Muhammad Irwan Yanwari, A. S. Prabuwono, T. R. Yudantoro, Nurseno Bayu Aji, Wiktasari, Slamet Handoko
Scheduling is a common problem that has been raised for a long time. Many algorithms have been created for this problem. Some algorithms offer flexibility in terms of constraints and complex operations. Because of that complexity, many algorithms will need huge computation resources and execution time. A platform like a web application has many restrictions such as execution time and computation resources. A complex algorithm is not suited for the web application platform. Priority scheduling is a scheduling algorithm based on a priority queue. Every schedule slot will produce a queue based on the constraints. Each constraint will have a different weight. Weight in queue represents their priority. This algorithm provides a light algorithm that only needs a few computations and execution times. The exam schedule is one of many problems in educational institutions. A web application is a popular platform that can be accessed from everywhere. Many educational institutions use web platforms as their main system platform. Web platforms have some restrictions such as execution time. Due to web platform restrictions, priority scheduling is a suitable algorithm for this platform. In this study, the author tries to implement a priority scheduling algorithm in scheduling cases with a website platform and shows that this algorithm solution can be an alternative for solving scheduling cases with low computational resources.
{"title":"Priority Scheduling Implementation for Exam Schedule","authors":"Muhammad Irwan Yanwari, A. S. Prabuwono, T. R. Yudantoro, Nurseno Bayu Aji, Wiktasari, Slamet Handoko","doi":"10.24002/ijis.v5i2.6871","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6871","url":null,"abstract":"Scheduling is a common problem that has been raised for a long time. Many algorithms have been created for this problem. Some algorithms offer flexibility in terms of constraints and complex operations. Because of that complexity, many algorithms will need huge computation resources and execution time. A platform like a web application has many restrictions such as execution time and computation resources. A complex algorithm is not suited for the web application platform. Priority scheduling is a scheduling algorithm based on a priority queue. Every schedule slot will produce a queue based on the constraints. Each constraint will have a different weight. Weight in queue represents their priority. This algorithm provides a light algorithm that only needs a few computations and execution times. The exam schedule is one of many problems in educational institutions. A web application is a popular platform that can be accessed from everywhere. Many educational institutions use web platforms as their main system platform. Web platforms have some restrictions such as execution time. Due to web platform restrictions, priority scheduling is a suitable algorithm for this platform. In this study, the author tries to implement a priority scheduling algorithm in scheduling cases with a website platform and shows that this algorithm solution can be an alternative for solving scheduling cases with low computational resources.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87220912","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}
Meyliana, Surjandy, A. Condrobimo, Henry Antonius Eka Widjaja, Wiedjaja Atmadja, Rudy Susanto, Bruno Sablan
Blockchain technology uses in many fields, and one of them is logistics. This study aims to propose designing and implementing a blockchain technology-based application for logistics delivery combined with the Internet of Things (IoT) called MSCWR. Logistics and delivery of valuable products have a common problem, and security is also questionable. Therefore, the research process in making prototypes starts by defining the problem, planning, prototyping, testing, and designing validation. The methodology used is User-Centered Design, focus group discussion conducted with business actors directly, and system or prototype development using the System Development Life Cycle framework. As a result, the business processes create using an activity diagram, the features define using a use case diagram, and the screen design to show the prototype development created at an early stage in the research. Finally, the testing conducts to test how well the system is running. In the end, the validation of test results performs in good results
{"title":"The Implementation of Business Process Blockchain Technology Based of MSCWR SmartBox Model","authors":"Meyliana, Surjandy, A. Condrobimo, Henry Antonius Eka Widjaja, Wiedjaja Atmadja, Rudy Susanto, Bruno Sablan","doi":"10.24002/ijis.v5i2.6793","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6793","url":null,"abstract":"Blockchain technology uses in many fields, and one of them is logistics. This study aims to propose designing and implementing a blockchain technology-based application for logistics delivery combined with the Internet of Things (IoT) called MSCWR. Logistics and delivery of valuable products have a common problem, and security is also questionable. Therefore, the research process in making prototypes starts by defining the problem, planning, prototyping, testing, and designing validation. The methodology used is User-Centered Design, focus group discussion conducted with business actors directly, and system or prototype development using the System Development Life Cycle framework. As a result, the business processes create using an activity diagram, the features define using a use case diagram, and the screen design to show the prototype development created at an early stage in the research. Finally, the testing conducts to test how well the system is running. In the end, the validation of test results performs in good results \u0000 ","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83581642","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}
Aisyatul Karima, Afandi Nur Aziz Thohari, F. Abdollah, Sirli Fahriah, Parsumo Rahardjo, Wahyu Sulistiyo, S. Sukamto
Abstract. The number of patients in Hospital during pandemic covid-19 has increasing significantly which cause do not get the optimal service because limitation of human resource. Furthermore, they need tools to detect human in patient’s room and monitor the movement of people. IoT capable to control the room properly. Regarding to these problems, the aim of this research is to develop SPAM (Smart Patient Monitoring System) which implement Internet of Thing (IoT) to control the patient in hospital using Rasberry Pi. Those data are real-time and completed by notification via telegram. Consequently, if there are emergency they can observe easily. We use Scructural Similarity Index Measurement (SSIM) technique by comparing different images on several consecutive frames of video by Rasberry Pi. The research methodology is instrument preparation, design system, data processing, testing and evaluation. The experiment prove that the system has effectively spotted human things accurately captured on camera more than 15 trials. Although there is a delay of between 5 and 40 seconds, notifications are also correctly transmitted. The system correctly recognizes when the light is bright with lux > 100 when evaluating the level of light intensity at a distance of 50 cm to 300 cm. Keywords: Security, Internet of Thing, Hospital, SSIM, Rasberry Pi
{"title":"SPAM (Smart Patient Monitoring System) using Structural Similarity Index Measurement","authors":"Aisyatul Karima, Afandi Nur Aziz Thohari, F. Abdollah, Sirli Fahriah, Parsumo Rahardjo, Wahyu Sulistiyo, S. Sukamto","doi":"10.24002/ijis.v5i2.6791","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6791","url":null,"abstract":"Abstract. The number of patients in Hospital during pandemic covid-19 has increasing significantly which cause do not get the optimal service because limitation of human resource. Furthermore, they need tools to detect human in patient’s room and monitor the movement of people. IoT capable to control the room properly. Regarding to these problems, the aim of this research is to develop SPAM (Smart Patient Monitoring System) which implement Internet of Thing (IoT) to control the patient in hospital using Rasberry Pi. Those data are real-time and completed by notification via telegram. Consequently, if there are emergency they can observe easily. We use Scructural Similarity Index Measurement (SSIM) technique by comparing different images on several consecutive frames of video by Rasberry Pi. The research methodology is instrument preparation, design system, data processing, testing and evaluation. The experiment prove that the system has effectively spotted human things accurately captured on camera more than 15 trials. Although there is a delay of between 5 and 40 seconds, notifications are also correctly transmitted. The system correctly recognizes when the light is bright with lux > 100 when evaluating the level of light intensity at a distance of 50 cm to 300 cm. \u0000 \u0000Keywords: Security, Internet of Thing, Hospital, SSIM, Rasberry Pi","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75147684","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}
David Sugiarto, J. Siswantoro, Muhammad Farid Naufal, B. Idrus
Indonesia is a country that has thousands of plant types that can be used as traditional medicine. However, some people have not utilized this potential optimally due to the lack of knowledge about medicinal plants' types, benefits, and substances. Therefore, there is a need to develop an application that can identify medicinal plants that grow in Indonesia and provide information about the benefits and content of the substances contained in them. In this study, medicinal plants will be recognized using a mobile application from leaf images based on a pre-trained convolutional neural network (CNN) with a transfer learning technique. Three pre-trained CNN architectures, namely VGG-16, MobileNetV2, and DenseNet-121, are explored for medicinal plant recognition. Hyperparameter tuning is performed at the fully connected layer of all architectures with 20 possible modifications to find the best model. The experimental results on 24 types of medicinal plants show that the model based on MobileNetV2 achieves the best classification accuracy of 97.74%. The best model is obtained by modifying the fully connected layer of MobileNetV2 into three dense layers with the number of neurons 736, 448, and 928, respectively. After the application recognizes the types of medicinal plants, information about the benefits and substances contained in them is displayed to the user.
{"title":"Mobile Application for Medicinal Plants Recognition from Leaf Image Using Convolutional Neural Network","authors":"David Sugiarto, J. Siswantoro, Muhammad Farid Naufal, B. Idrus","doi":"10.24002/ijis.v5i2.6633","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6633","url":null,"abstract":"Indonesia is a country that has thousands of plant types that can be used as traditional medicine. However, some people have not utilized this potential optimally due to the lack of knowledge about medicinal plants' types, benefits, and substances. Therefore, there is a need to develop an application that can identify medicinal plants that grow in Indonesia and provide information about the benefits and content of the substances contained in them. In this study, medicinal plants will be recognized using a mobile application from leaf images based on a pre-trained convolutional neural network (CNN) with a transfer learning technique. Three pre-trained CNN architectures, namely VGG-16, MobileNetV2, and DenseNet-121, are explored for medicinal plant recognition. Hyperparameter tuning is performed at the fully connected layer of all architectures with 20 possible modifications to find the best model. The experimental results on 24 types of medicinal plants show that the model based on MobileNetV2 achieves the best classification accuracy of 97.74%. The best model is obtained by modifying the fully connected layer of MobileNetV2 into three dense layers with the number of neurons 736, 448, and 928, respectively. After the application recognizes the types of medicinal plants, information about the benefits and substances contained in them is displayed to the user.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"70 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77936291","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}
Abstract. EMRs play an essential role in documenting clinical information. Nurses are integral to the success of an EMR implementation, as they are the largest group of employees in a hospital and provide patient care. A major factor in the success of EMR implementation is nurses' acceptance of the system. This study is designed to measure nurses' willingness to use EMRs in clinical practice, determine factors influencing nurses' acceptance of EMR documentation in clinical practice, and gain an understanding of the nurses' perspective on EMRs to encourage the adoption and implementation of EMRs in other health facilities in Saudi Arabia. This study included nurses from Hail General Hospital, Maternity and Children Hospital, King Khalid Hospital, and Hail General Hospital. Study results indicate that perceived usefulness and ease of use are strongly correlated, resulting in nurses' greater acceptance of EMRs. According to the study results, nurses are willing to use EMRs. Our result shows that overall, nurses find the EMR useful in their jobs, with 40.9% agreeing and 24.4% strongly agreeing. Whereas the overall easiness was 9.4% agreed and 24 strongly agreed. Nurses need to be prepared for a demanding workplace through their nursing curriculum. Nursing students and professionals should understand the importance of EMRs in ensuring high-quality, effective, and efficient patient care. It is imperative that nurses continuously improve their computer skills to keep up with technological advancements.
{"title":"An Investigation of Nurses' Perceptions of the Usefulness and Easiness of Using Electronic Medical Records in Saudi Arabia: A Technology Acceptance Model","authors":"A. Alhur","doi":"10.24002/ijis.v5i2.6833","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6833","url":null,"abstract":"Abstract. EMRs play an essential role in documenting clinical information. Nurses are integral to the success of an EMR implementation, as they are the largest group of employees in a hospital and provide patient care. A major factor in the success of EMR implementation is nurses' acceptance of the system. This study is designed to measure nurses' willingness to use EMRs in clinical practice, determine factors influencing nurses' acceptance of EMR documentation in clinical practice, and gain an understanding of the nurses' perspective on EMRs to encourage the adoption and implementation of EMRs in other health facilities in Saudi Arabia. This study included nurses from Hail General Hospital, Maternity and Children Hospital, King Khalid Hospital, and Hail General Hospital. Study results indicate that perceived usefulness and ease of use are strongly correlated, resulting in nurses' greater acceptance of EMRs. According to the study results, nurses are willing to use EMRs. Our result shows that overall, nurses find the EMR useful in their jobs, with 40.9% agreeing and 24.4% strongly agreeing. Whereas the overall easiness was 9.4% agreed and 24 strongly agreed. Nurses need to be prepared for a demanding workplace through their nursing curriculum. Nursing students and professionals should understand the importance of EMRs in ensuring high-quality, effective, and efficient patient care. It is imperative that nurses continuously improve their computer skills to keep up with technological advancements.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72514352","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}
Tenia Wahyuningrum, Gita Fadila Fitriana, A. Bahtiar, Aina Azalea Ardani, Imelda Imelda, T. G. Soares
The government has established a development program for the development of Information and Communication Technology with the term e-government. The implementation of e-government in government governance and public services certainly requires the use of information and communication technology (ICT) along with reliable human resources to manage it. There is still a reasonably high gap between the EBGS maturity level of the central agency and the index, and the local government is a challenge for the Meranti Islands Regency. To realize its vision and mission, the Meranti Islands Regency has made various efforts for transparency, accountability, good governance, and efficiency of government administration supported through ICT. The purpose of this research is the mapping of ICT utilization data in Meranti Islands Regency and the results of the identification of the obstacles that occur using GAP Analysis. GAP analysis uses Root Cause Analysis (RCA) and SWOT analysis for its analysis. The GAP analysis results show that based on the SWOT analysis, 18 strengths, 19 weaknesses, 12 opportunities, and 12 thread ats in the application of ICT are obtained, which are divided into 6 components. Based on the Root Cause Analysis, it was found that the main problem was caused by the low capacity of human resources in the application of ICT, as well as insufficient hardware/software requirements. For the study results study, it can be concluded that a SWOT analysis equipped with Root Cause Analysis can be used for strategic planning for implementing EBGS in the next fiveyears.
{"title":"Meranti Island E-Government Master Plan: A Root Cause and SWOT Analysis","authors":"Tenia Wahyuningrum, Gita Fadila Fitriana, A. Bahtiar, Aina Azalea Ardani, Imelda Imelda, T. G. Soares","doi":"10.24002/ijis.v5i2.6086","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6086","url":null,"abstract":"The government has established a development program for the development of Information and Communication Technology with the term e-government. The implementation of e-government in government governance and public services certainly requires the use of information and communication technology (ICT) along with reliable human resources to manage it. There is still a reasonably high gap between the EBGS maturity level of the central agency and the index, and the local government is a challenge for the Meranti Islands Regency. To realize its vision and mission, the Meranti Islands Regency has made various efforts for transparency, accountability, good governance, and efficiency of government administration supported through ICT. The purpose of this research is the mapping of ICT utilization data in Meranti Islands Regency and the results of the identification of the obstacles that occur using GAP Analysis. GAP analysis uses Root Cause Analysis (RCA) and SWOT analysis for its analysis. The GAP analysis results show that based on the SWOT analysis, 18 strengths, 19 weaknesses, 12 opportunities, and 12 thread ats in the application of ICT are obtained, which are divided into 6 components. Based on the Root Cause Analysis, it was found that the main problem was caused by the low capacity of human resources in the application of ICT, as well as insufficient hardware/software requirements. For the study results study, it can be concluded that a SWOT analysis equipped with Root Cause Analysis can be used for strategic planning for implementing EBGS in the next fiveyears.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76063169","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}
Patricia Meta Pudya Astari, Clara Hetty Primasari, Djoko Budiyanto Setyohadi, Yohanes Priadi Wibisono, Thomas Adi Purnomo Sidhi, M. Cininta
The rapid development of technology affects people’s lives, including education, and virtual reality is one of many digital learning media that can be useful for learning. Virtual reality allows users to interact with the environment through a virtual world. With this concept in mind, an application to support gamelan learning based on Virtual Reality was developed called Peking Metagamelan Virtual Reality. Peking is a gamelan instrument made of bronze with rectangular blades. This application needs to know the user’s opinion regarding its performance and usability in its development. Therefore, the Think-aloud method assisted in the usability analysis process in the VR Metagamelan Peking application. The Think-aloud approach helps to express what the user feels and thinks when using the application. The research process involved five respondents from various educational backgrounds and different experiences. Respondents were asked to work on several task scenarios that were ordered. During the task scenario, respondents were asked to convey their thoughts regarding the application they were trying. The results were then analyzed and produced some recommendations for further improvements to the VR Metagamelan Peking application. The recommendations included improving the application interface, adding several features, and reducing the character’s speed.
{"title":"Applying the Think-Aloud Method for Usability Analysis in the Peking Metagamelan Virtual Reality Learning Application","authors":"Patricia Meta Pudya Astari, Clara Hetty Primasari, Djoko Budiyanto Setyohadi, Yohanes Priadi Wibisono, Thomas Adi Purnomo Sidhi, M. Cininta","doi":"10.24002/ijis.v5i2.6605","DOIUrl":"https://doi.org/10.24002/ijis.v5i2.6605","url":null,"abstract":"The rapid development of technology affects people’s lives, including education, and virtual reality is one of many digital learning media that can be useful for learning. Virtual reality allows users to interact with the environment through a virtual world. With this concept in mind, an application to support gamelan learning based on Virtual Reality was developed called Peking Metagamelan Virtual Reality. Peking is a gamelan instrument made of bronze with rectangular blades. This application needs to know the user’s opinion regarding its performance and usability in its development. Therefore, the Think-aloud method assisted in the usability analysis process in the VR Metagamelan Peking application. The Think-aloud approach helps to express what the user feels and thinks when using the application. The research process involved five respondents from various educational backgrounds and different experiences. Respondents were asked to work on several task scenarios that were ordered. During the task scenario, respondents were asked to convey their thoughts regarding the application they were trying. The results were then analyzed and produced some recommendations for further improvements to the VR Metagamelan Peking application. The recommendations included improving the application interface, adding several features, and reducing the character’s speed.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76378720","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}
R. Gustriansyah, Juhaini Alie, A. Sanmorino, R. Heriansyah, Megat Norulazmi Megat Mohamed Noor
The COVID-19 pandemic has increased inflation and poverty rates in many cities, thus requiring considerable attention from the government as a policymaker. Therefore, this study aims to cluster regencies/cities that need mitigation priorities from the Indonesian government based on inflation and poverty rates in 2021. Four machine learning methods, namely k-Means (KM), Partitioning around medoids (PAM), Ward, and Divisive analysis (Diana) are utilized and compared to achieve that purpose. Clustering 90 regencies/cities in Indonesia produced five optimal clusters. Furthermore, the clustering results were validated using the Silhouette width (SW) and Dunn index (DI). The results showed that the k-means method produced the most compact cluster. Hence, this study's results can be utilized as a reference for the government in determining the steps and priorities of economic policy in Indonesia.
新冠肺炎疫情加剧了许多城市的通货膨胀率和贫困率，因此需要作为政策制定者的政府给予高度关注。因此，本研究旨在根据2021年的通货膨胀率和贫困率，对需要印尼政府优先缓解的县市/城市进行集群。四种机器学习方法，即k-Means (KM)， Partitioning around medidoids (PAM)， Ward和divide analysis (Diana)被利用和比较来实现这一目的。印度尼西亚的90个县/城市产生了5个最佳集群。此外，利用廓形宽度(SW)和邓恩指数(DI)对聚类结果进行了验证。结果表明，k-means方法产生的聚类最紧凑。因此，本研究的结果可以作为印尼政府确定经济政策的步骤和优先事项的参考。
{"title":"Machine Learning for Clustering Regencies-Cities Based on Inflation and Poverty Rates in Indonesia","authors":"R. Gustriansyah, Juhaini Alie, A. Sanmorino, R. Heriansyah, Megat Norulazmi Megat Mohamed Noor","doi":"10.24002/ijis.v5i1.5682","DOIUrl":"https://doi.org/10.24002/ijis.v5i1.5682","url":null,"abstract":"The COVID-19 pandemic has increased inflation and poverty rates in many cities, thus requiring considerable attention from the government as a policymaker. Therefore, this study aims to cluster regencies/cities that need mitigation priorities from the Indonesian government based on inflation and poverty rates in 2021. Four machine learning methods, namely k-Means (KM), Partitioning around medoids (PAM), Ward, and Divisive analysis (Diana) are utilized and compared to achieve that purpose. Clustering 90 regencies/cities in Indonesia produced five optimal clusters. Furthermore, the clustering results were validated using the Silhouette width (SW) and Dunn index (DI). The results showed that the k-means method produced the most compact cluster. Hence, this study's results can be utilized as a reference for the government in determining the steps and priorities of economic policy in Indonesia.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83949082","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 their inaugural releases in 2007, Google’s Android and Apple’s iOS have grown to dominate the mobile OS market share. Currently, they jointly possess over 99% of the global market share with Android being the leading mobile Operating System of choice worldwide, controlling close to 70% of the market share. Mobile devices have enabled the exponential growth of a plethora of mobile applications that play key roles in enabling many use cases that are pivotal in our daily lives. On the other hand, access to a large pool of potential end users is available to both legitimate and nefarious applications, thus making mobile devices a burgeoning target of malicious applications. Current malware detection solutions rely on tedious, time-consuming, knowledge-based, and manual processes to identify malware. This paper presents BarkDroid, a novel Android malware detection technique that uses the low-level Bark Frequency Cepstral Coefficients audio features to detect malware. The results obtained outperform results obtained using other features on the same datasets. BarkDroid achieved 97.9% accuracy, 98.5% precision, an F1 score of 98.6%, and shorter execution times.
{"title":"BarkDroid: Android Malware Detection Using Bark Frequency Cepstral Coefficients","authors":"Paul Tarwireyi, A. Terzoli, M. Adigun","doi":"10.24002/ijis.v5i1.6266","DOIUrl":"https://doi.org/10.24002/ijis.v5i1.6266","url":null,"abstract":"Since their inaugural releases in 2007, Google’s Android and Apple’s iOS have grown to dominate the mobile OS market share. Currently, they jointly possess over 99% of the global market share with Android being the leading mobile Operating System of choice worldwide, controlling close to 70% of the market share. Mobile devices have enabled the exponential growth of a plethora of mobile applications that play key roles in enabling many use cases that are pivotal in our daily lives. On the other hand, access to a large pool of potential end users is available to both legitimate and nefarious applications, thus making mobile devices a burgeoning target of malicious applications. Current malware detection solutions rely on tedious, time-consuming, knowledge-based, and manual processes to identify malware. This paper presents BarkDroid, a novel Android malware detection technique that uses the low-level Bark Frequency Cepstral Coefficients audio features to detect malware. The results obtained outperform results obtained using other features on the same datasets. BarkDroid achieved 97.9% accuracy, 98.5% precision, an F1 score of 98.6%, and shorter execution times.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85268862","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}
Mohd Faizal Ab Razak, M. Jaya, Z. Ismail, Ahmad Firdaus
Malware attack cases continue to rise in our current day. The Trojan attack, which may be extremely destructive by unlawfully controlling other users' computers in order to steal their data. As a result, Trojan horse detection is essential to identify the Trojan and limit Trojan attacks. In this study, we proposed a Trojan detection system that employed machine learning algorithms to detect Trojan horses within the system. A public dataset of Trojan horses that contain 2001 samples comprises of 1041 Trojan horses and 960 of benign is used to train the machine learning classification. In this paper, the Trojan detection system is trained using four types of classifiers which are Random Forest, J48, Decision Table and Naïve Bayes. WEKA is used for the execution of the classification process and performance analysis. The results indicated that the detection system trained with the Random Forest and Decision Table algorithms obtained the maximum level of accuracy.
{"title":"Trojan Detection System Using Machine Learning Approach","authors":"Mohd Faizal Ab Razak, M. Jaya, Z. Ismail, Ahmad Firdaus","doi":"10.24002/ijis.v5i1.5673","DOIUrl":"https://doi.org/10.24002/ijis.v5i1.5673","url":null,"abstract":"Malware attack cases continue to rise in our current day. The Trojan attack, which may be extremely destructive by unlawfully controlling other users' computers in order to steal their data. As a result, Trojan horse detection is essential to identify the Trojan and limit Trojan attacks. In this study, we proposed a Trojan detection system that employed machine learning algorithms to detect Trojan horses within the system. A public dataset of Trojan horses that contain 2001 samples comprises of 1041 Trojan horses and 960 of benign is used to train the machine learning classification. In this paper, the Trojan detection system is trained using four types of classifiers which are Random Forest, J48, Decision Table and Naïve Bayes. WEKA is used for the execution of the classification process and performance analysis. The results indicated that the detection system trained with the Random Forest and Decision Table algorithms obtained the maximum level of accuracy.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80943349","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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