Pub Date : 2022-12-19DOI: 10.33096/ilkom.v14i3.1224.264-274
Najirah Umar, Yuyun Yuyun, Hamdan Gani
The immersion is an essential component of the modern digital game. Currently, immersion is the required component which should be included in the digital game. The modern game which success within game industry surely has included immersion as a component. Although digital games have been introduced for many years, yet what is immersion game been known very little. Regarding the intensive study about user immersion, there is still a lack of knowledge about game immersion. First, the game designers, game developers, and gamers are facing problems how to understand whether their game is immersive or not. There is no knowledge regarding how to evaluate their game, whether immersive or not, and this process requires expert knowledge. Second, currently, the game designers are relied on speculative interpretation to evaluate their game because there is no method to examine whether the game is immersive or not. Therefore, this study aims to propose a method that enable to evaluate if the game is immersive or not. This method is emerged as knowledge and recommendation that quickly be able to assist the game designers, game developers, and gamers evaluating whether a game is immersive or not. First, this research conducts a literature review to categorize the game immersion features. Second, this study proposes an effective method that can analyse and recommends whether a game is immersive or not. Finally, this study reveals that the finding could be used as a recommendation for the other immersive technology platforms.
{"title":"Generating game immersion features for immersive game selection","authors":"Najirah Umar, Yuyun Yuyun, Hamdan Gani","doi":"10.33096/ilkom.v14i3.1224.264-274","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1224.264-274","url":null,"abstract":"The immersion is an essential component of the modern digital game. Currently, immersion is the required component which should be included in the digital game. The modern game which success within game industry surely has included immersion as a component. Although digital games have been introduced for many years, yet what is immersion game been known very little. Regarding the intensive study about user immersion, there is still a lack of knowledge about game immersion. First, the game designers, game developers, and gamers are facing problems how to understand whether their game is immersive or not. There is no knowledge regarding how to evaluate their game, whether immersive or not, and this process requires expert knowledge. Second, currently, the game designers are relied on speculative interpretation to evaluate their game because there is no method to examine whether the game is immersive or not. Therefore, this study aims to propose a method that enable to evaluate if the game is immersive or not. This method is emerged as knowledge and recommendation that quickly be able to assist the game designers, game developers, and gamers evaluating whether a game is immersive or not. First, this research conducts a literature review to categorize the game immersion features. Second, this study proposes an effective method that can analyse and recommends whether a game is immersive or not. Finally, this study reveals that the finding could be used as a recommendation for the other immersive technology platforms.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42818123","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1134.314-322
Poetri Lestari Lokapitasari Belluano, Benny Leonard Enrico Panggabean, P. Purnawansyah, Kasmira Kasmira
The Academic Information System (xSIA) is built to its users to manage Study Program modules, including student academic grades. xSIA applying the Moodle Learning Management System (LMS) was developed by implementing Quick UDP Internet Connection (QUIC) technology with the HTTP/3 protocol which can demonstrate protocol transaction speed performance. The design of information systems and databases employs the Convention Over Configuration paradigm. The Prototyping Model is used to graphically represent the workflow of the system with an experimental research design. System modeling utilizes Unified Modeling Language (UML) tools, Data Base Management System (DBMS) using PostgreSQL, and UDP ports as a means of data communication. The implementation of Quick UDP Internet Connection (QUIC) on the xSIA moodle LMS is effective for real-time communications that do not require conditions to open, maintain, or terminate connections as in streaming video conference. It is also optimal because the UDP data is transferred individually and checked for its integrity upon arrival. When a video streaming transaction last 02:36 seconds with a file size of 4.1mb, there is a significant difference of 100.98ms in the waiting time to first byte (ttfb).
学术信息系统(xSIA)是为其用户建立的，用于管理学习计划模块，包括学生的学术成绩。xSIA应用于Moodle学习管理系统(LMS)，采用HTTP/3协议实现快速UDP互联网连接(QUIC)技术，可以展示协议的交易速度性能。信息系统和数据库的设计采用“约定优于配置”范式。原型模型用于图形化地表示具有实验研究设计的系统的工作流程。系统建模使用统一建模语言(UML)工具，数据库管理系统(DBMS)使用PostgreSQL，并使用UDP端口作为数据通信手段。在xSIA moodle LMS上实现快速UDP互联网连接(Quick UDP Internet Connection, QUIC)，可以有效实现流媒体视频会议中不需要打开、维护或终止连接条件的实时通信。这也是最优的，因为UDP数据是单独传输的，并在到达时检查其完整性。当一个视频流事务持续02:36秒，文件大小为4.1mb时，到第一个字节(ttfb)的等待时间有100.98ms的显著差异。
{"title":"The development of Web-based information system using quick UDP internet connection","authors":"Poetri Lestari Lokapitasari Belluano, Benny Leonard Enrico Panggabean, P. Purnawansyah, Kasmira Kasmira","doi":"10.33096/ilkom.v14i3.1134.314-322","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1134.314-322","url":null,"abstract":"The Academic Information System (xSIA) is built to its users to manage Study Program modules, including student academic grades. xSIA applying the Moodle Learning Management System (LMS) was developed by implementing Quick UDP Internet Connection (QUIC) technology with the HTTP/3 protocol which can demonstrate protocol transaction speed performance. The design of information systems and databases employs the Convention Over Configuration paradigm. The Prototyping Model is used to graphically represent the workflow of the system with an experimental research design. System modeling utilizes Unified Modeling Language (UML) tools, Data Base Management System (DBMS) using PostgreSQL, and UDP ports as a means of data communication. The implementation of Quick UDP Internet Connection (QUIC) on the xSIA moodle LMS is effective for real-time communications that do not require conditions to open, maintain, or terminate connections as in streaming video conference. It is also optimal because the UDP data is transferred individually and checked for its integrity upon arrival. When a video streaming transaction last 02:36 seconds with a file size of 4.1mb, there is a significant difference of 100.98ms in the waiting time to first byte (ttfb).","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69492580","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1291.284-293
Ivan Anggriawan, Wawan Gunawan
During the pandemic, to reduce the number of Covid-19 spreads, the government imposed social distancing and work from home (WFH) to reduce community activities outside the home. This caused people to have irregular patterns or lifestyles which less any physical activity . It surely can lower immunity system in which can increase the risk of being infected by the virus. Therefore, during the pandemic, sports or exercises become one of the activities that regularly carried out by the community to increase their immunity. One of the sports activities that can be done to maintain their immunity is cycling. Cycling itself is a light activity that can be practiced by all ages. This occasion is certainly a good marketing target for bicycle selling companies, but the company sometimes experiences problems regarding bicycle stocks that do not match with the consumer market target. The purpose of this study is to find out what types of bicycles are on demand by predicting bicycle sales and looking at the desired interests of the community. This study uses the K-Means Clustering algorithm. The results of the K-Means Clustering research are divided into three clusters; Cluster 1 with 209 members with the most interest in mountain bikes, Cluster 2 with 787 members with the most interest in folding bicycles, and Cluster 3 with 540 members with bicycle interests. Most of them are city bicycles, from the clustering process above, the Dunn Index validation (Dunn Index) can be obtained with a value of 0.1324532.
{"title":"Implementation of Data Mining Using K-Means Algorithm for Bicycle Sales Prediction","authors":"Ivan Anggriawan, Wawan Gunawan","doi":"10.33096/ilkom.v14i3.1291.284-293","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1291.284-293","url":null,"abstract":"During the pandemic, to reduce the number of Covid-19 spreads, the government imposed social distancing and work from home (WFH) to reduce community activities outside the home. This caused people to have irregular patterns or lifestyles which less any physical activity . It surely can lower immunity system in which can increase the risk of being infected by the virus. Therefore, during the pandemic, sports or exercises become one of the activities that regularly carried out by the community to increase their immunity. One of the sports activities that can be done to maintain their immunity is cycling. Cycling itself is a light activity that can be practiced by all ages. This occasion is certainly a good marketing target for bicycle selling companies, but the company sometimes experiences problems regarding bicycle stocks that do not match with the consumer market target. The purpose of this study is to find out what types of bicycles are on demand by predicting bicycle sales and looking at the desired interests of the community. This study uses the K-Means Clustering algorithm. The results of the K-Means Clustering research are divided into three clusters; Cluster 1 with 209 members with the most interest in mountain bikes, Cluster 2 with 787 members with the most interest in folding bicycles, and Cluster 3 with 540 members with bicycle interests. Most of them are city bicycles, from the clustering process above, the Dunn Index validation (Dunn Index) can be obtained with a value of 0.1324532.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49312119","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1283.194-202
Ratu Mutiara Siregar, W. Kusuma, Annisa Annisa
Precision Medicine is used to improve proper health care and patients' quality of life, one of which is diabetes. Diabetes Mellitus (DM) is a multifactorial and heterogeneous group of disorders characterized by deficiency or failure to maintain normal glucose homeostasis. About 90% of all DM patients are Type 2 Diabetes Mellitus (T2DM). Biological characteristics and genetic information of T2DM disease were obtained by looking for associations in Single Nucleotide Polymorphism (SNP) which allows for determining the relationship between phenotypic and genotypic information and identifying genes associated with T2DM disease. This research focuses on the Support Vector Regression method and Genetic Algorithm to obtain SNPs that have previously calculated the correlation value using Spearman's rank correlation. Then do association mapping on the SNP results from the SVR-GA selection and check pastasis interaction. The results produced 14 SNP importance. Evaluation of the model using the mean absolute error (MAE) obtained is 0.02807. If the value of MAE is close to zero, then a model can be accepted. The genes generated from the association can be used to assist other researchers in finding the right treatment for T2DM patients according to their genetic profile.
{"title":"Association of single nucleotide polymorphism and phenotype in type 2 of diabetes mellitus using Support Vector Regression and Genetic Algorithm","authors":"Ratu Mutiara Siregar, W. Kusuma, Annisa Annisa","doi":"10.33096/ilkom.v14i3.1283.194-202","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1283.194-202","url":null,"abstract":"Precision Medicine is used to improve proper health care and patients' quality of life, one of which is diabetes. Diabetes Mellitus (DM) is a multifactorial and heterogeneous group of disorders characterized by deficiency or failure to maintain normal glucose homeostasis. About 90% of all DM patients are Type 2 Diabetes Mellitus (T2DM). Biological characteristics and genetic information of T2DM disease were obtained by looking for associations in Single Nucleotide Polymorphism (SNP) which allows for determining the relationship between phenotypic and genotypic information and identifying genes associated with T2DM disease. This research focuses on the Support Vector Regression method and Genetic Algorithm to obtain SNPs that have previously calculated the correlation value using Spearman's rank correlation. Then do association mapping on the SNP results from the SVR-GA selection and check pastasis interaction. The results produced 14 SNP importance. Evaluation of the model using the mean absolute error (MAE) obtained is 0.02807. If the value of MAE is close to zero, then a model can be accepted. The genes generated from the association can be used to assist other researchers in finding the right treatment for T2DM patients according to their genetic profile.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46748234","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}
A library visitor would want a quiet atmosphere without noise when in the library so that he can concentrate when reading a book. However, not all visitors come to the library to read books; some want to chat and use free Wi-Fi or other, so it disturbs the concentration of other visitors who read books. Therefore, it is necessary to have a tool to detect sound pressure or sound based on the sound level and the sound produced in a library based on the noise level limit in the library, namely 45-55 dB (desible). This tool is designed based on a microcontroller where the definition of a microcontroller is a complete microprocessor system contained in a microcontroller chip which is different from the multi-purpose microprocessor used in a PC because a microcontroller generally already includes the minimum system supporting components of a microprocessor, namely memory, and programming. This tool can help officers monitor the library room for noise that can interfere with the concentration and comfort of library visitors. Based on the results of testing, the overall system is as desired, including the noise detection tool can work in an integrated system, where when the sound sensor detects a noise that exceeds the sound limit, the buzzer will sound, the red led light turns on, the sound module issues a voice message pre-recorded and also the device can be controlled or monitored from the web application.
{"title":"Design of library noise detection tools based on voice pressure parameters","authors":"Yuda Irawan, Refni Wahyuni, Hasnor Khotimah, Herianto -, Bambang Kurniawan, Haris Tri Saputra, Yulisman Yulisman, Abd. Muhaimin, Reno Renaldi, Rahmaddeni Rahmaddeni","doi":"10.33096/ilkom.v14i3.1191.237-244","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1191.237-244","url":null,"abstract":"A library visitor would want a quiet atmosphere without noise when in the library so that he can concentrate when reading a book. However, not all visitors come to the library to read books; some want to chat and use free Wi-Fi or other, so it disturbs the concentration of other visitors who read books. Therefore, it is necessary to have a tool to detect sound pressure or sound based on the sound level and the sound produced in a library based on the noise level limit in the library, namely 45-55 dB (desible). This tool is designed based on a microcontroller where the definition of a microcontroller is a complete microprocessor system contained in a microcontroller chip which is different from the multi-purpose microprocessor used in a PC because a microcontroller generally already includes the minimum system supporting components of a microprocessor, namely memory, and programming. This tool can help officers monitor the library room for noise that can interfere with the concentration and comfort of library visitors. Based on the results of testing, the overall system is as desired, including the noise detection tool can work in an integrated system, where when the sound sensor detects a noise that exceeds the sound limit, the buzzer will sound, the red led light turns on, the sound module issues a voice message pre-recorded and also the device can be controlled or monitored from the web application.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48214939","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1135.275-283
R. Gustriansyah, Juhaini Alie, N. Suhandi
The Sustainable Development Goals (SDGs) are a blueprint for improving the human life quality. Goal 16 (G16) is related to security, and it is in line with the Universal Declaration of Human Rights and the Preamble to the 1945 Constitution. To support the implementation of the G16 achievement, the Indonesian National Police (Polri) has made serious efforts to provide a sense of safety for the community and to minimize crime rates. One of the efforts that could be made is to map areas based on the level of crimes so that the Polri can determine the appropriate strategy/priority of action for mitigation. Therefore, this study aimed to cluster provinces in Indonesia based on the four G16 indicators of the SDGs related to security, namely the number of homicide cases, the victim proportion, the proportion of people who feel safe walking alone in the area where they live, and the proportion of victims of violence that reported to the police in the past year using five hierarchical clustering methods, namely: Single-Linkage, Average-Linkage, Complete-Linkage, Ward, and Division Analysis. Then, methods were validated and compared using six cluster validations to obtain the most compact method. The results showed that Ward's method outperformed the others and produced three clusters. Clusters 1, 2, and 3 contained 18, 5, and 11 provinces respectively.
{"title":"Hierarchical clustering for crime rate mapping in Indonesia","authors":"R. Gustriansyah, Juhaini Alie, N. Suhandi","doi":"10.33096/ilkom.v14i3.1135.275-283","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1135.275-283","url":null,"abstract":"The Sustainable Development Goals (SDGs) are a blueprint for improving the human life quality. Goal 16 (G16) is related to security, and it is in line with the Universal Declaration of Human Rights and the Preamble to the 1945 Constitution. To support the implementation of the G16 achievement, the Indonesian National Police (Polri) has made serious efforts to provide a sense of safety for the community and to minimize crime rates. One of the efforts that could be made is to map areas based on the level of crimes so that the Polri can determine the appropriate strategy/priority of action for mitigation. Therefore, this study aimed to cluster provinces in Indonesia based on the four G16 indicators of the SDGs related to security, namely the number of homicide cases, the victim proportion, the proportion of people who feel safe walking alone in the area where they live, and the proportion of victims of violence that reported to the police in the past year using five hierarchical clustering methods, namely: Single-Linkage, Average-Linkage, Complete-Linkage, Ward, and Division Analysis. Then, methods were validated and compared using six cluster validations to obtain the most compact method. The results showed that Ward's method outperformed the others and produced three clusters. Clusters 1, 2, and 3 contained 18, 5, and 11 provinces respectively.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42238717","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1328.218-228
Bahtiar Imran, Erfan Wahyudi, Ahmad Subki, Salman Salman, Ahmad Yani
A stroke is a fatal disease that usually occurs to the people over the age of 65. The treatment progress of the medical field is growing rapidly, especially with the technological advance, with the emergence of various medical record data sets that can be used in medical records to identify trends in these data sets using data mining. The purpose of this study was to propose a model to classify stroke survivors using data mining, by utilizing data from the kaggle sharing dataset. The models proposed in this study were AdaBoost, Decision Tree and Random Forest, evaluation results using Confusion Matrix and ROC Analysis. The results obtained were that the decision tree model was able to provide the best accuracy results compared to the other models, which was 0.953 for Number of Folds 5 and 10. From the results of this study, the decision tree model was able to provide good classification results for stroke sufferers.
{"title":"Classification of stroke patients using data mining with adaboost, decision tree and random forest models","authors":"Bahtiar Imran, Erfan Wahyudi, Ahmad Subki, Salman Salman, Ahmad Yani","doi":"10.33096/ilkom.v14i3.1328.218-228","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1328.218-228","url":null,"abstract":"A stroke is a fatal disease that usually occurs to the people over the age of 65. The treatment progress of the medical field is growing rapidly, especially with the technological advance, with the emergence of various medical record data sets that can be used in medical records to identify trends in these data sets using data mining. The purpose of this study was to propose a model to classify stroke survivors using data mining, by utilizing data from the kaggle sharing dataset. The models proposed in this study were AdaBoost, Decision Tree and Random Forest, evaluation results using Confusion Matrix and ROC Analysis. The results obtained were that the decision tree model was able to provide the best accuracy results compared to the other models, which was 0.953 for Number of Folds 5 and 10. From the results of this study, the decision tree model was able to provide good classification results for stroke sufferers.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45012313","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1252.186-193
M. F. Banjar, Ira Irawati, Fitriyani Umar, Lilis Nur Hayati
Stroke is a disease in which the sufferer experiences or experiences a rupture of a blood vessel in the brain so that the brain does not get a blood supply that provides oxygen. Patients who suffer from stroke will experience cognitive disorders ranging from decreased consciousness, visuospatial disorders, non-verbal learning disorders, communication disorders, and reduced levels of patient attention. Data from the World Stroke Organization shows that there are 13.7 million new stroke cases every year, and about 5.5 million deaths occur due to stroke. This research aims to analyze the attributes of any variables that affect the classification of strike disease and to test the performance of stroke classification in the form of accuracy, precision, recall, and f-measure. The method used is a random forest using a tree, namely 50, 100, 200, and 500. The classification of stroke is divided into stroke and no stroke. The data used is 5110, divided into 70% training data and 30% testing data. The results showed that the performance of a random forest using 100 trees was better than using 50, 200, and 500 trees, with an accuracy value of 86.82%, a precision of 15.76%, a recall of 38.15%, and an f1-score 22.30% after doing SMOTE ..
{"title":"Analysis of Stroke Classification Using Random Forest Method","authors":"M. F. Banjar, Ira Irawati, Fitriyani Umar, Lilis Nur Hayati","doi":"10.33096/ilkom.v14i3.1252.186-193","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1252.186-193","url":null,"abstract":"Stroke is a disease in which the sufferer experiences or experiences a rupture of a blood vessel in the brain so that the brain does not get a blood supply that provides oxygen. Patients who suffer from stroke will experience cognitive disorders ranging from decreased consciousness, visuospatial disorders, non-verbal learning disorders, communication disorders, and reduced levels of patient attention. Data from the World Stroke Organization shows that there are 13.7 million new stroke cases every year, and about 5.5 million deaths occur due to stroke. This research aims to analyze the attributes of any variables that affect the classification of strike disease and to test the performance of stroke classification in the form of accuracy, precision, recall, and f-measure. The method used is a random forest using a tree, namely 50, 100, 200, and 500. The classification of stroke is divided into stroke and no stroke. The data used is 5110, divided into 70% training data and 30% testing data. The results showed that the performance of a random forest using 100 trees was better than using 50, 200, and 500 trees, with an accuracy value of 86.82%, a precision of 15.76%, a recall of 38.15%, and an f1-score 22.30% after doing SMOTE ..","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47350988","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1254.178-185
Muhammad Indra Abidin, I. Nurtanio, A. Achmad
Deep-fake in videos is a video synthesis technique by changing the people’s face in the video with others’ face. Deep-fake technology in videos has been used to manipulate information, therefore it is necessary to detect deep-fakes in videos. This paper aimed to detect deep-fakes in videos using the ResNext Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) algorithms. The video data was divided into 4 types, namely video with 10 frames, 20 frames, 40 frames and 60 frames. Furthermore, face detection was used to crop the image to 100 x 100 pixels and then the pictures were processed using ResNext CNN and LSTM. The confusion matrix was employed to measure the performance of the ResNext CNN-LSTM algorithm. The indicators used were accuracy, precision, and recall. The results of data classification showed that the highest accuracy value was 90% for data with 40 and 60 frames. While data with 10 frames had the lowest accuracy with 52% only. ResNext CNN-LSTM was able to detect deep-fakes in videos well even though the size of the image was small.
{"title":"Deepfake Detection in Videos Using Long Short-Term Memory and CNN ResNext","authors":"Muhammad Indra Abidin, I. Nurtanio, A. Achmad","doi":"10.33096/ilkom.v14i3.1254.178-185","DOIUrl":"https://doi.org/10.33096/ilkom.v14i3.1254.178-185","url":null,"abstract":"Deep-fake in videos is a video synthesis technique by changing the people’s face in the video with others’ face. Deep-fake technology in videos has been used to manipulate information, therefore it is necessary to detect deep-fakes in videos. This paper aimed to detect deep-fakes in videos using the ResNext Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) algorithms. The video data was divided into 4 types, namely video with 10 frames, 20 frames, 40 frames and 60 frames. Furthermore, face detection was used to crop the image to 100 x 100 pixels and then the pictures were processed using ResNext CNN and LSTM. The confusion matrix was employed to measure the performance of the ResNext CNN-LSTM algorithm. The indicators used were accuracy, precision, and recall. The results of data classification showed that the highest accuracy value was 90% for data with 40 and 60 frames. While data with 10 frames had the lowest accuracy with 52% only. ResNext CNN-LSTM was able to detect deep-fakes in videos well even though the size of the image was small.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46084453","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 : 2022-12-19DOI: 10.33096/ilkom.v14i3.1136.294-302
Zulhipni Reno Saputra Elsi, K. Karnadi, Jimmie Jimmie, Fajrie Agus Dwino Putra, H. Hartini, Sri Primaini Agustanti
This study aims to find out about Information Technology management at Muhammadiyah University of Palembang and to get right advice in managing Information Technology from the University level to the Study Program. Regarding benchmarks in Information Technology Governance use the Cobit 5 framework with the Evaluate, Direct and Monitor domains. Monitoring and evaluation was carried out using a questionnaire distributed to lecturers and employees at the Muhammadiyah University of Palembang and the researchers did observations on the management of higher education information technology governance. Based on the questionnaire result, the highest gap occurs in sub domain 4, which is 3.65 while the observation result towards the capability level is at level 3 with a value of 56.67%, the sub domain ensuring resource optimization has the highest capability value of 66.67%. Based on the data obtained using the EDM domain, the University of Muhamadiyah Palembang has to set Standard Operating Procedures (SOP) and Work Instructions (IK) so every five processes can run well to create good IT governance.
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