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":"39 1","pages":"33-40"},"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":"11 1","pages":"79-87"},"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":"1 1","pages":"118-127"},"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":"60 1","pages":"1-10"},"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}
In various disease diagnoses, one of the parameters is white blood cells, consisting of eosinophils, basophils, neutrophils, lymphocytes, and monocytes. Manual identification takes a long time and tends to be subjective depending on the staff's experience, so the automatic identification of white blood cells will be faster and more accurate. White blood cells are identified by examining a colored blood smear (SADT) and examined under a digital microscope to obtain a cell image. Image identification of white blood cells is determined through HSV color space segmentation (Hue, Saturation Value) and feature extraction of the Gray Level Cooccurrence Matrix (GLCM) method using the Angular Second Moment (ASM), Contrast, Entropy, and Inverse Different Moment (IDM) features. The purpose of this study was to identify white blood cells by comparing the classification accuracy of the K-nearest neighbor (KNN), Naive Bayes Classification (NBC), and Multilayer Perceptron (MLP) methods. The classification results of 100 training data and 50 white blood cell image testing data. Tests on the KNN, NBC, and MLP methods yielded an accuracy of 82%, 80%, and 94%, respectively. Therefore, MLP was chosen as the best classification model in the identification of white blood cells.
{"title":"Identification of White Blood Cells Using Machine Learning Classification Based on Feature Extraction","authors":"Anwar Siswanto Musliman, A. Fadlil, A. Yudhana","doi":"10.15575/JOIN.V6I1.704","DOIUrl":"https://doi.org/10.15575/JOIN.V6I1.704","url":null,"abstract":"In various disease diagnoses, one of the parameters is white blood cells, consisting of eosinophils, basophils, neutrophils, lymphocytes, and monocytes. Manual identification takes a long time and tends to be subjective depending on the staff's experience, so the automatic identification of white blood cells will be faster and more accurate. White blood cells are identified by examining a colored blood smear (SADT) and examined under a digital microscope to obtain a cell image. Image identification of white blood cells is determined through HSV color space segmentation (Hue, Saturation Value) and feature extraction of the Gray Level Cooccurrence Matrix (GLCM) method using the Angular Second Moment (ASM), Contrast, Entropy, and Inverse Different Moment (IDM) features. The purpose of this study was to identify white blood cells by comparing the classification accuracy of the K-nearest neighbor (KNN), Naive Bayes Classification (NBC), and Multilayer Perceptron (MLP) methods. The classification results of 100 training data and 50 white blood cell image testing data. Tests on the KNN, NBC, and MLP methods yielded an accuracy of 82%, 80%, and 94%, respectively. Therefore, MLP was chosen as the best classification model in the identification of white blood cells.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":"36 1","pages":"63-72"},"PeriodicalIF":0.7,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78942900","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 student counseling process is the spearhead of character development proclaimed by the government through education regulation number 20 of 2018 concerning strengthening character education. Counseling at the secondary school level carries out to attend to these problems that might resolve with a decision support system. So that makes research challenging to measure completion on target because it is not doing based on data. The counseling teacher does not know about student's mental and emotional health conditions, so it is often wrong to handle them. Therefore, we need a system that can recognize conditions and provide recommendations for managing problems and predicting students who have potential issues. The Algorithm used to predict problem students is K-Nearest Neighbor with a dataset of 100 students. The stages of predictive calculation are data collection, data cleaning, simulation, and accuracy evaluation. Meanwhile, building the system is done using the rapid application development methodology where the instrument used to map the student's condition is the Strenght and Difficulties Questionaire instrument. This research is a system to predict problem students with an accuracy rate of 83%. The level of user experience based on the User Experience Questionnaire (UEQ) results in the conclusion that the system reaches "Above Average.". This system is expecting to help counseling teachers implement an early warning system, help students know learning modalities, and help parents recognize the child's personality better.
{"title":"Prediction System for Problem Students using k-Nearest Neighbor and Strength and Difficulties Questionnaire","authors":"D. Kurniadi, A. Mulyani, I. Muliana","doi":"10.15575/JOIN.V6I1.701","DOIUrl":"https://doi.org/10.15575/JOIN.V6I1.701","url":null,"abstract":"The student counseling process is the spearhead of character development proclaimed by the government through education regulation number 20 of 2018 concerning strengthening character education. Counseling at the secondary school level carries out to attend to these problems that might resolve with a decision support system. So that makes research challenging to measure completion on target because it is not doing based on data. The counseling teacher does not know about student's mental and emotional health conditions, so it is often wrong to handle them. Therefore, we need a system that can recognize conditions and provide recommendations for managing problems and predicting students who have potential issues. The Algorithm used to predict problem students is K-Nearest Neighbor with a dataset of 100 students. The stages of predictive calculation are data collection, data cleaning, simulation, and accuracy evaluation. Meanwhile, building the system is done using the rapid application development methodology where the instrument used to map the student's condition is the Strenght and Difficulties Questionaire instrument. This research is a system to predict problem students with an accuracy rate of 83%. The level of user experience based on the User Experience Questionnaire (UEQ) results in the conclusion that the system reaches \"Above Average.\". This system is expecting to help counseling teachers implement an early warning system, help students know learning modalities, and help parents recognize the child's personality better.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":"537 1","pages":"53-62"},"PeriodicalIF":0.7,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76992286","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 : 2020-12-21DOI: 10.24252/JOIN.V5I2.17667
Evi Lusiana, Muh. Zukri Malik, Suriyani Suriyani
Breast cancer is a problem that often occurs in women both in developed and developing countries. For this reason, it is necessary to prevent the increasing mortality rate, one of which is by increasing self-efficacy which can be achieved by providing advice, information and motivation with empowerment education. Based on this, the researchers conducted this study with the aim of knowing the effect of empowerment education in increasing the self-efficacy of breast cancer patients. The research method used is a quantitative study with a one group test approach. The results obtained are from 5 (five) items of self-efficacy, 3 (three) items that have changed, namely self-confidence in getting information about illness / complaints experienced (p: 0.023), receiving help from the community, family and friends (p. : 0.02), and treats breast cancer disease and symptoms (0.041). Based on these results it can be concluded that empowerment education activities should be one of the activities of providing nursing interventions to breast cancer patients. Keywords: Empowerment Education; Self Efficacy; Breast cancer
{"title":"EFEKTIFITAS KEGIATAN EMPOWERMENT EDUCATION DALAM MENINGKATKAN SELF EFFICACY PASIEN KANKER PAYUDARA DI RS.UMUM KOTA MAKASSAR","authors":"Evi Lusiana, Muh. Zukri Malik, Suriyani Suriyani","doi":"10.24252/JOIN.V5I2.17667","DOIUrl":"https://doi.org/10.24252/JOIN.V5I2.17667","url":null,"abstract":"Breast cancer is a problem that often occurs in women both in developed and developing countries. For this reason, it is necessary to prevent the increasing mortality rate, one of which is by increasing self-efficacy which can be achieved by providing advice, information and motivation with empowerment education. Based on this, the researchers conducted this study with the aim of knowing the effect of empowerment education in increasing the self-efficacy of breast cancer patients. The research method used is a quantitative study with a one group test approach. The results obtained are from 5 (five) items of self-efficacy, 3 (three) items that have changed, namely self-confidence in getting information about illness / complaints experienced (p: 0.023), receiving help from the community, family and friends (p. : 0.02), and treats breast cancer disease and symptoms (0.041). Based on these results it can be concluded that empowerment education activities should be one of the activities of providing nursing interventions to breast cancer patients. Keywords: Empowerment Education; Self Efficacy; Breast cancer","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":"137 1","pages":"136-145"},"PeriodicalIF":0.7,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75753041","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}
S. Supriyanto, M. Harika, Maya Sri Ramadiani, D. R. Ramdania
The main challenge that facial recognition introduces is the difficulty of uneven lighting or dark tendencies. The image is poorly lit, which makes it difficult for the system to perform facial recognition. This study aims to normalize the lighting in the image using the Multiscale Retinex method. This method is applied to a face recognition system based on Principal Component Analysis to determine whether this method effectively improves images with uneven lighting. The results showed that the Multiscale Retinex approach to face recognition's correctness was better, from 40% to 76%. Multiscale Retinex has the advantage of dark facial image types because it produces a brighter image output.
{"title":"Multiscale Retinex Application to Analyze Face Recognition","authors":"S. Supriyanto, M. Harika, Maya Sri Ramadiani, D. R. Ramdania","doi":"10.15575/JOIN.V5I2.668","DOIUrl":"https://doi.org/10.15575/JOIN.V5I2.668","url":null,"abstract":"The main challenge that facial recognition introduces is the difficulty of uneven lighting or dark tendencies. The image is poorly lit, which makes it difficult for the system to perform facial recognition. This study aims to normalize the lighting in the image using the Multiscale Retinex method. This method is applied to a face recognition system based on Principal Component Analysis to determine whether this method effectively improves images with uneven lighting. The results showed that the Multiscale Retinex approach to face recognition's correctness was better, from 40% to 76%. Multiscale Retinex has the advantage of dark facial image types because it produces a brighter image output.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":"17 1","pages":"217-226"},"PeriodicalIF":0.7,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85440415","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 : 2020-07-23DOI: 10.24252/join.v5i1.10473
Hertiana Hertiana, Ariyanti Saleh
{"title":"EFEKTIVITAS PENDIDIKAN KESEHATAN TERHADAP PENGETAHUAN DAN SIKAP KELUARGA DALAM MERAWAT PENDERITA GANGGUAN JIWA DI KOTA PALOPO","authors":"Hertiana Hertiana, Ariyanti Saleh","doi":"10.24252/join.v5i1.10473","DOIUrl":"https://doi.org/10.24252/join.v5i1.10473","url":null,"abstract":"","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":"6 1","pages":"38"},"PeriodicalIF":0.7,"publicationDate":"2020-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80180500","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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