2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)最新文献

Measurement of Information Security Awareness Level: A Case Study of Online Transportation Users 信息安全意识水平的测量:以在线交通用户为例

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315375

R. Prakoso, Y. Ruldeviyani, K. F. Arisya, A. L. Fadhilah

{"title":"Measurement of Information Security Awareness Level: A Case Study of Online Transportation Users","authors":"R. Prakoso, Y. Ruldeviyani, K. F. Arisya, A. L. Fadhilah","doi":"10.1109/ISRITI51436.2020.9315375","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315375","url":null,"abstract":"The rise of misuse of online transportation accounts causes a person to be aware to protect their personal information. A person's awareness is an important factor for safeguarding his personal information assets and reducing crime loopholes. This research was conducted to measure the security awareness of online transportation users. This research was conducted by distributing questionnaires to 215 respondents who use online transportation applications in Indonesia. The framework used to measure the level of information security awareness is the Knowledge-Attitude-Behavior (KAB) model and Human Aspects of Information Security Questionnaire (HAIS-Q). Analytic Hierarchy Process (AHP) will be used as a data processing method to assess information security awareness level of online transportation users. The result shows that information security awareness level of online transportation users is at the level of “good”. But some focus areas of users indicate the score at the level of “average”, which the score is not enough to protect personal assets so need certain improvements in the application and user aspects that can increase the level of information security awareness of online transportation users.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115721914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Combination of Defected Ground Structure and Line Resonator for Mutual Coupling Reduction 一种用于减少相互耦合的缺陷接地结构和线谐振器的组合

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315370

Nur Muhamad Ziko Iskandar, E. Setijadi, A. Affandi

引用次数: 1

Comparison of The Classification Data Mining Methods to Identify Civil Servants in Indonesian Social Insurance Company 印尼社会保险公司公务员分类数据挖掘方法比较

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315444

A. Sasmito, Y. Ruldeviyani

引用次数: 1

Comparison of PSO, FA, and BA for Discrete Optimization Problems 离散优化问题的PSO、FA和BA的比较

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315371

Denni Huda Pratama, S. Suyanto

引用次数: 1

Comparison Of Eight Elements Array Structure Design For Coastal Surveillance Radar 海岸监视雷达八元阵列结构设计比较

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315394

Dian Rusdiyanto

引用次数: 0

Speech Gender Classification Using Bidirectional Long Short Term Memory 基于双向长短期记忆的语音性别分类

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315380

Rangga Dwi Alamsyah, S. Suyanto

引用次数: 5

Removing Noise, Reducing dimension, and Weighting Distance to Enhance $k$-Nearest Neighbors for Diabetes Classification 去噪、降维和加权距离增强$k$近邻糖尿病分类

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315515

Syifa Khairunnisa, S. Suyanto, Prasti Eko Yunanto

{"title":"Removing Noise, Reducing dimension, and Weighting Distance to Enhance $k$-Nearest Neighbors for Diabetes Classification","authors":"Syifa Khairunnisa, S. Suyanto, Prasti Eko Yunanto","doi":"10.1109/ISRITI51436.2020.9315515","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315515","url":null,"abstract":"Various methods of machine learning have been implemented in the medical field to classify various diseases, such as diabetes. The k-nearest neighbors (KNN) is one of the most known approaches for predicting diabetes. Many researchers have found by combining KNN with one or more other algorithms may provide a better result. In this paper, a combination of three procedures, removing noise, reducing the dimension, and weighting distance, is proposed to improve a standard voting-based KNN to classify Pima Indians Diabetes Dataset (PIDD) into two classes. First, the noises in the training set are removed using k-means clustering (KMC) to make the voter data in both classes more competent. Second, its dimensional is then reduced to decrease the intra-class data distances but increase the inter-class ones. Two methods of dimensional reduction: principal component analysis (PCA) and autoencoder (AE), are applied to investigate the linearity of the dataset. Since there is an imbalance on the dataset, a proportional weight is incorporated into the distance formula to get the fairness of the voting. A 5-fold cross validation-based evaluation shows that each proposed procedure works very well in enhancing the KNN. KMC is capable of increasing the accuracy of KNN from 81.6% to 86.7%. Combining KMC and PCA improves the KNN accuracy to be 90.9%. Next, a combination of KMC and AE enhances the KNN to gives an accuracy of 97.8%. Combining three proposed procedures of KMC, PCA, and Weighted KNN (WKNN) increases the accuracy to be 94.5%. Finally, the combination of KMC, AE, and WKNN reaches the highest accuracy of 98.3%. The facts that AE produces higher accuracies than PCA inform that the features in the dataset have a high non-linearity.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129858232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interference Mitigation in Cognitive Radio Network Based on Grey Wolf Optimizer Algorithm 基于灰狼优化算法的认知无线网络干扰抑制

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315517

Gregorius Dwi Perkasa, Niki Min Hidayati Robbi, I. Mustika, Widyawan

{"title":"Interference Mitigation in Cognitive Radio Network Based on Grey Wolf Optimizer Algorithm","authors":"Gregorius Dwi Perkasa, Niki Min Hidayati Robbi, I. Mustika, Widyawan","doi":"10.1109/ISRITI51436.2020.9315517","DOIUrl":"https://doi.org/10.1109/ISRITI51436.2020.9315517","url":null,"abstract":"Cognitive Radio Network (CNR) is a dynamic network where the users can adjust spectrum usage dynamically in accordance to the operational environment to minimize interference. However, it still has a major problem regarding the channel allocation used by the nodes. This problem exists because channel allocations are completely randomly generated so that they might cause interference to users on the same channel. To handle resource allocation problems in the CRN, the authors proposed a solution using the Grey Wolf Optimizer (GWO). This optimizer algorithm is an optimization included in the metaheuristic algorithm with the source of inspiration from the behavior of the gray wolf colony in hunting prey. In this job, Alpha serves as a prime candidate in finding the best channel. The ultimate goal of using this GWO optimization is to get the most optimal channel allocation scheme for each node in the cognitive radio network so that it has minimal interference and maximum network throughput. The authors have modified the fitness function and coding scheme of GWO to get the best share of resources from the CRN. From the simulations tested, the results showed that channel allocation using the GWO algorithm was able to increase throughput and reduce network interference.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128245245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Enhancement of Multi-User Key Extraction Scheme (MKES) Based on Imperfect Signal Reciprocity 基于不完全信号互易的多用户密钥提取方案的性能增强

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/ISRITI51436.2020.9315330

Suwadi, Wirawan, Mike Yuliana

引用次数: 0

Techno-Economic 5G New Radio Planning Using 26 GHz Frequency at Pulogadung Industrial Area 普落洞工业区26ghz频段5G新无线电技术经济规划

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI: 10.1109/isriti51436.2020.9315455

Desi Rianti, A. Hikmaturokhman, Dina Rachmawaty

{"title":"Techno-Economic 5G New Radio Planning Using 26 GHz Frequency at Pulogadung Industrial Area","authors":"Desi Rianti, A. Hikmaturokhman, Dina Rachmawaty","doi":"10.1109/isriti51436.2020.9315455","DOIUrl":"https://doi.org/10.1109/isriti51436.2020.9315455","url":null,"abstract":"The Pulogadung industrial area is a widely known developing industrial area that is perfectly ideal for the implementation of 5G technology to help run the Indonesian economy. Nonetheless, it is noteworthy that knowing the level of economic feasibility of an operator is highly crucial before making an investment in a network performance. This study focuses on an analysis of 5G network design in terms of coverage using the Urban Micro propagation model in the Uplink (UL) and Downlink (DL) Outdoor to Outdoor (O2O) Line of Sight (LOS) scenarios. In addition, it also aims to cover the discussion on the economic level of project feasibility using an optimistic scenario assuming 80% users, which is based on the projected increase in population growth of 5G users using the bass growth model method since its implementation in 2021–2030. The economic analysis used the parameters of Capital Expenditure (CAPEX), Operational Expenditure (OPEX), Net Present Value (NPV), Internal Rate of Return (IRR) to determine the feasibility of planning a 5G New Radio network in the Pulogadung Industrial Area. The calculation of Cost Benefit in the optimistic techno-economic scenario shows that each UL O2O LOS NPV scenario resulted in Rp. 28.369.498.095.53 with an IRR of 31.18%, while DL O2O LOS NPV resulted in Rp. 24.862.173.071.28 with an IRR of 26.68%. This result indicates that the performance of the 5G NR network in the Pulogadung Industrial Estate assuming the projections for the next 10 years is feasible.","PeriodicalId":325920,"journal":{"name":"2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129888496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5