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All Journal PRODUCTUM : Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) Biomolecular and Health Science Journal Indonesian Journal of Electrical Engineering and Computer Science
Sofiah, Amila
Department Of Engineering, Faculty Of Advanced Technology And Multidisipline, Universitas Airlangga, Surabaya
Arts Humanities Biochemistry, Genetics & Molecular Biology Immunology & microbiology Medicine & Pharmacology Neuroscience Public Health

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Maximizing Millennial Students Role in Combating COVID-19 Hoaxes and Myths Astri Dewayani; Euvanggelia Dwilda Ferdinandus; Rizki Putra Prastio; Indah Fahmiyah; Amila Sofiah; Rodik Wahyu Indrawan; Mochammad Nurul; Gagas Gayuh Aji; Nanda Rachmad Putra Gofur; Siti Khaerunnisa; Dewi Sriani; Yankel Sena
Biomolecular and Health Science Journal Vol. 4 No. 1 (2021): Biomolecular and Health Science Journal
Publisher : Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/bhsj.v4i1.26910

Abstract

Introduction: Since the outbreak of Corona Disease-19 (COVID-19) spreads all over the world, various ways of health attempts have been conducted. However, overflowed information intertwines with mis/disinformation could raise public anxiety and stigma-related diseases. We aimed to assess the help of the young generation of millennials and Gen-Z whom are active college students in debunking hoaxes and myths of COVID-19 into their community.Method: The selected students were given a short course on COVID-19 basic information, prevention, and circulated myths. Later, they become ambassadors and actively educated via offline and online platforms. The impact of outspread information on audiences was investigated through a qualitative survey.Result: The knowledge of students were measured by pre- and post-test within the short course. Prior knowledge showed the least understanding part was prevention and myth of COVID-19. There was a significant improvement of knowledge in post-test after receiving seminar (p=0.0002). There were 97 respondents who filled the online survey that predominantly in young adulthood age. Respondent's insight was enhanced and they likely intend to spread the actual information to their surroundings.Conclusion: Appointing student as the spokesperson for health education can raise their social responsibility. Clarifying misinformation and health behaviour could be more influential within the same sharing community. In addition, the use of various online platforms could efficiently reach massive target, especially young ages.
The application of instrumentation system on a contactless robotic triage assistant to detect early transmission on a COVID-19 suspect Niko Azhari Hidayat; Prisma Megantoro; Abdufattah Yurianta; Amila Sofiah; Shofa Aulia Aldhama; Yutika Amelia Effendi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1334-1344

Abstract

This article discusses the instrumentation system of airlangga robotic triage assistant version 1 (ARTA-1), a robot used as a contact-free triage assistant for Coronavirus disease (COVID-19) suspects. The triage process consists of automatic vital signs check-up as well as the suspect’s anamnesis that in turns will determine whether the suspect will get a specific care or not. Measurements of a suspect’s vital conditions, i.e. temperature, height, and weight, are carried out with sensors integrated with the Arduino boards, while a touch-free, hand gesture questions and answers is carried out to complete anamnesis process. A portable document format (PDF) format of the triage report, which recommends what to do to the suspect, will then be automatically generated and emailed to a designated medical staff.
Transformasi analisis konfigurasi desain smart office desk untuk kebutuhan work from home Irna Arlianti; Amila Sofiah; Hertina Susandari
Productum: Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) Vol 6, No 1 (2023)
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24821/productum.v6i1.6206

Abstract

The work from home concept has become a common work system to reduce the rate of spread of COVID-19 cases. The adjustment of the portion of working in the office only below 50% in the next few years. Unfortunately, the impact of working from home is the flexibility of working time. There is no dividing wall between work time and personal time. Increased workloads and work delays often occur which ultimately affect the performance of workers. The work desk design development could be alternative solution. Referring to the trend of furniture design in the next few years, smart furniture design is becoming a trend that is in demand and needed to improve the quality of life. Smart furniture includes the application of intelligent systems / controllers to furniture designs in the form of sensors and actuators that are tailored to user needs. Research was conducted on the configuration analysis of smart office desk designs for the needs of working at home. The results are recommendations for the layout of user detector on the desk, the process of integrating the desk and the user detector, the final design, the design requirements and objectives in the development of a smart office desk.
Predicting vulnerability for brain tumor: data-driven approach utilizing machine learning Effendi, Yutika Amelia; Sofiah, Amila; Hidayat, Niko Azhari; Ebrie, Awol Seid; Hamzah, Zainy
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i3.pp1579-1589

Abstract

Brain tumors, whether benign or malignant, present a complex and multifaceted challenge in healthcare, affecting individuals across various age groups. Predicting the vulnerability of brain tumors using health risk factors and symptoms is crucial, yet there have been limited research studies, particularly those integrating artificial intelligence (AI) technology. This research explores machine learning models such as support vector machines (SVMs), multi-layer perceptrons (MLPs), and logistic regression (LR) for the early detection of brain tumors. Evaluation metrics, including accuracy, precision, recall, and F1-score, are employed to assess model performance. The results indicate that the SVM outperforms other models, providing a robust foundation for predictive accuracy. To enhance accessibility and usability, the research also integrates these models into a mobile application predictor. The application is beneficial for assisting individuals in early detection by identifying potential risk factors and symptoms that may lead to a brain tumor. In conclusion, the integration of machine learning through a mobile application represents a transformative approach to personalized healthcare. By empowering individuals with cutting-edge technology, this research strives to enhance early detection and decision-making regarding potential brain tumor risks and symptoms, ultimately contributing to improved patient outcomes and quality of life.
Co-Authors Abdufattah Yurianta Aldhama, Shofa Aulia Astri Dewayani Ebrie, Awol Seid Effendi, Yutika Amelia Ferdinandus, Euvanggelia Dwilda Gagas Gayuh Aji, Gagas Gayuh Hamzah, Zainy Hertina Susandari Hidayat, Niko Azhari Indah Fahmiyah Irna Arlianti Nanda Rachmad Putra Gofur Nurul, Mochammad Prisma Megantoro Rizki Putra Prastio Rodik Wahyu Indrawan Siti Khaerunnisa Sriani, Dewi Yankel Sena