Pub Date : 2022-10-02DOI: 10.23917/khif.v8i2.16902
Yosa Aditya Prakosa, Alfa Faridh Suni
– Anagram is a turn-based role-playing game where two players construct words by arranging given letters. A significant aspect of playing a game is the challenge. A good challenge comes from an opponent with a close ability. In a two-player game like Anagram, the second player can be a nonhuman player called Non-Playable Character (NPC). A balanced game is more engaging. Therefore, it is imperative to insert artificial intelligence (AI) into an NPC to make it possess a balance ability. This study investigates the AI algorithm that is the most appropriate to make a balance NPC for Anagram games. We tested three scenarios: Descending AI, Random AI, and AI with k-Nearest Neighbour (k-NN). Descending AI gets an Anagram solution by selecting a word with the highest score from all possible answers. Random AI picks a word randomly from the possible answers, while AI with k-NN chooses a word closest to one of the human players. The results show that Descending AI is the best algorithm to make the strongest NPC, which always gets the highest score, followed by Random AI and AI with k-NN. However, AI with the k-NN algorithm makes the constructed NPC has the highest number of turns at an average of 18, while Descending AI gets 14 turns and Random AI has 15 turns. Looking at the remaining lives at the end of the game, AI with k-NN makes the NPC has 25 lives left, while Descending AI has 59 lives, and Random AI has 48 lives. Less remaining lives suggest that NPC containing AI with the k-NN algorithm matches closer to the human player and therefore is more suitable for Anagram NPC.
{"title":"Backtracking and k-Nearest Neighbour for Non-Player Character to Balance Opponent in a Turn-Based Role Playing Game of Anagram","authors":"Yosa Aditya Prakosa, Alfa Faridh Suni","doi":"10.23917/khif.v8i2.16902","DOIUrl":"https://doi.org/10.23917/khif.v8i2.16902","url":null,"abstract":"– Anagram is a turn-based role-playing game where two players construct words by arranging given letters. A significant aspect of playing a game is the challenge. A good challenge comes from an opponent with a close ability. In a two-player game like Anagram, the second player can be a nonhuman player called Non-Playable Character (NPC). A balanced game is more engaging. Therefore, it is imperative to insert artificial intelligence (AI) into an NPC to make it possess a balance ability. This study investigates the AI algorithm that is the most appropriate to make a balance NPC for Anagram games. We tested three scenarios: Descending AI, Random AI, and AI with k-Nearest Neighbour (k-NN). Descending AI gets an Anagram solution by selecting a word with the highest score from all possible answers. Random AI picks a word randomly from the possible answers, while AI with k-NN chooses a word closest to one of the human players. The results show that Descending AI is the best algorithm to make the strongest NPC, which always gets the highest score, followed by Random AI and AI with k-NN. However, AI with the k-NN algorithm makes the constructed NPC has the highest number of turns at an average of 18, while Descending AI gets 14 turns and Random AI has 15 turns. Looking at the remaining lives at the end of the game, AI with k-NN makes the NPC has 25 lives left, while Descending AI has 59 lives, and Random AI has 48 lives. Less remaining lives suggest that NPC containing AI with the k-NN algorithm matches closer to the human player and therefore is more suitable for Anagram NPC.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114591607","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 : 2022-09-15DOI: 10.23917/khif.v8i2.17069
Ardi Pujiyanta, Fiftin Novianto
Grid computing can be considered large-scale distributed cluster computing and parallel distributed network processing. The two most important issues in managing user work are resource allocation and scheduling of required resources. When user jobs are submitted, they are managed by resource intermediaries who find and allocate the right resources. After the resource allocation stage, work scheduled on the existing resources according to the user's required resources. In most grid systems with traditional scheduling, jobs are submitted and placed in waiting room queues to wait for the required resources to become available. Each grid system can use a different scheduling algorithm to execute jobs based on other parameters, such as resources, delivery time, and execution duration. There is no guarantee that these traditional scheduling algorithms will get the job done. The First Come First Serve Left Right Hole Scheduling (FCFS-LRH) reservation strategy improves resource utilization in a grid system by using a local scheduler. Compared to traditional strategies. There are two objectives of this research. First, compare the first fit, best fit, and worst fit algorithms to find empty timeslots and place them in a virtual view. Second, reduce the idle time value. The results showed that the FCFS-LRH method could reduce the idle time value of the FCFS-EDF and FCFS methods. The overall execution time of the first fit with the FCFS-LRH strategy is better than the FCFS-EDF
{"title":"Job Scheduling on Grid Computing Using First Fit, Best Fit, and Worst Fit","authors":"Ardi Pujiyanta, Fiftin Novianto","doi":"10.23917/khif.v8i2.17069","DOIUrl":"https://doi.org/10.23917/khif.v8i2.17069","url":null,"abstract":"Grid computing can be considered large-scale distributed cluster computing and parallel distributed network processing. The two most important issues in managing user work are resource allocation and scheduling of required resources. When user jobs are submitted, they are managed by resource intermediaries who find and allocate the right resources. After the resource allocation stage, work scheduled on the existing resources according to the user's required resources. In most grid systems with traditional scheduling, jobs are submitted and placed in waiting room queues to wait for the required resources to become available. Each grid system can use a different scheduling algorithm to execute jobs based on other parameters, such as resources, delivery time, and execution duration. There is no guarantee that these traditional scheduling algorithms will get the job done. The First Come First Serve Left Right Hole Scheduling (FCFS-LRH) reservation strategy improves resource utilization in a grid system by using a local scheduler. Compared to traditional strategies. There are two objectives of this research. First, compare the first fit, best fit, and worst fit algorithms to find empty timeslots and place them in a virtual view. Second, reduce the idle time value. The results showed that the FCFS-LRH method could reduce the idle time value of the FCFS-EDF and FCFS methods. The overall execution time of the first fit with the FCFS-LRH strategy is better than the FCFS-EDF","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121736846","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 : 2022-09-15DOI: 10.23917/khif.v8i2.17488
Marzuki Pilliang, M. Munawar
Risk Management is an integral part of every project. Risk management must estimate the risks’ significance, especially in the SDLC process, and mitigate those risks. Since 2016, many papers and journals have researched planning, design, and risk control in software development projects over the last five years. This study aims to find the most exciting topics for researchers in risk management, especially in software engineering projects. This paper takes a systematic approach to reviewing articles containing risk management in software development projects. This study collects papers and journals included in the international online library database, then summarizes them according to the stages of the PICOC methodology. This paper results in the focus of research in the last five years on Agile methods. The current issue is that many researchers are trying to explicitly integrate risk management into the Agile development process by creating a comprehensive risk management framework. This SLR helps future research get a theoretical basis to solve the studied problem. The SLR explains the focuses of previous research, analysis of research results, and the weaknesses of the investigation. For further study, take one of the topic papers, do a critical review, and find research gaps.
{"title":"Risk Management in Software Development Projects: A Systematic Literature Review","authors":"Marzuki Pilliang, M. Munawar","doi":"10.23917/khif.v8i2.17488","DOIUrl":"https://doi.org/10.23917/khif.v8i2.17488","url":null,"abstract":"Risk Management is an integral part of every project. Risk management must estimate the risks’ significance, especially in the SDLC process, and mitigate those risks. Since 2016, many papers and journals have researched planning, design, and risk control in software development projects over the last five years. This study aims to find the most exciting topics for researchers in risk management, especially in software engineering projects. This paper takes a systematic approach to reviewing articles containing risk management in software development projects. This study collects papers and journals included in the international online library database, then summarizes them according to the stages of the PICOC methodology. This paper results in the focus of research in the last five years on Agile methods. The current issue is that many researchers are trying to explicitly integrate risk management into the Agile development process by creating a comprehensive risk management framework. This SLR helps future research get a theoretical basis to solve the studied problem. The SLR explains the focuses of previous research, analysis of research results, and the weaknesses of the investigation. For further study, take one of the topic papers, do a critical review, and find research gaps.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129733558","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 : 2022-09-15DOI: 10.23917/khif.v8i2.16349
Refianto Damai Darmawan, W. Kusuma, H. Rahmawan
Covid-19 is a global pandemic that drives many researchers to strive to look for its solution, especially in the field of health, medicine, and total countermeasures. Early screening with in-silico processes is crucial to minimize the search space of the potential drugs to cure a disease. This research aims to find potential drugs of covid-19 disease in the ZINC database to be further investigated through the in-vitro method. About 997.402.117 chemical compounds are searched about their similarity to some of the confirmed drugs to combat coronavirus. Sequential computation would take months to accomplish this task. The general programming graphic processing unit approach is used to implement a similarity comparison algorithm in parallel, in order to speed up the process. The result of this study shows the parallel algorithm implementation can speed up the computation process up to 55 times faster, and also that some of the chemical compounds have high similarity scores and can be found in nature
{"title":"Herbal Compound Screening with GPU Computation on ZINC Database through Similarity Comparison Approach","authors":"Refianto Damai Darmawan, W. Kusuma, H. Rahmawan","doi":"10.23917/khif.v8i2.16349","DOIUrl":"https://doi.org/10.23917/khif.v8i2.16349","url":null,"abstract":"Covid-19 is a global pandemic that drives many researchers to strive to look for its solution, especially in the field of health, medicine, and total countermeasures. Early screening with in-silico processes is crucial to minimize the search space of the potential drugs to cure a disease. This research aims to find potential drugs of covid-19 disease in the ZINC database to be further investigated through the in-vitro method. About 997.402.117 chemical compounds are searched about their similarity to some of the confirmed drugs to combat coronavirus. Sequential computation would take months to accomplish this task. The general programming graphic processing unit approach is used to implement a similarity comparison algorithm in parallel, in order to speed up the process. The result of this study shows the parallel algorithm implementation can speed up the computation process up to 55 times faster, and also that some of the chemical compounds have high similarity scores and can be found in nature","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130400757","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}
- Dental disease is one of the health problems commonly found in Indonesia. Data from the Indonesian Health Authority indicates an imbalance between the number of handled dental cases and the number of dental specialists who treat them. Technological advances bring significant improvements in the quality of medical services. A reliable Group Decision Support System (GDSS) requires a knowledge base editor for expert knowledge acquisition. A critical aspect in building a knowledge base is the interactive interface design. The problem that often arises is that experts find it hard to use a system because the interface does not meet their expectations. In this study, we analyze the interface requirements for a knowledge base editor with a group of experts. The purpose is to report on the process of designing a knowledge base editor interface with a user-centered expert group using the Information Systems Research (ISR-Framework) framework. We conducted several Focus Group Discussions involving 20 dentists, one dental specialist, and one Information Technology Expert in the GDSS field. The repetitive characteristics of this method help increase the value of user satisfaction. The research results expectedly support the ISR framework as a guide for designing future knowledge acquisition applications.
{"title":"Design of Dental Disease Knowledge Base Editor Dialog using ISR-Framework","authors":"Aridhanyati Arifin, Rahadian Kurniawan, S. Kusumadewi, Andri Panca Purnama, Kukuh Eka Nugraha","doi":"10.23917/khif.v8i1.15107","DOIUrl":"https://doi.org/10.23917/khif.v8i1.15107","url":null,"abstract":"- Dental disease is one of the health problems commonly found in Indonesia. Data from the Indonesian Health Authority indicates an imbalance between the number of handled dental cases and the number of dental specialists who treat them. Technological advances bring significant improvements in the quality of medical services. A reliable Group Decision Support System (GDSS) requires a knowledge base editor for expert knowledge acquisition. A critical aspect in building a knowledge base is the interactive interface design. The problem that often arises is that experts find it hard to use a system because the interface does not meet their expectations. In this study, we analyze the interface requirements for a knowledge base editor with a group of experts. The purpose is to report on the process of designing a knowledge base editor interface with a user-centered expert group using the Information Systems Research (ISR-Framework) framework. We conducted several Focus Group Discussions involving 20 dentists, one dental specialist, and one Information Technology Expert in the GDSS field. The repetitive characteristics of this method help increase the value of user satisfaction. The research results expectedly support the ISR framework as a guide for designing future knowledge acquisition applications.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117273755","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 : 2022-03-26DOI: 10.23917/khif.v8i1.15854
I. M. Erwin, D. Prajitno, E. Prakasa
Traffic accidents are generally caused by human error as a driver. The main cause is that the vehicle shifts away from the driving lane without the driver realizing it. Usually, because the driver is sleepy or drunk. Therefore, it is necessary to have a system that functions to assist the driver's navigation to stay on the correct driving path, such as a driver assistance system (DAS). In this system, the driving lane detector is the main part. This system serves to assist the driver's navigation to stay on the correct driving path. Vehicles are installed with cameras to record video towards the road ahead. Computers are also installed for image processing, identifying left and right road lines, and forming ego-lane. This paper offers an image processing-based method for recognizing driving lanes and presenting visualizations in real-time. This method has been tested using a data set, that video driving on Indonesian highway on the Cipali and Palikanci sections using dashboard camera. The test results obtained an accuracy of 99.25%.
{"title":"Detection of Highway Lane using Color Filtering and Line Determination","authors":"I. M. Erwin, D. Prajitno, E. Prakasa","doi":"10.23917/khif.v8i1.15854","DOIUrl":"https://doi.org/10.23917/khif.v8i1.15854","url":null,"abstract":"Traffic accidents are generally caused by human error as a driver. The main cause is that the vehicle shifts away from the driving lane without the driver realizing it. Usually, because the driver is sleepy or drunk. Therefore, it is necessary to have a system that functions to assist the driver's navigation to stay on the correct driving path, such as a driver assistance system (DAS). In this system, the driving lane detector is the main part. This system serves to assist the driver's navigation to stay on the correct driving path. Vehicles are installed with cameras to record video towards the road ahead. Computers are also installed for image processing, identifying left and right road lines, and forming ego-lane. This paper offers an image processing-based method for recognizing driving lanes and presenting visualizations in real-time. This method has been tested using a data set, that video driving on Indonesian highway on the Cipali and Palikanci sections using dashboard camera. The test results obtained an accuracy of 99.25%.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123246705","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 : 2022-03-16DOI: 10.23917/khif.v8i1.13727
Asril Adi Sunarto, Yuli Noviawan
Coronavirus Disease (COVID-19) has made Indonesia's health condition critical. Therefore, the President of the Republic of Indonesia disclosed Presidential Decree No. 7 in 2020 regarding the Task Force for the Acceleration of Coronavirus Disease 2019 (COVID-19) Handling. The decree relates to Act No. 14 in 2008 regarding Public Information Disclosure, Presidential Regulation No. 95 in 2018 concerning Electronic-Based Government Systems, and Presidential Instruction No. 3 in 2003 concerning National Policies and Strategies for E-Government Development. The decree demands information system development, similar to https://covid19.go .id, which describes COVID-19 nationwide. The site explains what COVID-19 and data of the COVID-19 outspread with geolocation and digital map, which may attract public attention. The presidential instruction forces local governments to build an information system, which is in line with the site by the central government. This paper describes the development of the system using a spiral model. It involves a variety of free and open-source software such as CodeIgniter, Mapbox, Morris Chart, MySQL, and WordPress. The site has been operational, and it attracts 150 visitors a day with 200 visits per day. As of January 6, 2021, the website has recorded 89,852 views.
{"title":"Information System on Mapping and Geolocation of COVID-19 in the City of Sukabumi","authors":"Asril Adi Sunarto, Yuli Noviawan","doi":"10.23917/khif.v8i1.13727","DOIUrl":"https://doi.org/10.23917/khif.v8i1.13727","url":null,"abstract":"Coronavirus Disease (COVID-19) has made Indonesia's health condition critical. Therefore, the President of the Republic of Indonesia disclosed Presidential Decree No. 7 in 2020 regarding the Task Force for the Acceleration of Coronavirus Disease 2019 (COVID-19) Handling. The decree relates to Act No. 14 in 2008 regarding Public Information Disclosure, Presidential Regulation No. 95 in 2018 concerning Electronic-Based Government Systems, and Presidential Instruction No. 3 in 2003 concerning National Policies and Strategies for E-Government Development. The decree demands information system development, similar to https://covid19.go .id, which describes COVID-19 nationwide. The site explains what COVID-19 and data of the COVID-19 outspread with geolocation and digital map, which may attract public attention. The presidential instruction forces local governments to build an information system, which is in line with the site by the central government. This paper describes the development of the system using a spiral model. It involves a variety of free and open-source software such as CodeIgniter, Mapbox, Morris Chart, MySQL, and WordPress. The site has been operational, and it attracts 150 visitors a day with 200 visits per day. As of January 6, 2021, the website has recorded 89,852 views.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123136848","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 : 2022-03-10DOI: 10.23917/khif.v8i1.15213
Rindu Hafil Muhammadi, Tri Ginanjar Laksana, Amalia Beladinna Arifa
- Data from the Ministry of Civil Works and Public Housing (Kementrian PUPR) in 2019 shows that around 81 million millennials do not own houses. Government Regulation Number 25 of 2020 on the Implementation of Public Housing Savings, commonly called PP 25 Tapera 2020, is one of the government’s efforts to ensure that Indonesian people can afford houses. Tapera is a deposit of workers for house financing, which is refundable after the term expires. Immediately after enaction, there were many public responses regarding the ordinance. We investigate public sentiments commenting on the regulation and use Support Vector Machine (SVM) in the study since it has a good level of accuracy. It also requires labels and training data. To speed up labeling, we use the lexicon-based method. The issue in the lexicon-based lies in the dictionary component as the most significant factor. Therefore, it is possible to update the dictionary automatically by combining lexicon-based and SVM. The SVM approach can contribute to lexicon-based, and lexicon-based can help label datasets on SVM to produce good accuracy. The research begins with collecting data from Twitter, preprocessing raw and unstructured data into ready-to-use data, labeling the data with lexicon-based, weighting with TF-IDF, processing using SVM, and evaluating algorithm performance model with a confusion matrix. The results showed that the combination of lexicon-based and SVM worked well. Lexicon-based managed to label 519 tweet data. SVM managed to get an accuracy value of 81.73% with the RBF kernel function. Another test with a Sigmoid kernel attains the highest precision at 78.68%. The RBF kernel has the highest recall result with a value of 81.73%. Then, the F1-score for both the RBF kernel and Sigmoid is 79.60%.
{"title":"Combination of Support Vector Machine and Lexicon-Based Algorithm in Twitter Sentiment Analysis","authors":"Rindu Hafil Muhammadi, Tri Ginanjar Laksana, Amalia Beladinna Arifa","doi":"10.23917/khif.v8i1.15213","DOIUrl":"https://doi.org/10.23917/khif.v8i1.15213","url":null,"abstract":"- Data from the Ministry of Civil Works and Public Housing (Kementrian PUPR) in 2019 shows that around 81 million millennials do not own houses. Government Regulation Number 25 of 2020 on the Implementation of Public Housing Savings, commonly called PP 25 Tapera 2020, is one of the government’s efforts to ensure that Indonesian people can afford houses. Tapera is a deposit of workers for house financing, which is refundable after the term expires. Immediately after enaction, there were many public responses regarding the ordinance. We investigate public sentiments commenting on the regulation and use Support Vector Machine (SVM) in the study since it has a good level of accuracy. It also requires labels and training data. To speed up labeling, we use the lexicon-based method. The issue in the lexicon-based lies in the dictionary component as the most significant factor. Therefore, it is possible to update the dictionary automatically by combining lexicon-based and SVM. The SVM approach can contribute to lexicon-based, and lexicon-based can help label datasets on SVM to produce good accuracy. The research begins with collecting data from Twitter, preprocessing raw and unstructured data into ready-to-use data, labeling the data with lexicon-based, weighting with TF-IDF, processing using SVM, and evaluating algorithm performance model with a confusion matrix. The results showed that the combination of lexicon-based and SVM worked well. Lexicon-based managed to label 519 tweet data. SVM managed to get an accuracy value of 81.73% with the RBF kernel function. Another test with a Sigmoid kernel attains the highest precision at 78.68%. The RBF kernel has the highest recall result with a value of 81.73%. Then, the F1-score for both the RBF kernel and Sigmoid is 79.60%.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124541026","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 : 2022-03-04DOI: 10.23917/khif.v8i1.15205
Rahman Indra Kesuma, Rivaldo Fernandes, Martin Clinton Tosima Manullang
- A new coronavirus variant known as n-Cov has emerged with a fast transmission rate. The World Health Organization (WHO) has declared the related disease or COVID-19 as a global pandemic that requires special handling. Many parties have shown efforts to reduce virus transmission by implementing health protocols and adapting a new normal lifestyle. Implementation of the health protocol creates new problems, especially in the health check at the main entrance. The officers in charge of measuring body temperature are at risk of getting infected by COVID. Such a measurement is prone to errors. This study proposed a solution to build an automatic gate system that worked based on the new normal health protocol. The system utilizes the MLX90614 contactless temperature sensor to probe body temperature. It applies deep learning implementing the Convolutional Neural Network (CNN) algorithm with the MobileNetV2 architecture as a determinant of the conditions of wearing face masks. The system is equipped with an IoT-based remote controller to control the gate. Experimental results prove that the system works well. Temperature measurement takes a response time of 20 seconds for each user with 99% accuracy for the sensor and masks classification model.
{"title":"Automatic Gate for Body Temperature Check and Masks Wearing Compliance Using an Embedded System and Deep Learning","authors":"Rahman Indra Kesuma, Rivaldo Fernandes, Martin Clinton Tosima Manullang","doi":"10.23917/khif.v8i1.15205","DOIUrl":"https://doi.org/10.23917/khif.v8i1.15205","url":null,"abstract":"- A new coronavirus variant known as n-Cov has emerged with a fast transmission rate. The World Health Organization (WHO) has declared the related disease or COVID-19 as a global pandemic that requires special handling. Many parties have shown efforts to reduce virus transmission by implementing health protocols and adapting a new normal lifestyle. Implementation of the health protocol creates new problems, especially in the health check at the main entrance. The officers in charge of measuring body temperature are at risk of getting infected by COVID. Such a measurement is prone to errors. This study proposed a solution to build an automatic gate system that worked based on the new normal health protocol. The system utilizes the MLX90614 contactless temperature sensor to probe body temperature. It applies deep learning implementing the Convolutional Neural Network (CNN) algorithm with the MobileNetV2 architecture as a determinant of the conditions of wearing face masks. The system is equipped with an IoT-based remote controller to control the gate. Experimental results prove that the system works well. Temperature measurement takes a response time of 20 seconds for each user with 99% accuracy for the sensor and masks classification model.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124742570","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 : 2022-03-04DOI: 10.23917/khif.v8i1.14036
S. Enggari, Sarjon Defit
An ideal couple should sustain the family's ark till the end of their life without divorce. This study aims at seeking the association between divorce and internet behavior of searching negative keywords. The study observes four keywords, which are porn, sex, gay, and lesbian. We collected keyword usage data from google trend reports and obtained divorce court figures from the Religion Court of Padang. We used the apriori algorithm to reveal the association between divorce and internet behavior observing individual keyword searches and in groups. We used the K-Means algorithm in classifying negative word searches and divorce trial numbers from a group of existing data. We also investigate the combination of the apriori algorithm and the K-Means method to detect divorce facts and the behavior of internet users. The combined method has been successful in revealing the positive association between divorce facts and the behavior of internet users.
{"title":"Divorce Fact Detection Based on Internet User Behavior Using Hybrid Systems with Combination of Apriori Algorithm and K-Means Method","authors":"S. Enggari, Sarjon Defit","doi":"10.23917/khif.v8i1.14036","DOIUrl":"https://doi.org/10.23917/khif.v8i1.14036","url":null,"abstract":"An ideal couple should sustain the family's ark till the end of their life without divorce. This study aims at seeking the association between divorce and internet behavior of searching negative keywords. The study observes four keywords, which are porn, sex, gay, and lesbian. We collected keyword usage data from google trend reports and obtained divorce court figures from the Religion Court of Padang. We used the apriori algorithm to reveal the association between divorce and internet behavior observing individual keyword searches and in groups. We used the K-Means algorithm in classifying negative word searches and divorce trial numbers from a group of existing data. We also investigate the combination of the apriori algorithm and the K-Means method to detect divorce facts and the behavior of internet users. The combined method has been successful in revealing the positive association between divorce facts and the behavior of internet users.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121782174","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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