Pub Date : 2022-01-24DOI: 10.25139/inform.v7i1.4269
Anang Widodo, S.Kom., M.T, Muslim Alamsyah
The spread of COVID-19, which is getting faster every day, has made people wary. If residents suffer from the symptoms and risks of COVID-19, they are afraid and ashamed because they feel ostracized by their neighbors, relatives, and families. It is a shame and fear of reporting that causes the transmission of COVID-19 to accelerate. Therefore, it is necessary to create a system that can answer the problem, namely a system that can detect first aid symptoms and risks of COVID-19 suffered by residents, so that residents know their health status without checking the health of the COVID-19 task force in each area. The system is made by reading the location of residents who report their health to know where they are and their health status. A method for reading the location of system users based on IP addresses is called IP Geolocation, which stands for Internet Protocol Geolocation. The determination of the health status of residents is in the category of Negative COVID-19, ODR, ODP, PDP, or Positive COVID-19 using the Fuzzy Inference System (FIS) method. The IP Geolocation and FIS results will be displayed on a map (google maps). Implementing this system will make it easier for the Government to monitor the spread of COVID-19 based on public reports and information. By testing using the black box method based on partition equivalence with seven facilities in the system, one mistake makes the facility a weakness of IP Geolocation.
{"title":"Mapping COVID-19 in a Region Using IP Geolocation and Fuzzy Inference System","authors":"Anang Widodo, S.Kom., M.T, Muslim Alamsyah","doi":"10.25139/inform.v7i1.4269","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4269","url":null,"abstract":"The spread of COVID-19, which is getting faster every day, has made people wary. If residents suffer from the symptoms and risks of COVID-19, they are afraid and ashamed because they feel ostracized by their neighbors, relatives, and families. It is a shame and fear of reporting that causes the transmission of COVID-19 to accelerate. Therefore, it is necessary to create a system that can answer the problem, namely a system that can detect first aid symptoms and risks of COVID-19 suffered by residents, so that residents know their health status without checking the health of the COVID-19 task force in each area. The system is made by reading the location of residents who report their health to know where they are and their health status. A method for reading the location of system users based on IP addresses is called IP Geolocation, which stands for Internet Protocol Geolocation. The determination of the health status of residents is in the category of Negative COVID-19, ODR, ODP, PDP, or Positive COVID-19 using the Fuzzy Inference System (FIS) method. The IP Geolocation and FIS results will be displayed on a map (google maps). Implementing this system will make it easier for the Government to monitor the spread of COVID-19 based on public reports and information. By testing using the black box method based on partition equivalence with seven facilities in the system, one mistake makes the facility a weakness of IP Geolocation.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87002561","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 : 2022-01-23DOI: 10.25139/inform.v7i1.4284
S. W. Kuseh, Henry Nunoo‐Mensah, G. S. Klogo, E. T. Tchao
Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms "Trust aggregation approaches in IoT", and "Trust computation in SIoT" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.
社交物联网(Social Internet of Things, SIoT)是将社交网络概念整合到物联网中，以增强物联网对象和用户之间的社交互动。预计SIoT将提供充分的服务选择和发现。在沟通网络中讨论社会概念时，信任是一个必不可少的因素。信任通常导致双方(即委托人和受托人)之间的相互关系，双方都享有互惠互利。对于安全的社会关系，信任管理(Trust management, TM)是SIoT的一个重要特征。这项工作的主要目的是对SIoT可用的信任管理建议/方案进行全面审查。本文选择了四种用于信任管理的主要信任计算算法，并对它们进行了详细的研究。在IEEE Xplore、Scopus、ResearchGate和Google Scholar数据库中检索了包含“物联网中的信任聚合方法”和“SIoT中的信任计算”这两个术语的文章，并特别强调了2018年至2021年间发表的作品。本文还讨论了每种TM技术的优缺点、信任度量/特征、贡献以及文献中最先进的SIoT TM建议的局限性。文章进一步提出了SIoT领域的开放性问题和可能的研究方向。
{"title":"A Survey of Trust Management Schemes for Social Internet of Things","authors":"S. W. Kuseh, Henry Nunoo‐Mensah, G. S. Klogo, E. T. Tchao","doi":"10.25139/inform.v7i1.4284","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4284","url":null,"abstract":"Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms \"Trust aggregation approaches in IoT\", and \"Trust computation in SIoT\" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89863045","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 : 2022-01-22DOI: 10.25139/inform.v7i1.4367
Heny Yuniarti, R. Sigit, Amran Zamzami
The development of technological advances in the health sector in the last decades has grown very rapidly. Currently, most people do not receive routine medical check-ups because of the long lines of patients and the expensive rates they must pay to see a specialist doctor. This causes many people to ignore the importance of routine health checks as recommended by the National Health Agency. The purpose of this research is to make a device that can perform routine checks independently at home, using an Arduino microcontroller for checking cholesterol, uric acid, obesity, and hypoxia. This tool has several sensors, namely Ultrasonic & Load Cell sensors to measure weight and height, which are used to detect obesity through the BMI table. In addition, there is a Pulse and Oxygen in Blood Sensor (SPO2) sensor to detect heart rate and oxygen saturation to detect hypoxia using the fuzzy logic method. Cholesterol and uric acid examination using the Electrode Based biosensor method with a digital detection device (amperometric biosensor). Testing the Tsukamoto fuzzy logic method system obtained a data accuracy value of 100%, following the rules set for classifying hypoxic diseases. The trial phase was carried out as many as 10 trials, where 90% of patients did not experience hypoxia, and 10% had mild hypoxia. The results of testing the BMI table method system for obesity obtained a data accuracy value of 100% according to the calculation of the BMI calculator. In phase 10 trials, 30% of patients were lean, 50% obese, and 20% obese. The system test results use a range of values, each with a data accuracy value of 100% according to the classification of cholesterol and uric acid levels. Ten trials showed that 70% of patients were in normal condition, 20% of patients with low cholesterol, and 10% of patients were in high limits. As for gout, 70% of patients are in normal condition, and 30% of patients are in high uric acid condition.
{"title":"Implementation System of Health Care Kiosk for Detecting Cholesterol Disease, Uric Acid, Obesity and Hypoxia","authors":"Heny Yuniarti, R. Sigit, Amran Zamzami","doi":"10.25139/inform.v7i1.4367","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4367","url":null,"abstract":"The development of technological advances in the health sector in the last decades has grown very rapidly. Currently, most people do not receive routine medical check-ups because of the long lines of patients and the expensive rates they must pay to see a specialist doctor. This causes many people to ignore the importance of routine health checks as recommended by the National Health Agency. The purpose of this research is to make a device that can perform routine checks independently at home, using an Arduino microcontroller for checking cholesterol, uric acid, obesity, and hypoxia. This tool has several sensors, namely Ultrasonic & Load Cell sensors to measure weight and height, which are used to detect obesity through the BMI table. In addition, there is a Pulse and Oxygen in Blood Sensor (SPO2) sensor to detect heart rate and oxygen saturation to detect hypoxia using the fuzzy logic method. Cholesterol and uric acid examination using the Electrode Based biosensor method with a digital detection device (amperometric biosensor). Testing the Tsukamoto fuzzy logic method system obtained a data accuracy value of 100%, following the rules set for classifying hypoxic diseases. The trial phase was carried out as many as 10 trials, where 90% of patients did not experience hypoxia, and 10% had mild hypoxia. The results of testing the BMI table method system for obesity obtained a data accuracy value of 100% according to the calculation of the BMI calculator. In phase 10 trials, 30% of patients were lean, 50% obese, and 20% obese. The system test results use a range of values, each with a data accuracy value of 100% according to the classification of cholesterol and uric acid levels. Ten trials showed that 70% of patients were in normal condition, 20% of patients with low cholesterol, and 10% of patients were in high limits. As for gout, 70% of patients are in normal condition, and 30% of patients are in high uric acid condition.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"42 168 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83271106","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 : 2022-01-20DOI: 10.25139/inform.v7i1.4281
Yoyon Arie Budi Suprio, M. Rizky Maulana
Many educational institutions have been forced to adapt how they present the teaching and learning process, including the creation of appropriate learning media due to the current Covid-19 pandemic. This is accomplished through the development of an integrated online learning system known as E-Learning. Aside from all of the benefits and positive outcomes that E-Learning can give, there are also drawbacks to student information security, such as assignment theft, piracy of E-Learning, the misuse of passwords by irresponsible students, and other problems. To anticipate this, the researcher intended to group students' awareness of their respective E-Learning information security by using the Fuzzy C Means method. Fuzzy C Means uses a fuzzy grouping model so that data can be members of all classes or clusters formed with different degrees or levels of membership between 0 to 1. The sample used to represent the population is 20 students of STIKOM PGRI Banyuwangi, Indonesia. The results obtained are to find out how well the grouping of student awareness clusters on E-Learning information security. There are 3 clusters of student E-Learning information security awareness. Cluster 1 consists of students with high awareness, cluster 2 contains categories of students with low awareness, and the third cluster consists of students with moderate awareness.
由于当前的Covid-19大流行，许多教育机构被迫调整其教学过程的呈现方式，包括创建适当的学习媒体。这是通过开发一种称为E-Learning的综合在线学习系统来实现的。除了电子学习可以带来的所有好处和积极成果之外，学生信息安全也存在缺点，例如作业盗窃，电子学习盗版，不负责任的学生滥用密码以及其他问题。为了预测这一点，研究人员打算通过使用模糊C均值方法对学生对各自电子学习信息安全的认识进行分组。Fuzzy C Means采用模糊分组模型，使得数据可以是0 ~ 1之间不同隶属度或等级的所有类或聚类的成员。用于代表人口的样本是印度尼西亚班尤旺吉STIKOM PGRI的20名学生。所得的结果是找出学生对E-Learning信息安全意识集群的分组效果如何。学生E-Learning信息安全意识有3个集群。聚类1由高意识的学生组成，聚类2包含低意识的学生类别，第三类由中等意识的学生组成。
{"title":"Grouping Student Awareness on Security Of E-Learning Information Using Fuzzy C-Means Method","authors":"Yoyon Arie Budi Suprio, M. Rizky Maulana","doi":"10.25139/inform.v7i1.4281","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4281","url":null,"abstract":"Many educational institutions have been forced to adapt how they present the teaching and learning process, including the creation of appropriate learning media due to the current Covid-19 pandemic. This is accomplished through the development of an integrated online learning system known as E-Learning. Aside from all of the benefits and positive outcomes that E-Learning can give, there are also drawbacks to student information security, such as assignment theft, piracy of E-Learning, the misuse of passwords by irresponsible students, and other problems. To anticipate this, the researcher intended to group students' awareness of their respective E-Learning information security by using the Fuzzy C Means method. Fuzzy C Means uses a fuzzy grouping model so that data can be members of all classes or clusters formed with different degrees or levels of membership between 0 to 1. The sample used to represent the population is 20 students of STIKOM PGRI Banyuwangi, Indonesia. The results obtained are to find out how well the grouping of student awareness clusters on E-Learning information security. There are 3 clusters of student E-Learning information security awareness. Cluster 1 consists of students with high awareness, cluster 2 contains categories of students with low awareness, and the third cluster consists of students with moderate awareness.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89339757","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 : 2022-01-20DOI: 10.25139/inform.v7i1.4282
Prince Awuah Baffour, Henry Nunoo‐Mensah, Eliel Keelson, Benjamin Kommey
Facial emotion recognition (FER) forms part of affective computing, where computers are trained to recognize human emotion from human expressions. Facial Emotion Recognition is very necessary for bridging the communication gap between humans and computers because facial expressions are a form of communication that transmits 55% of a person's emotional and mental state in a total face-to-face communication spectrum. Breakthroughs in this field also make computer systems (robotic systems) better serve or interact with humans. Research has far advanced for this cause, and Deep learning is at its heart. This paper systematically discusses state-of-the-art deep learning architectures and algorithms for facial emotion detection and recognition. The paper also reveals the dominance of CNN architectures over other known architectures like RNNs and SVMs, highlighting the contributions, model performance, and limitations of the reviewed state-of-the-art. It further identifies available opportunities and open issues worth considering by various FER research in the future. This paper will also discover how computation power and availability of large facial emotion datasets have also limited the pace of progress.
{"title":"A Survey on Deep Learning Algorithms in Facial Emotion Detection and Recognition","authors":"Prince Awuah Baffour, Henry Nunoo‐Mensah, Eliel Keelson, Benjamin Kommey","doi":"10.25139/inform.v7i1.4282","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4282","url":null,"abstract":"Facial emotion recognition (FER) forms part of affective computing, where computers are trained to recognize human emotion from human expressions. Facial Emotion Recognition is very necessary for bridging the communication gap between humans and computers because facial expressions are a form of communication that transmits 55% of a person's emotional and mental state in a total face-to-face communication spectrum. Breakthroughs in this field also make computer systems (robotic systems) better serve or interact with humans. Research has far advanced for this cause, and Deep learning is at its heart. This paper systematically discusses state-of-the-art deep learning architectures and algorithms for facial emotion detection and recognition. The paper also reveals the dominance of CNN architectures over other known architectures like RNNs and SVMs, highlighting the contributions, model performance, and limitations of the reviewed state-of-the-art. It further identifies available opportunities and open issues worth considering by various FER research in the future. This paper will also discover how computation power and availability of large facial emotion datasets have also limited the pace of progress.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"117 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82159298","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 : 2022-01-07DOI: 10.25139/inform.v7i1.4163
D. Suprianto, Muhammad Taufik Prayitno, Luqman Affandi
Coffee is a major commodity of the Indonesian plantation industry. One of Indonesia's lack of competitiveness in the international market is the low quality of coffee beans. This is because traditional farmers still use conventional methods for drying. The undried coffee cherries can damage the quality of coffee beans. Based on these problems, the researchers made a Smart Greenhouse dryer using the Internet of Things Platform. The Internet of Things is used to allow it to be monitored remotely in real-time. Temperature and humidity data in the greenhouse will be analyzed using a fuzzy algorithm. Actuators use the fuzzy output results to control the temperature and humidity of the greenhouse to reach the ideal drying conditions. The perfect drying temperature enables coffee cherries to achieve a moisture content of 12.55% within 14 days. Data on average temperature and humidity per day will be recorded and calculated to determine when the coffee cherries are ready for the next stage. The system can also calculate estimated days based on moisture content. With this, the drying of coffee cherries will be optimal and get the water content of the Indonesian National Standard to increase the quality and selling price of the coffee beans. The results show that Smart Greenhouse can be controlled remotely via the website. The integrated Sugeno Fuzzy algorithm keeps the greenhouse at the ideal drying temperature. Test results show that Smart Greenhouse can reduce the water content of coffee cherries 7.4 days more efficiently than conventional drying methods.
{"title":"Smart Greenhouse Coffee Dryer with Fuzzy Algorithm on Internet of Things Platform","authors":"D. Suprianto, Muhammad Taufik Prayitno, Luqman Affandi","doi":"10.25139/inform.v7i1.4163","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4163","url":null,"abstract":"Coffee is a major commodity of the Indonesian plantation industry. One of Indonesia's lack of competitiveness in the international market is the low quality of coffee beans. This is because traditional farmers still use conventional methods for drying. The undried coffee cherries can damage the quality of coffee beans. Based on these problems, the researchers made a Smart Greenhouse dryer using the Internet of Things Platform. The Internet of Things is used to allow it to be monitored remotely in real-time. Temperature and humidity data in the greenhouse will be analyzed using a fuzzy algorithm. Actuators use the fuzzy output results to control the temperature and humidity of the greenhouse to reach the ideal drying conditions. The perfect drying temperature enables coffee cherries to achieve a moisture content of 12.55% within 14 days. Data on average temperature and humidity per day will be recorded and calculated to determine when the coffee cherries are ready for the next stage. The system can also calculate estimated days based on moisture content. With this, the drying of coffee cherries will be optimal and get the water content of the Indonesian National Standard to increase the quality and selling price of the coffee beans. The results show that Smart Greenhouse can be controlled remotely via the website. The integrated Sugeno Fuzzy algorithm keeps the greenhouse at the ideal drying temperature. Test results show that Smart Greenhouse can reduce the water content of coffee cherries 7.4 days more efficiently than conventional drying methods.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86203090","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 : 2022-01-07DOI: 10.25139/inform.v7i1.4231
D. Suprianto, Ermi Pristiya, Arief Prasetyo
Chicken consumption is one of the high-value economic sectors. In order to harvest chickens optimally, it is necessary to maintain the temperature and humidity of the chicken coop regularly. The application of IoT to monitor the temperature and humidity of the chicken coop is significant. Therefore, an automatic temperature-humidity control system based on decisions made using the Sugeno fuzzy method is also needed. Smart chicken coop with the fuzzy algorithm on platform internet of things can be used as an alternative process temperature and humidity control automatically replace conventional method. Based on the results of the tests, this system can control temperature and humidity at 30.3°C, which is the ideal temperature for the growing time of broilers.
{"title":"Smart Chicken Coop Ecosystem for Optimal Growth of Broiler Chickens Using Fuzzy on IoT","authors":"D. Suprianto, Ermi Pristiya, Arief Prasetyo","doi":"10.25139/inform.v7i1.4231","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4231","url":null,"abstract":"Chicken consumption is one of the high-value economic sectors. In order to harvest chickens optimally, it is necessary to maintain the temperature and humidity of the chicken coop regularly. The application of IoT to monitor the temperature and humidity of the chicken coop is significant. Therefore, an automatic temperature-humidity control system based on decisions made using the Sugeno fuzzy method is also needed. Smart chicken coop with the fuzzy algorithm on platform internet of things can be used as an alternative process temperature and humidity control automatically replace conventional method. Based on the results of the tests, this system can control temperature and humidity at 30.3°C, which is the ideal temperature for the growing time of broilers.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79053405","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 lot of the company's business activities failed due to not adapting to user needs and technological developments. Previous studies show that there is no way to implement UX guidelines that explain the specific user needs for the UX of e-commerce systems. Therefore, we need a way of implementing UX for e-commerce websites. We used usability parameters in ISO 9241-11, namely effectiveness, efficiency, and satisfaction, to measure the system's usability and then conduct an interview to follow up the result. This research identifies how e-commerce companies implement UX best practices for their systems that can be used for other people who want to design their e-commerce applications.
{"title":"Using ISO 9241-11 To Identify How E-Commerce Companies Applied UX Guidelines","authors":"Fauza Adelma Syafrizal, Rahmat Izwan Heroza, Ermatita, Mgs. Afriyan Firdaus, Pacu Putra, Lovinta Happy Atrinawati, Monterico Adrian","doi":"10.25139/inform.v7i1.4261","DOIUrl":"https://doi.org/10.25139/inform.v7i1.4261","url":null,"abstract":"A lot of the company's business activities failed due to not adapting to user needs and technological developments. Previous studies show that there is no way to implement UX guidelines that explain the specific user needs for the UX of e-commerce systems. Therefore, we need a way of implementing UX for e-commerce websites. We used usability parameters in ISO 9241-11, namely effectiveness, efficiency, and satisfaction, to measure the system's usability and then conduct an interview to follow up the result. This research identifies how e-commerce companies implement UX best practices for their systems that can be used for other people who want to design their e-commerce applications.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"290 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76999727","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 : 2021-08-10DOI: 10.25139/inform.v6i2.4081
E. Puspitarini, A. Maukar, Fitri Marisa, Kurniawan Wahyu Haryanto, Teguh Pradana
Massive Open Online Course (MOOC) is defined as an online open-access course available to an unlimited number of students from any location. These online lectures provide convenience and timeliness for students, enabling them to study from anywhere and anytime. With the demand for online learning, universities require a business design model for the MOOC application that will be used as online learning with the hope that it can be carried out continuously and in the long term to support the existence of online learning. The online learning process in Indonesian education in the era of the Industrial Revolution 4.0 and the implementation of the Merdeka Belajar Kampus Merdeka (MBKM). This research aims to create a business model for the implementation of the MOOC application as an open online lecture. The stages of this research method include a literature review study related to business models by the world's leading MOOC platforms, including Coursera, EdX, Udacity, and Udemy. Then analyzed and made a business model using the nine-block canvas method and implemented the MOOC application in the context of the MBKM Curriculum.
{"title":"Business Models Canvas of MOOCs: an Investigation of Sustainable Practices for MOOC Universities","authors":"E. Puspitarini, A. Maukar, Fitri Marisa, Kurniawan Wahyu Haryanto, Teguh Pradana","doi":"10.25139/inform.v6i2.4081","DOIUrl":"https://doi.org/10.25139/inform.v6i2.4081","url":null,"abstract":"Massive Open Online Course (MOOC) is defined as an online open-access course available to an unlimited number of students from any location. These online lectures provide convenience and timeliness for students, enabling them to study from anywhere and anytime. With the demand for online learning, universities require a business design model for the MOOC application that will be used as online learning with the hope that it can be carried out continuously and in the long term to support the existence of online learning. The online learning process in Indonesian education in the era of the Industrial Revolution 4.0 and the implementation of the Merdeka Belajar Kampus Merdeka (MBKM). This research aims to create a business model for the implementation of the MOOC application as an open online lecture. The stages of this research method include a literature review study related to business models by the world's leading MOOC platforms, including Coursera, EdX, Udacity, and Udemy. Then analyzed and made a business model using the nine-block canvas method and implemented the MOOC application in the context of the MBKM Curriculum.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81848781","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 : 2021-07-31DOI: 10.25139/inform.v6i2.4000
Yudi Kristyawan, Zahid Faizal Kholil
Water dispensers are electronic devices that are widely available in households and offices. In general, water dispensers use faucets to drain water. During the pandemic, many people avoid touching equipment used by many people. Various ways have been done so that the water dispenser can be operated automatically without touching the faucet. Previous research on water dispensers was only applied to one type of water. This study aims to make an automatic water dispenser without touching the faucet used for two types of water, namely hot water or cold water. This research is based on hand gesture detection to choose hot water or cold water. The APDS-9960 gesture sensor detects hand movements to select hot or cold water, and then a servo motor is used to open the water faucet. After that, the position of the glass is validated by the ultrasonic sensor HC-SR04, and water will flow for 30 seconds into the glass. The entire input and output process is controlled using Arduino. The results show that this automatic water dispenser can detect hand gestures at a maximum distance of 15 cm with a hand movement speed of 2 to 3.7 seconds. This automatic water dispenser can detect three kinds of glass, namely ceramic, clear glass, and plastic, at a distance of 1 to 3 cm, and the volume of water flowing for 30 seconds is 240 ml.
{"title":"Automatic Water Dispenser Based on Hand Gesture Detection Using Arduino","authors":"Yudi Kristyawan, Zahid Faizal Kholil","doi":"10.25139/inform.v6i2.4000","DOIUrl":"https://doi.org/10.25139/inform.v6i2.4000","url":null,"abstract":"Water dispensers are electronic devices that are widely available in households and offices. In general, water dispensers use faucets to drain water. During the pandemic, many people avoid touching equipment used by many people. Various ways have been done so that the water dispenser can be operated automatically without touching the faucet. Previous research on water dispensers was only applied to one type of water. This study aims to make an automatic water dispenser without touching the faucet used for two types of water, namely hot water or cold water. This research is based on hand gesture detection to choose hot water or cold water. The APDS-9960 gesture sensor detects hand movements to select hot or cold water, and then a servo motor is used to open the water faucet. After that, the position of the glass is validated by the ultrasonic sensor HC-SR04, and water will flow for 30 seconds into the glass. The entire input and output process is controlled using Arduino. The results show that this automatic water dispenser can detect hand gestures at a maximum distance of 15 cm with a hand movement speed of 2 to 3.7 seconds. This automatic water dispenser can detect three kinds of glass, namely ceramic, clear glass, and plastic, at a distance of 1 to 3 cm, and the volume of water flowing for 30 seconds is 240 ml.","PeriodicalId":52760,"journal":{"name":"Inform Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84982249","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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