013","DOIUrl":"https://doi.org/10.1142/s0219265921490013","url":null,"abstract":"Owing to uncertainties associated with energy and maintenance of large Wireless Sensor Networks (WSN) during transmission, energy-efficient routing strategies are gaining popularity. A Dynamic Threshold Adaptive Routing Algorithm (DTAR) is proposed for determining the most appropriate node to become a Cluster Head (CH) using adaptive participation criteria. For determining the next Forwarder Node (FN), an adaptive ranking scheme depends on distance ([Formula: see text]) and Residual Energy ([Formula: see text]). However, additional parameters such as Delivery Ratio (DR), End-to-End delay ([Formula: see text] delay), and Message Success Rate (MSR) should be considered to achieve the most optimal approach to achieve energy efficiency. The proposed DTAR algorithm is validated on variable clustered networks in order to investigate the effect of opportunistic routing with increasing network size and energy resources. The proposed algorithm shows a substantial decrease in energy consumption during transmission. Energy Consumption (EC), Packet Delivery Ratio (PDR), End-to-End delay ([Formula: see text] delay), and Message Success Rate (MSR) are used to illustrate the effectiveness of the proposed algorithm for energy efficiency.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85894656","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 : 2022-05-12DOI: 10.1142/s0219265922410018
A. R. Suhas, M. Manoj Priyatham
A physical region can have multiple parts, each part is monitored with the help of a Special DDN (SDDN). In the existing methods, namely, LEACH, the Fuzzy method has a larger path between the initiator DDN to destination DDN. Non-healthy DDNs can occur in the Group-based Detection Data Network (GDDN) when the battery level of the DDN reaches below the threshold. The possibility of more Non-healthy DDNs can be of multiple reasons (i) when the link path is of larger length (ii) Same DDN is used multiple times as an SDDN and (iii) repeated communication between base station to DDNs causes the DDN to lose more battery. If a mechanism is created to recover the DDNs or recharge them, then the number of Non-healthy DDNs can be reduced and DDN performance can be improved a lot. The Proposed Genetic (PGENETIC) method will find the SDDN in a battery-aware manner and also at path will be of minimum length along with regular interval trigger to identify DDNs which are non-healthy and replace or recharge them. PGENETIC is compared with LEACH, Fuzzy method, and Proposed CHEF (PCHEF) and proved that PGENETIC exhibits better performance.
一个物理区域可以包含多个部分，每个部分通过SDDN (Special DDN)进行监控。在现有的方法中，即LEACH，模糊方法在发起者DDN到目的DDN之间的路径更大。当GDDN (Group-based Detection Data Network)的电池电量低于阈值时，可能会出现非健康DDNs。出现更多非健康DDN的可能性有多种原因:(i)链路路径长度较大;(ii)同一DDN作为SDDN多次使用;(iii)基站与DDN之间的重复通信导致DDN消耗更多电池。如果建立恢复DDN或为其充值的机制，则可以减少非健康DDN的数量，并大大提高DDN的性能。提出的遗传(PGENETIC)方法将以电池感知的方式找到SDDN，并且在路径长度最小的情况下，以及定期间隔触发来识别非健康ddn并替换或充电。将PGENETIC算法与LEACH、Fuzzy、Proposed CHEF (PCHEF)算法进行了比较，证明了PGENETIC算法具有更好的性能。
{"title":"Health Ratio Optimization of Group Detection-Based Data Network Using Genetic Algorithm","authors":"A. R. Suhas, M. Manoj Priyatham","doi":"10.1142/s0219265922410018","DOIUrl":"https://doi.org/10.1142/s0219265922410018","url":null,"abstract":"A physical region can have multiple parts, each part is monitored with the help of a Special DDN (SDDN). In the existing methods, namely, LEACH, the Fuzzy method has a larger path between the initiator DDN to destination DDN. Non-healthy DDNs can occur in the Group-based Detection Data Network (GDDN) when the battery level of the DDN reaches below the threshold. The possibility of more Non-healthy DDNs can be of multiple reasons (i) when the link path is of larger length (ii) Same DDN is used multiple times as an SDDN and (iii) repeated communication between base station to DDNs causes the DDN to lose more battery. If a mechanism is created to recover the DDNs or recharge them, then the number of Non-healthy DDNs can be reduced and DDN performance can be improved a lot. The Proposed Genetic (PGENETIC) method will find the SDDN in a battery-aware manner and also at path will be of minimum length along with regular interval trigger to identify DDNs which are non-healthy and replace or recharge them. PGENETIC is compared with LEACH, Fuzzy method, and Proposed CHEF (PCHEF) and proved that PGENETIC exhibits better performance.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79283778","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 : 2022-01-31DOI: 10.1142/s0219265921430477
A. Madhuri, V. E. Jyothi, S. Praveen, S. Sindhura, V. S. Srinivas, D. L. S. Kumar
One of the important technologies in present days is Intrusion detection technology. By using the machine learning techniques, researchers were developed different intrusion systems. But, the designed models toughness is affected by the two parameters, in that first one is, high network traffic imbalance in several categories, and another is, non-identical distribution is present in between the test set and training set in feature space. An artificial neural network (ANN) multi-level intrusion detection model with semi-supervised hierarchical [Formula: see text]-means method (HSK-means) is presented in this paper. Error rate of intrusion detection is reduced by the ANN’s accurate learning so it uses the Grasshopper Optimization Algorithm (GOA) which is analysed in this paper. Based on selection of important and useful parameters as bias and weight, error rate of intrusion detection system is reduced in the GOA algorithm and this is the main objective of the proposed system. Cluster based method is used in the pattern discovery module in order to find the unknown patterns. Here the test sample is treated as unlabelled unknown pattern or the known pattern. Proposed approach performance is evaluated by using the dataset as KDDCUP99. It is evident from the experimental findings that the projected model of GOA based semi supervised learning approach is better in terms of sensitivity, specificity and overall accuracy than the intrusion systems which are existed previously.
{"title":"A New Multi-Level Semi-Supervised Learning Approach for Network Intrusion Detection System Based on the ‘GOA’","authors":"A. Madhuri, V. E. Jyothi, S. Praveen, S. Sindhura, V. S. Srinivas, D. L. S. Kumar","doi":"10.1142/s0219265921430477","DOIUrl":"https://doi.org/10.1142/s0219265921430477","url":null,"abstract":"One of the important technologies in present days is Intrusion detection technology. By using the machine learning techniques, researchers were developed different intrusion systems. But, the designed models toughness is affected by the two parameters, in that first one is, high network traffic imbalance in several categories, and another is, non-identical distribution is present in between the test set and training set in feature space. An artificial neural network (ANN) multi-level intrusion detection model with semi-supervised hierarchical [Formula: see text]-means method (HSK-means) is presented in this paper. Error rate of intrusion detection is reduced by the ANN’s accurate learning so it uses the Grasshopper Optimization Algorithm (GOA) which is analysed in this paper. Based on selection of important and useful parameters as bias and weight, error rate of intrusion detection system is reduced in the GOA algorithm and this is the main objective of the proposed system. Cluster based method is used in the pattern discovery module in order to find the unknown patterns. Here the test sample is treated as unlabelled unknown pattern or the known pattern. Proposed approach performance is evaluated by using the dataset as KDDCUP99. It is evident from the experimental findings that the projected model of GOA based semi supervised learning approach is better in terms of sensitivity, specificity and overall accuracy than the intrusion systems which are existed previously.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76894161","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 : 2021-12-01DOI: 10.1142/s0219265921990012
{"title":"Author Index Volume 21 (2021)","authors":"","doi":"10.1142/s0219265921990012","DOIUrl":"https://doi.org/10.1142/s0219265921990012","url":null,"abstract":"","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87644479","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}
M. Jayakrishnan, Abdul Karim Mohamad, Mokhtar Mohd Yusof
The comprehensive stimulation for this research arises from the necessity to continually understand and investigate the Information System (IS) discipline body of knowledge from organizational practice. Specifically, in this study, we focus on comparing a few available excellence frameworks, data analytics, and cybernetics approaches. Such knowledge and skill practice in the IS field is predominant for both IS research and teaching. On the other hand, to propose a relevant performance reporting model using data analytics and cybernetics that entail a body of knowledge and skill is crucial for the development and transformation of organizational excellence. Yet, it helps to design an online real-time organizational dashboard that produces knowledge for its application and decision-making within an organizational practice. IS discipline in an organization is comparatively young and its specification in academia as well as in practice is rapidly changing, we focus on the practical design, and IS structure for organizational excellence through employing information technologies.
{"title":"Organization Cybernetics for Railway Supplier Selection","authors":"M. Jayakrishnan, Abdul Karim Mohamad, Mokhtar Mohd Yusof","doi":"10.15575/JOIN.V6I1.689","DOIUrl":"https://doi.org/10.15575/JOIN.V6I1.689","url":null,"abstract":"The comprehensive stimulation for this research arises from the necessity to continually understand and investigate the Information System (IS) discipline body of knowledge from organizational practice. Specifically, in this study, we focus on comparing a few available excellence frameworks, data analytics, and cybernetics approaches. Such knowledge and skill practice in the IS field is predominant for both IS research and teaching. On the other hand, to propose a relevant performance reporting model using data analytics and cybernetics that entail a body of knowledge and skill is crucial for the development and transformation of organizational excellence. Yet, it helps to design an online real-time organizational dashboard that produces knowledge for its application and decision-making within an organizational practice. IS discipline in an organization is comparatively young and its specification in academia as well as in practice is rapidly changing, we focus on the practical design, and IS structure for organizational excellence through employing information technologies.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81115468","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}
Since the Indonesian Ulema Council (MUI) was established in 1975 until now, this institution has produced 201 edicts covering various fields. Text mining is one of the techniques used to collect data hidden from data that form text. One method of extracting text is Clustering. The present study implements the Fuzzy C-Means Clustering method in MUI fatwa documents to classify existing fatwas based on the similarity of the issues discussed. Silhouette Coefficient is used to analyze the resulting clusters, with the best value of 0.0982 with 10 clusters grouping. Classify fatwas based on the similarity of the issues discussed can make it easier and faster in the search for an Islamic law in Indonesia.
{"title":"Implementation of Fuzzy C-Means for Clustering the Majelis Ulama Indonesia (MUI) Fatwa Documents","authors":"Fajar Rohman Hariri","doi":"10.15575/JOIN.V6I1.591","DOIUrl":"https://doi.org/10.15575/JOIN.V6I1.591","url":null,"abstract":"Since the Indonesian Ulema Council (MUI) was established in 1975 until now, this institution has produced 201 edicts covering various fields. Text mining is one of the techniques used to collect data hidden from data that form text. One method of extracting text is Clustering. The present study implements the Fuzzy C-Means Clustering method in MUI fatwa documents to classify existing fatwas based on the similarity of the issues discussed. Silhouette Coefficient is used to analyze the resulting clusters, with the best value of 0.0982 with 10 clusters grouping. Classify fatwas based on the similarity of the issues discussed can make it easier and faster in the search for an Islamic law in Indonesia.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88680075","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}
The assignment problem is one of the fundamental problems in the field of combinatorial optimization. The Hungarian algorithm can be developed to solve various assignment problems according to each criterion. The assignment problem that is solved in this paper is a dynamic assignment to find the maximum weight on the resource allocation problems. The dynamic characteristic lies in the weight change that can occur after the optimal solution is obtained. The Hungarian algorithm can be used directly, but the initialization process must be done from the beginning every time a change occurs. The solution becomes ineffective because it takes up a lot of time and memory. This paper proposed a fast dynamic assignment algorithm based on the Hungarian algorithm. The proposed algorithm is able to obtain an optimal solution without performing the initialization process from the beginning. Based on the test results, the proposed algorithm has an average time of 0.146 s and an average memory of 4.62 M. While the Hungarian algorithm has an average time of 2.806 s and an average memory of 4.65 M. The fast dynamic assignment algorithm is influenced linearly by the number of change operations and quadratically by the number of vertices.
{"title":"A Fast Dynamic Assignment Algorithm for Solving Resource Allocation Problems","authors":"Ivanda Zevi Amalia, Ahmad Saikhu, Rully Soelaiman","doi":"10.15575/JOIN.V6I1.692","DOIUrl":"https://doi.org/10.15575/JOIN.V6I1.692","url":null,"abstract":"The assignment problem is one of the fundamental problems in the field of combinatorial optimization. The Hungarian algorithm can be developed to solve various assignment problems according to each criterion. The assignment problem that is solved in this paper is a dynamic assignment to find the maximum weight on the resource allocation problems. The dynamic characteristic lies in the weight change that can occur after the optimal solution is obtained. The Hungarian algorithm can be used directly, but the initialization process must be done from the beginning every time a change occurs. The solution becomes ineffective because it takes up a lot of time and memory. This paper proposed a fast dynamic assignment algorithm based on the Hungarian algorithm. The proposed algorithm is able to obtain an optimal solution without performing the initialization process from the beginning. Based on the test results, the proposed algorithm has an average time of 0.146 s and an average memory of 4.62 M. While the Hungarian algorithm has an average time of 2.806 s and an average memory of 4.65 M. The fast dynamic assignment algorithm is influenced linearly by the number of change operations and quadratically by the number of vertices.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88926169","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}
Based on the observations conducted to the students of Diploma of Telecommunications Engineering Telkom University. It revealed that the students have difficulty learning and understanding the chapters of call processing and network optimization in the course of cellular communication systems. It has resulted from the current learning media, which are only in the form of textbooks and Powerpoint slides considered less attractive. Hence, the learning process becomes ineffective and has an impact on low learning outcomes. In this study, an interactive learning media was designed with the Multimedia Development Life Cycle (MDLC) method, Adobe Flash professional CS6 software, using the action script 2.0 programming language. Learning media were designed according to users’ needs and learning outcomes of cellular communication system courses. Based on the testing results, the functionality showed 100% of features function as design specifications. Meanwhile, the user satisfaction testing results obtained an average MOS of 4.73, which means that the learning media is classified great. Furthermore, based on the quantitative testing, the average value of Quiz after using this interactive learning media was 81, which means that the learning media can increase students’ interest so that it affects the increase in learning outcomes by 66% from previous years.
基于对电讯大学电讯工程文凭专业学生的观察。结果表明，在蜂窝通信系统课程中，学生对呼叫处理和网络优化章节的学习和理解存在一定困难。这是由于目前的学习媒体，这些媒体只有教科书和Powerpoint幻灯片的形式，被认为不那么有吸引力。因此，学习过程变得无效，并对低学习成果产生影响。本研究采用多媒体开发生命周期(Multimedia Development Life Cycle, MDLC)方法，采用Adobe Flash专业CS6软件，采用action script 2.0编程语言，设计了一个交互式学习媒体。根据用户的需求和蜂窝通信系统课程的学习效果设计学习媒体。根据测试结果，该功能100%显示了设计规范的功能特征。同时，用户满意度测试结果的平均MOS为4.73，说明该学习媒体分类程度较高。此外，根据定量测试，使用该互动学习媒体后，Quiz的平均值为81，这意味着学习媒体可以提高学生的兴趣，从而影响学习成果比往年提高66%。
{"title":"Interactive Learning Media for Cellular Communication Systems using the Multimedia Development Life Cycle Model","authors":"Hasanah Putri, Iqbal Shadiq, Gigin Gantini Putri","doi":"10.15575/JOIN.V6I1.544","DOIUrl":"https://doi.org/10.15575/JOIN.V6I1.544","url":null,"abstract":"Based on the observations conducted to the students of Diploma of Telecommunications Engineering Telkom University. It revealed that the students have difficulty learning and understanding the chapters of call processing and network optimization in the course of cellular communication systems. It has resulted from the current learning media, which are only in the form of textbooks and Powerpoint slides considered less attractive. Hence, the learning process becomes ineffective and has an impact on low learning outcomes. In this study, an interactive learning media was designed with the Multimedia Development Life Cycle (MDLC) method, Adobe Flash professional CS6 software, using the action script 2.0 programming language. Learning media were designed according to users’ needs and learning outcomes of cellular communication system courses. Based on the testing results, the functionality showed 100% of features function as design specifications. Meanwhile, the user satisfaction testing results obtained an average MOS of 4.73, which means that the learning media is classified great. Furthermore, based on the quantitative testing, the average value of Quiz after using this interactive learning media was 81, which means that the learning media can increase students’ interest so that it affects the increase in learning outcomes by 66% from previous years.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86051970","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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