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"Seiring dengan semakin banyaknya masyarakat yang menggunakan forum tanya-jawab kesehatan online, kebutuhan akan adanya sistem tanya-jawab kesehatan yang dapat berjalan secara otomatis semakin besar. Salah satu bagian penting dari sistem tanya-jawab kesehatan otomatis adalah question processing untuk mendapatkan informasi relevan dari pertanyaan pengguna. Terdapat beberapa task yang merupakan bagian dari question processing, di antaranya pengenalan pertanyaan, pengenalan entitas kesehatan, dan ekstraksi frase kunci. Pada penelitian ini, penulis mencoba tiga model untuk menyelesaikan ketiga task tersebut, yaitu IndoDistilBERT, IndoDistilBERT-BiLSTMs, dan IndoDistilBERT-BiLSTMs-CRF. Hasil eksperimen menunjukkan bahwa IndoDistilBERT-BiLSTMs-CRF memberikan hasil terbaik untuk task pengenalan pertanyaan dengan skor F1 sebesar 94,45%, lebih baik 3,15% dibandingkan baseline. Untuk task pengenalan entitas kesehatan, IndoDistilBERT-BiLSTMs memberikan hasil terbaik dengan skor F1 sebesar 73,78%, lebih baik 3,53% dibandingkan baseline. Untuk task ekstraksi frase kunci, model IndoDistilBERT-BiLSTMs memberikan hasil terbaik dengan skor F1 sebesar 77,42%, lebih baik 4,25% dibandingkan baseline. Selain itu, percobaan dengan pendekatan multi-task learning untuk menyelesaikan task pengenalan entitas kesehatan dan ekstraksi frase kunci belum mampu mengungguli hasil dari pendekatan single-task learning untuk masing-masing task.

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With the increasing number of people who use health question-and-answer online forum, the need for a health question-and-answer system that can run automatically is getting bigger. One of the important parts of an automated health question-and-answer system is question processing to get relevant information from user queries. There are several tasks which are part of question processing, including question recognition, medical entity recognition, and keyphrases extraction. On this research, we try three models to solve those three tasks, namely IndoDistilBERT, IndoDistilBERT-BiLSTMs, and IndoDistilBERT-BiLSTMs-CRF. Our experiment shows that IndoDistilBERT-BiLSTMs-CRF gives the best results for question recognition task with F1-score of 94,45%, 3,15% better than baseline. For medical entity recognition task, IndoDistilBERT-BiLSTMs gives the best results with F1-score of 73,78%, 3,53% better than baseline. For keyphrases extraction task, IndoDistilBERT-BiLSTMs gives the best results with F1-score of 77,42%, 4,25% better than baseline. Besides that, experiments with multi-task learning approach to solve medical entity recognition and keyphrases extraction have not been able to outperform the results of single-task learning approach for each task."

"Pandemi virus Corona yang telah masuk di Indonesia menyebabkan terciptanya program pembatasan sosial dengan tujuan untuk mengurangi penyebaran virus sehingga menciptakan suatu keadaan baru yang harus dijalani masyarakat yang disebut dengan New Normal. Dengan adanya New Normal ini membuat masyarakat Indonesia memiliki keinginan untuk memiliki alternatif untuk berkonsultasi kesehatan yaitu dengan telekonsultasi menggunakan aplikasi Halodoc. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi niat beralih penggunaan layanan konsultasi kesehatan offline ke telekonsultasi dengan studi kasus aplikasi Halodoc menggunakan teori push pull mooring (PPM). Penelitian ini menggunakan metode analisis secara kuantitatif dan kualitatif (mix method). Metode analisis secara kuantitatif dilakukan dengan cara menyebarkan kuesioner online yang menghasilkan sebanyak 538 data valid. Hasil data kuantitatif diolah dan dianalisis menggunakan metode CB-SEM dengan bantuan software AMOS 26 dan SPSS 25. Metode analisis secara kualitatif dilakukan dengan memberikan wawancara ke 5 responden. Hasil analisis data kuantitatif menunjukkan bahwa terdapat 9 hipotesis yang diterima dan 2 hipotesis yang ditolak. Variabel perceived severity, perceived susceptibility, perceived usefulness, perceived ease of use, economic feasibility, perceived informativeness, subjective norm, switching cost, dan trust berpengaruh terhadap niat beralih masyarakat dari konsultasi kesehatan di rumah sakit ke telekonsultasi. Sedangkan variabel inconvenience dan ubiquitous care tidak berpengaruh terhadap niat beralih. Semua variabel yang dianalisis memiliki efek yang tidak signifikan terhadap niat beralih. Peneliti berharap hasil penelitian ini dapat membantu Halodoc untuk menyesuaikan fitur telekonsultasinya agar meningkatkan niat beralih masyarakat Indonesia untuk menggunakan fitur telekonsultasi aplikasi Halodoc.

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The Coronavirus pandemic that has entered Indonesia has led to creation of a social restriction program to reduce the spread of the virus to create a new situation that must be endured by the community called the New Normal. With this New Normal, Indonesian people desire an alternative for health consultations, namely teleconsultation using the Halodoc application. This study analyses the factors that influence the intention to switch offline health consulting services to teleconsultation with a case study of the Halodoc application using the push-pull mooring (PPM) theory. This research uses quantitative and qualitative analysis methods (mix method). The quantitative analysis method was carried out by distributing online questionnaires, which resulted in 538 valid data. The results of quantitative data were processed and analyzed using the CB-SEM method with the help of AMOS 26 and SPSS 25 software. The qualitative analysis method was carried out by giving interviews with five respondents. The results of quantitative data analysis show that there are nine accepted hypotheses and two rejected hypotheses. Variables perceived severity, perceived susceptibility, perceived usefulness, perceived ease of use, economic feasibility, perceived informativeness, subjective norm, switching cost, and trust affects on people's intention to switch from health consultations in hospitals to teleconsultation. Meanwhile, inconvenience and ubiquitous care variables do not affect switching intentions. Furthermore, all variables analyzed had no significant effect on switching intention. The researcher hopes that this study's results can help Halodoc adjust its teleconsultation feature to increase the intention of switching Indonesian people to use the teleconsultation feature of the Halodoc application."

"Telemedicine adalah praktek kesehatan melalui aplikasi dengan memakai komunikasi audio, visual dan data, termasuk perawatan, diagnosis, konsultasi dan pengobatan serta pertukaran data medis jarak jauh. Berdasarkan hasil analisis sentimen pada aplikasi telemedicine, sering ditemukan adanya ketidakseimbangan data/imbalance data. Oleh karena itu perlu dilakukan pengembangan dengan memasukan teknik Imbalance Data dalam melakukan analisis sentimen agar mendapatkan hasil akurasi lebih baik dari penelitian sebelumnya. Tujuan penelitian ini adalah untuk mengidentifikasi penggunaan SVM-SMOTE dan EasyEnsemble dalam meningkatkan kinerja klasifikasi XGBoost pada imbalance data sentimen pada Telemedicine. Identifikasi dilakukan dengan memasukkan metode SVM-SMOTE dan EasyEnsemble Dalam Meningkatkan Kinerja Klasifikasi XGBoost menggunakan data yang diperoleh dari aplikasi Halodoc. Hasil penelitian menunjukkan bahwa penggunaan SVM SMOTE dan EasyEnsamble untuk dataset yang tidak seimbang dengan pembagian skema data 75% data training dan 25% data testing dapat meningkatkan kinerja klasifikasi XGBoost.  Hasil uji menggunakan data yang telah dilakukan balancing dengan SVM-SMOTE, EasyEnsamble dan kombinasi keduanya didapat model terbaik yang layak digunakan dalam melakukan peningkatan pada kinerja klasifikasi imbalance data sentimen pada aplikasi kesehatan. Setelah dilakukan balancing pada dataset, diperoleh nilai tertinggi AUC 0.9254 dan GMeans 0.9249, sedangkan hasil yang diperoleh dengan data set yang tidak seimbang, diperoleh nilai AUC 0.8577 dan GMeans 0.8480. Maka dapat disimpulkan bawah penggunaan SVM-SMOTE, EasyEnsemble atau kombinasi keduanya dapat meningkatkan kinerja klasifikasi pada XGBoost.

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Telemedicine is the practice of healthcare through applications using audio, visual, and data communication, including remote care, diagnosis, consultation, treatment, and the exchange of medical data. Sentiment analysis on telemedicine applications often experiences data imbalance issues. Therefore, it is necessary to implement Imbalance Data techniques into sentiment analysis to achieve better accuracy than previous studies. This research aims to identify the use of SVM-SMOTE and EasyEnsemble to enhance the performance of XGBoost classification on imbalanced sentiment data in telemedicine. The identification is carried out by applying SVM-SMOTE and EasyEnsemble methods to improve XGBoost classification performance using data obtained from the Halodoc application. The research results show that using SVM-SMOTE and EasyEnsemble for imbalanced datasets, with a data split of 75% for training and 25% for testing, can enhance XGBoost classification performance. Tests conducted with balanced data using SVM-SMOTE, EasyEnsemble, and the combination resulted in the best model suitable for improving classification performance on imbalanced sentiment data in health applications. After balancing the dataset, the highest AUC value achieved was 0.9254 and GMeans was 0.9249, whereas, with the imbalanced dataset, the AUC was 0.8577 and GMeans was 0.8480. Thus, it can be concluded that the use of SVM-SMOTE, EasyEnsemble, or the combination can improve classification performance in XGBoost."

"Dunia sedang dilanda pandemi virus COVID-19. Pemerintah di berbagai negara menetapkan protokol pembatasan untuk menghambat penyebaran virus COVID-19. Protokol tersebut membatasi akses ke pelayanan kesehatan, sistem pelayanan tatap muka di minimalisir. Hal tersebut memberikan dampak pada anak dengan autisme. Menurut Kaplan, pada anak dengan autisme gejala inti tidak bisa diobati dengan obat medis, akan tetapi dengan edukasi dan intervensi perilaku. Akan tetapi, sebelum pandemi, edukasi dan intervensi umumnya dilaksanakan dengan sistem tatap muka. Solusi dari masalah tersebut adalah penggunaan layanan kesehatan jarak jauh atau telehealth. Penelitian ini adalah penelitian yang membahas bagaimana penggunaan telehealth-telemedicine untuk intervensi pada kasus anak dengan autisme di masa pandemi COVID-19. Penelitian ini menggunakan metode literature review dengan menggunakan database Pubmed, Proquest, Sage Journal, dan Portal Garuda yang menghasilkan 9 artikel terinklusi. Penelitian terinklusi dilaksanakan pada rentang waktu dinyatakannya COVID-19 sebagai pandemi, yaitu tanggal 11 Maret 2020 hingga 1 Mei 2022. Hasil penelitian menunjukkan bahwa intervensi menghasilkan dampak pada anak dengan autisme berupa pengurangan perilaku yang ditargetkan, dan meningkatnya keterampilan. Selain itu pada cargeiver dijumpai peningkatan kepuasan dan persepsi mengenai pelayanan telehealth. Bagi penyedia layanan telehealth, dijumpai artikel yang menjelaskan tentang persepsi mengenai layanan telehealth tersebut. Berdasarkan temuan yang didapat, pelayanan telehealth di rekomendasikan bagi anak dengan autisme, para caregiver baik orang tua ataupun  bukan, penyedia jasa layanan juga di rekomendasikan jika ingin menyelenggarakan layanan telehealth berdasarkan temuan berupa tingkat kepuasan dan perkembangan yang muncul setelah intervensi. Sedangkan bagi pemerintah diharapkan mengembangkan kebijakan dan program terkait dengan telehealth terutama di masa pandemi, sehingga masyarakat yang membutuhkan tetap mendapat pelayanan yang dibutuhkan.

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The world is being hit by the COVID-19 pandemic. Governments in various countries set protocols for the spread of the COVID-19 virus. The protocol limits access to health services, the face-to-face service system is minimized. This has an impact on children with autism. According to Kaplan, children with autism symptoms cannot be treated with medical drugs, but with education and behavioral interventions. However, before the pandemic, education and intervention were generally carried out face-to-face. The solution to this problem is the use of remote health services or telehealth. This study is a study that discusses how telehealth is used for intervention in cases of children with autism during the COVID-19 pandemic. This study uses a literature review method using the Pubmed, Proquest, Sage Journal, and Garuda Portal databases which produces 9 included articles. Inclusive research was carried out during the time period that COVID-19 was declared a pandemic, namely March 11, 2020 to May 1, 2022. The results showed that the intervention had an impact on children with autism in the form of a reduction in targeted behavior and skills. In addition to the carrier, increased satisfaction and perception of telehealth services. For telehealth service providers, article explain the perception of the telehealth service. Based on the findings obtained, telehealth services are recommended for children with autism, caregivers, whether parents or not. Service providers are also recommended if they want to provide telehealth services based on the findings about the level of satisfaction and development that appears after the intervention. Meanwhile, the government is expected to develop policies and programs related to telehealth, especially during the pandemic, so that people in need can still receive the services they need."

"Pelaksanaan telekonsultasi dalam praktik telemedicine seharusnya perlu dikuti dengan adanya payung hukum yang dapat menaungi layanan tersebut. Hal ini disebabkan pelaksanaan layanan tersebut dapat menimbulkan suatu ketidakpastian dalam hubungan antara dokter dan pasien. Skripsi ini membahas tentang perbandingan pengaturan layanan telekonsultasi dalam praktik telemedicine di Indonesia dan Inggris. Penelitian ini dilakukan dengan menggunakan metode penelitian kualitatif dengan bentuk penelitian yuridis normatif. Pengaturan layanan telekonsultasi dalam praktik telemedicine di Indonesia hanya berdasarkan Peraturan Menteri Kesehatan Nomor 20 tahun 2019 Tentang Penyelenggaraan Pelayanan Telemedicine Antar Fasilitas Pelayanan Kesehatan yang belum mengatur secara khusus hubungan antara dokter dan pasien, sedangkan Inggris telah memiliki berbagai pengaturan tentang telemedicine khususnya layanan telekonsultasi yang diterbitkan oleh lembaga dan organisasi kesehatan yang berwenang di Inggris. Hasil dari perbandingan pengaturan layanan telekonsultasi dalam praktik telemedicine ini menunjukkan bahwa terdapat beberapa persamaan dan perbedaan yang signifikan antara Indonesia dan Inggris. Oleh karena itu, agar terdapat kepastian hukum dalam pelaksanaan layanan telekonsultasi pada praktik telemedicine di Indonesia, diharapkan Inggris dapat menjadi contoh bagi Indonesia agar mengatur secara jelas pelaksanaan layanan tersebut.

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The implementation of teleconsultation in the practice of telemedicine should be followed by the existence of a legal protection that can cover the service. This is because the implementation of these services can create an uncertainty in the relationship between doctors and patients. This thesis discusses the comparison of teleconsultation service arrangements in telemedicine practice in Indonesia and England. This research was conducted using a qualitative research method with a normative juridical research form. The regulation of teleconsultation services in telemedicine practice in Indonesia is only based on the Regulation of the Minister of Health Number 20 of 2019 concerning the Implementation of Telemedicine Services between Health Care Facilities which has not specifically regulated the relationship between doctors and patients, while England already has various regulations regarding telemedicine, especially teleconsultation services issued by England health authorities and organizations. The results of this comparison of teleconsulting service arrangements in telemedicine practice indicate that there are some significant similarities and differences between Indonesia and England. Therefore, so that there is legal certainty in the implementation of teleconsultation services in telemedicine practices in Indonesia, it is hoped that England can become an example for Indonesia to clearly regulate the implementation of these services."

"Skripsi ini menganalisis implementasi telemedicine dan regulatory sandbox di Indonesia berdasarkan Kepmenkes 1280/2023, UU 17/2023, dan Permenkes 20/2019, serta di Singapura berdasarkan Health Care Services Act (HCSA) dan National Telemedicine Guidelines (NTG). Skripsi ini disusun dengan metode penelitian doktrinal dengan tipe penelitian deskriptif-preskriptif, mengkaji telemedicine dan regulatory sandbox dengan membandingkan konsep, regulasi, dan isu hukum di Indonesia dan Singapura. Dalam hal ini, Singapura menggunakan sistem lisensi untuk telemedicine dibawah HCSA dengan NTG yang digunakan sebagai pedoman khusus. Sebelum sistem lisensi digunakan, Singapura menyelenggarakan regulatory sandbox LEAP hingga 2021, guna menyesuaikan HCSA dengan perkembangan teknologi kesehatan. Di Indonesia, telemedicine belum mempunyai pengaturan secara khusus. Meskipun sudah berkembang cukup baik melalui aplikasi berbasis smartphone yang diselenggarakan oleh health-tech company, hal ini belum sesuai dengan standar perangkat telemedicine. Kepmenkes 1280/2023 hanya mengakomodir telemedicine yang diselenggarakan melalui aplikasi berbasis smartphone, yang mana belum mendukung standarisasi telemedicine. Oleh karena itu, disarankan kepada Kementerian Kesehatan untuk mempercepat penyusunan regulasi yang sesuai dengan standar telemedicine melalui regulatory sandbox yang juga melibatkan pemangku kepentingan lain.

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This thesis analyzes the implementation of telemedicine and regulatory sandboxes in Indonesia based on Kepmenkes 1280/2023, UU 17/2023, and Permenkes 20/2019, as well as in Singapore based on the Health Care Services Act (HCSA) and National Telemedicine Guidelines (NTG). The research employs a doctrinal methodology with a descriptive-prescriptive approach, examining telemedicine and regulatory sandboxes by comparing concepts, regulations, and legal issues in Indonesia and Singapore. In this context, Singapore uses a licensing system for telemedicine under the HCSA with NTG as specific guidelines. Before the licensing system was implemented, Singapore conducted the LEAP regulatory sandbox until 2021 to adapt the HCSA to health technology developments. In Indonesia, telemedicine does not yet have specific regulations. Although it has developed quite well through smartphone-based applications run by health-tech companies, this does not meet telemedicine equipment standards. Kepmenkes 1280/2023 only accommodates telemedicine conducted through smartphone applications, which does not support telemedicine standardization. Therefore, it is recommended that the Ministry of Health expedite the formulation of regulations that meet telemedicine standards through regulatory sandboxes involving other stakeholders."

"The aims and scope of the second edition are unchanged from the first edition. The major market is in health informatics education. The three part format, which covers principles of health interoperability, HL7 and interchange formats, and SNOMED CT and clinical terminology, works well. In the US, The ONC (Office of the National Coordinator for Health Information Technology) has estimated that the HITECH stimulus will create more than 50,000 new jobs for health informatics professionals, who need to be educated."

"Pervasive healthcare is an emerging research discipline, focusing on the development and application of pervasive and ubiquitous computing technology for healthcare and wellness. Pervasive healthcare seeks to respond to a variety of pressures on healthcare systems, including the increased incidence of life-style related and chronic diseases, emerging consumerism in healthcare, need for empowering patients and relatives for self-care and management of their health, and need to provide seamless access for healthcare services, independent of time and place. Pervasive healthcare may be defined from two perspectives. First, it is the development and application of pervasive computing (or ubiquitous computing, ambient intelligence) technologies for healthcare, health and wellness management. Second, it seeks to make healthcare available to anyone, anytime, and anywhere by removing locational, time and other restraints while increasing both the coverage and quality of healthcare. This book proposes to define the emerging area of pervasive health and introduce key management principles, most especially knowledge management, its tools, techniques and technologies. In addition, the book takes a socio-technical, patient-centric approach which serves to emphasize the importance of a key triumvirate in healthcare management namely, the focus on people, process and technology. Last but not least the book discusses in detail a specific example of pervasive health, namely the potential use of a wireless technology solution in the monitoring of diabetic patients."