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"Kondisi geografis Indonesia yang dilalui The Ring of Fire dan memiliki garis pantai sepanjang 95.181 KM (Pregiwati, 2019) menyebabkan Indonesia rawan akan bencana alam berupa letusan gunung api, tsunami, dan gempa bumi. Oleh sebab itu, dibutuhkan suatu early warning system (EWS) yang dapat memberikan informasi pemantauan kejadian alam di wilayah Indonesia agar masyarakat lebih siaga dalam menghadapi bencana alam. Sayangnya, EWS yang telah dimiliki Indonesia memiliki rating yang masih cukup rendah. Keluhan pengguna yang disampaikan melalui ulasan aplikasi pada App Store menunjukkan bahwa adanya kekurangan pada fitur aplikasi, desain antarmuka sistem, serta alur informasi yang tidak jelas. Penelitian ini bertujuan untuk merancang desain interaksi aplikasi mobile EWS bencana alam sebagai pengembangan dari aplikasi sebelumnya yang dapat mengatasi keluhan-keluhan pengguna. Dalam pengembangan desain interaksi, digunakan metode design thinking. Dalam implementasinya, metode design thinking terdiri atas lima proses utama, yakni define, needfinding & synthesis, ideation, prototyping, dan testing. Dalam tahap define, dilakukan wawancara dengan responden yang ahli di bidang early warning system dan bencana alam Indonesia. Selanjutnya, pada tahap needfinding & synthesis, dilakukan wawancara dengan responden umum. Dari proses-proses tersebut, penelitian ini akan menghasilkan analisis fitur dan kebutuhan pengguna, stakeholder EWS di Indonesia, rumusan desain interaksi, serta penilaian evaluasi kegunaan (usability) dari rumusan desain yang telah dibuat. Fitur-fitur yang dikembangkan dalam aplikasi ini antara lain fitur geolokasi dan geotagging, fitur berita dan prediksi bencana alam, fitur pemberian ulasan dampak bencana, fitur notifikasi, fitur informasi tindakan penyelamatan, serta fitur informasi lokasi posko dan data korban. Penelitian ini dapat memberikan manfaat dalam meningkatkan wawasan dan pengetahuan pembaca terkait EWS untuk bencana alam serta menjadi produk acuan untuk pengembangan EWS Indonesia di masa yang akan datang.

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The geographical condition of Indonesia which is passed by The Ring of Fire and has a coastline of 95,181 KM (Pregiwati, 2019) causing Indonesia to be prone to natural disasters in the form of volcanic eruptions, tsunamis, and earthquakes. Therefore, an early warning system (EWS) is needed to provide information on monitoring natural events which can help people be more alert. Unfortunately, Indonesia's early warning system has a fairly low rating. User complaints submitted through application reviews indicate that there are deficiencies in application features, system interface design, and unclear information flow. This study aims to design an interaction design for a natural disaster early warning system mobile application as a development of the previous one that can overcome user complaints. In the development of interaction design, the design thinking method is used. In its implementation, the design thinking method consists of five main processes, namely define, needfinding & synthesis, ideation, prototyping, and testing. In the stage define, interviews were conducted with respondents who are experts in the field of early warning systems and Indonesian natural disasters. Furthermore, at the needfinding & synthesis stage, interviews were conducted with general respondents. From these processes, this research will produce an analysis of user needs and features, stakeholder early warning system in Indonesia, formulation of interaction design, and usability evaluation assessment of the design formulation that has been made. The features developed in this application include geolocation and geotagging features, news and predictions of natural disasters features, features for providing disaster impact reviews, notification features, feature that provide information about rescue actions, and feature that provide information about post locations and victims data. This research can provide benefits in increasing the reader's insight and knowledge regarding the early warning system (EWS) for natural disasters and also being a reference product for the development of Indonesia's EWS in the future."

"Indonesia merupakan negara yang wilayahnya sering mengalami bencana alam. Salah satu penanganan bencana alam adalah pengumpulan informasi berita bencana seperti artikel atau koran, yang mana berguna untuk meningkatkan readability. Meskipun be- gitu, sekadar pengumpulan artikel saja cukup sulit karena identfikasinya dapat memakan waktu serta makna yang termuat pada berita juga masih perlu diserap. Oleh karena itu perlu dilakukan klasifikasi dokumen untuk memilih teks dokumen yang relevan dengan bencana alam, kemudian dari teks dokumen yang relevan dilakukan ekstraksi informasi. Penelitian mengenai klasifikasi teks bencana alam serta ekstraksi informasi yang sudah dilakukan masih menggunakan pendekatan pemelajaran mesin tradisional serta belum memanfaatkan pre-trained model berbasis bahasa Indonesia. Penggunaan pre-trained model dan pendekatan deep learning sendiri sering memperoleh performa yang lebih baik, sehingga ada kemungkinan performa yang dihasilkan dapat ditingkatkan. Dalam penelitian ini dilakukan eksperimen menggunakan pre-trained word embedding seperti Word2Vec dan fastText, pendekatan deep learning seperti BERT dan BiLSTM untuk task klasifikasi. Hasil dengan pendekatan pemelajaran mesin tradisional dengan BoW yang sudah direproduksi menjadi yang terbaik hampir secara keseluruhan, meskipun jenis classifier yang digunakan adalah MLP yang mana sudah menerapkan deep learning karena memiliki beberapa neuron. Kemudian pada penggunaan model pre-trained seperti BERT, terdapat keterbatasan panjang masukan. Keterbatasan ini dapat ditangani dengan membuat representasi dokumen menjadi lebih pendek menggunakan metode peringkasan teks. Hasil representasi ringkasan dokumen dalam penelitian ini mampu meningkatkan performa akurasi klasifikasi baik pada pendekatan pemelajaran mesin tradisional maupun deep learning. Penelitian ini juga melakukan ekperimen penggunaan pre-trained model yang sudah fine-tuned untuk task ekstraksi lokasi seperti NER dan dependency parsing berbasis bahasa Indonesia, meskipun belum dihasilkan performa yang cukup baik.

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Indonesia is a country whose often experiences natural disasters. One way to deal with natural disasters is to collect disaster news information such as articles or newspapers, which are useful for increasing readability. Even so, just collecting articles is quite difficult because identification can take time and the meaning contained in the news still needs to be absorbed. Therefore, it is necessary to classify documents to select document texts that are relevant to natural disasters, then extract information from the relevant document texts. Research on natural disaster text classification and information extraction that has been carried out still uses the traditional machine learning approach and has not yet utilized Indonesian language-based pre-trained models. The use of pre- trained models and deep learning approaches themselves often get better performance, so there is a possibility that the resulting performance can be improved. In this study, experiments were carried out using pre-trained word embedding such as Word2Vec and fastText, deep learning approaches such as BERT and BiLSTM for classification tasks. The results with traditional machine learning approaches with reproducible BoW are the best almost overall, even though the type of classifier used is MLP which already implements deep learning because it has few neurons. Then in the use of pre-trained models such as BERT, there are limitations to the length of the input. This limitation can be overcome by making the document representation shorter using the text summary method. The results of the document summary representation in this study were able to improve the performance of classification accuracy in both traditional and deep learning machine learning approaches. This study also conducted experiments using pre-trained models that had been fine-tuned for location extraction tasks such as NER and Indonesian language-based dependency parsing, although they did not produce sufficiently good performance."

"Berdasarkan keputusan Rapat Kerja Kesehatan Nasional tahun 1990, dan dalam rangka mencegah dan memperkecil terjadinya letusan kejadian luar biasa klb diare, Departemen Kesehatan telah menetapkan Petunjuk Pelaksanaan Sistem Kewaspadaan Dini Kejadian Luar Biasa Penyakit Menular dan Keracunan dimana didalamnya termasuk klb diare. Namun demikian letusan klb diare dari tahun ke tahun masih tetap terjadi dengan frekuensi yang cukup tinggi.Pelaksanaan SKD-KLB Penyakit Menular ini, titik beratnya berada di tingkat Kabupaten dan Kota. Dengan demikian Pelaksanaan SKD-KLB Penyakit Menular di tingkat Kabupaten harus ditingkatkan Salah satu upaya untuk meningkatkan pelaksanaan SKD-KLB ini di tingkat Kabupaten adalah dengan Cara menyajikan data kajadian kasus diare dan faktor-faktor lain yang mempengaruhi terjadinya letusan klb diare. Dalam bentuk yang dapat memberikan kemudahan kepada pengambil keputusan di tingkat Kabupaten menginterprestasikan data tersebut sehingga dengan cepat dan tepat menentukan langkah-langkah mencegah meningkatnya kejadian diare menjadi KLB.Studi ini merancang suatu metode SKD-KLB Diare berbasis Sistem Informasi Geografis (SIG) di Kabupaten Pandeglang dengan menggunakan program aplikasi Epi Info dan Epi Map. Dengan diterapkannya model ini, akan memudahkan petugas pemberantasan penyakit menular, dalam hal ini diare, di Kabupaten Pandeglang dalam mengamati kemungkinan terjadinya klb diare di suatu kecamatan tertentu .Studi ini melingkupi tahapan definisi sistem yaitu penjajagan sistem yang ada serta menganalisa informasi yang di manfaatkan serta menentukan sistem yang diperlukan. Langkah berikutnya adalah desain fisik yaitu menentukan susunan file, format input, pengembangan grogram dan pengernbangan prosedur.Studi ini telah berhasil merancang Sistem Kewaspadaan Dini Kejadian Luar Biasa Diare di Kabupaten Pandeglang. Selanjutnya di sarankan agar Sistem ini dapat di pergunakan dan di terapkan di semua Kabupaten dan Kota.

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Based on the result of National Health Workshop held in 1990, Ministry of Health declared the Guidance for the implementation of Communicable Diseases and Poinsoning Outbreak early Warning System to prevent and to control the possibility of the eruption of communicable diseases and Poinsoning outbreak.

Even though, the MOH had declared the Guidance, there were still diarhoea outbreak happened all over the country. There for the implementation of the Outbreak Early Warning System should be intensified.

Since the back bone of the system is the Regency Health Service, the capability of the decision maker in Regency Health Service should be improved they should have the easiness in making interpretation on the data just by having a glance on it, whether there will be an outbreak or not. It can be done by having the picture of cases distribution by area. There for the Regencies Health Services should be accommodated with the early warring system based on Geographic Information System. The problem is how the system should be. To overcome the problem, there is a system developed based on geographic information system by using Epi Info and Epi Map application program. The system was developed through several steps. Firstly designed the system by examining the existing system, information needed and drawing the flow of the information. Secondly, designed the physical system itself by defining the files needed, format of the input and output, mechanism of system maintenance and conducting working procedure. Unfortunately, due to time limitation, there was no chance to have the system tried out.

It is suggested that the system should be tried out and it would be useful if every regency and municipality can use and operate the system in order to know whether the condition in the regency is almost close to the outbreak of diarhoea or not."

"Berbagai upaya telah dilakukan untuk meliput peristiwa bencana alam. Kendatipun demikian, upaya-upaya yang dilakukan belum secara optimal menampilkan informasi dari perspektif pengguna. Informasi terkait bencana alam yang dipublikasi oleh media lewat berita meliputi lokasi, kronologi, dan statistik terkait bencana. Berita yang dipublikasi media dapat dikumpulkan dengan menggunakan data mining dan diolah untuk memvisualisasikan informasi berbagai jenis bencana alam yang terjadi di Indonesia secara real-time. Visualisasi informasi bencana alam dapat memberikan masyarakat akses ke informasi bencana-bencana alam yang terjadi di Indonesia. Visualisasi informasi bencana alam dikembangkan menggunakan metode User-Centered Design (UCD) yang melibatkan pengguna dalam pengembangan. Dilakukan user research dengan menyebar kuesioner daring dan melakukan wawancara lanjut. Hasil user research digunakan untuk menspesifikasikan kelompok pengguna dari visualisasi informasi bencana alam. Hasil user research juga digunakan sebagai design insights untuk mengembangkan desain solusi dari visualisasi informasi bencana alam. Desain visualisasi informasi bencana alam yang telah dikembangkan dievaluasi dengan melaksanakan usability testing dan pengisian kuesioner system usability scale. Desain yang sudah dikembangkan memiliki rata-rata task success sebesar 89% dan tingkat penerimaan Acceptable. Terdapat peluang perbaikan lanjutan untuk desain yang sudah dikembangkan. Peluang tersebut meliputi kebutuhan utama visualisasi informasi bencana alam dan kebutuhan di luar desain seperti bantuan korban bencana alam dan edukasi bencana alam. 

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Various attempts have been made to cover natural disasters. Nevertheless, the efforts made have not optimally displayed information from the user's perspective. Information related to natural disasters published by the media through news includes location, chronology, and statistics related to disasters. News published by the media can be collected using data mining and processed to visualize information on various types of natural disasters that occur in Indonesia in real-time. Visualization of natural disaster information can give people access to information on natural disasters that occur in Indonesia. Visualization of natural disaster information is developed using the User-Centered Design (UCD) method which involves the user in development. User research was conducted by distributing online questionnaires and conducting further interviews. The results of user research are used to specify user groups from visualization of natural disaster information. The results of user research are also used as design insights to develop design solutions from information visualization of natural disasters. The design of the visualization of natural disaster information that has been developed is evaluated by carrying out usability testing and filling out a usability scale system questionnaire. The design that was developed has an average task success of 89% and an acceptable acceptance level. There are opportunities for further improvement for designs that have already been developed. These opportunities include the main needs for visualization of natural disaster information and needs outside of design such as assistance for victims of natural disasters and education for natural disasters."

"Sistem Peringatan Dini Bencana (Disaster Early Warning System) atau yang disebut DEWS adalah sistem yang dikelola oleh Badan Penanggulangan Bencana Daerah Provinsi DKI Jakarta dan digunakan oleh petugas Unit Pelaksana Teknis Pusat Data dan Informasi Kebencanaan (UPT PDIK) serta petugas di Kelurahan terdampak bencana banjir. DEWS bertujuan untuk membantu masyarakat dalam menerima, memahami, dan bereaksi secara cepat dan tepat terhadap peringatan dini yang diinformasikan oleh petugas. DEWS dinilai belum optimal dan sesuai dengan ekspektasi yang diharapkan dalam mengelola layanan peringatan dini bencana. Hal ini ditunjukan dari permasalahan-permasalahan terkait kinerja DEWS.Tujuan penelitian ini adalah untuk melakukan evaluasi terkait analisis faktor yang memengaruhi kesuksesan dari Sistem Peringatan Dini Bencana (DEWS) dan rekomendasi peningkatan kualitas sistem. Salah satu cara menghindari kegagalan layanan e-government adalah dengan menentukan dan mendefinisikan faktor kesuksesan diawal implementasi (Napitupulu, Syafrullah, Rahim, Amar, & Sucahyo, 2018). Penelitian ini mengadopsi model kesuksesan DeLone & McLean dengan penambahan variabel kualitas teknologi pelengkap. Data dikumpulkan dengan menggunakan kuesioner yang disebar kepada petugas UPT PDIK BPBD Provinsi DKI Jakarta dan petugas kelurahan dimana DEWS telah terpasang. Data hasil kuesioner diolah dengan menggunakan Partial Least Squares-Structural Equation Model (PLS SEM).Dari 11 hipotesis pada penelitian ini setelah dilakukan pengolahan data dengan menggunakan PLS SEM terdapat 5 hipotesis yang diterima dan 6 yang ditolak. Kepuasan pengguna (user satisfaction) menjadi variabel paling memiliki pengaruh positif kepada kesuksesan DEWS. Kemudian diikuti kualitas sistem (system quality), kualitas teknologi pelengkap (complimentary). Penggunaan (use) saat ini belum memiliki pengaruh pada kesuksesan, dimana kualitas layanan berpengaruh positif pada penggunaan, namun belum berpengaruh pada kepuasan pengguna. Kualitas informasi (information quality) saat ini juga belum memiliki pengaruh positif pada penggunaan dan kepuasan pengguna.

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The Disaster Early Warning System, called DEWS, is a system managed by the DKI Jakarta Provincial Disaster Management Agency and used by Disaster Data and Information Center Technical Implementation Unit (UPT PDIK) officers and officers in villages district that affected by flood disasters. DEWS aims to assist the community in receiving, understanding, and reacting quickly and precisely to early warnings that are informed by officers. DEWS is considered not optimal and in accordance with the expectations expected to manage disaster early warning services. This is shown from the problems related to DEWS performance.

The purpose of this study is to evaluate the analysis of factors that influence the success of the Disaster Early Warning System (DEWS) and recommendations for improving the quality of the system. One way to avoid the failure of e-government services is to determine and define success factors at the beginning of implementation (Napitupulu, Syafrullah, Rahim, Amar, & Sucahyo, 2018). This study adopts the DeLone & McLean success model with the addition of complementary technology quality variables. Data was collected using a questionnaire distributed to UPT PDIK BPBD DKI Jakarta Province staff and village officials in district where DEWS has been installed. Data from the questionnaire were processed using the Partial Least Squares-Structural Equation Model (PLS SEM).

By 11 hypotheses in this study after processing data using PLS SEM, there are 5 accepted and 6 rejected hypotheses. User satisfaction has the most positive influence on DEWS success. Then followed by the system quality and complimentary. Use does not currently have an influence on success, where service quality has a positive effect on use, but has not affected user satisfaction. The information quality at this time also does not have a positive influence on the use and user satisfaction."

"This book documents seven examples of early warning systems for hydrometeorological and other hazards that have proven effective in reducing losses due to these hazards. The cases studied encompass a variety of climatic regimes and stages of economic development, raging across the industrialized countries of Germany, France, Japan and the United States, to Bangladesh, the island nation of Cuba and the mega-city of Shanghai."

"Many aspects of disaster risk management, such as for earthquakes, volcanic eruptions, floods, avalanches and mudslides call for similar prevention and preparedness instruments, management concepts, and countermeasures. This textbook assumes the viewpoint of a regional disaster risk manager who is responsible for a certain area, and for making the lives of the people who live there safer, regardless of the type of natural disaster that may occur. The same holds true for boosting preparedness and awareness in the population at risk. The book includes numerous examples of hazard mitigation concepts and techniques, as well as ways of intensively involving the local population in prevention schemes at an early stage. Furthermore, this textbook provides an in-depth examination of the function of risk communication, both as an instrument for official information dissemination and as a function of public media. To close, a chapter on risk splitting offers insights into insurance-based models for risk financing."

"Participation to preserve, care and positive behavior in accordance with the insight wisdom in managing the real envirinment is closely rooted in the tradition of women. This study aims to determine the potential of women ..."

"[ABSTRAKKrisis rupiah di tahun 1997-1999 adalah gejolak besar bagi ekonomi Indonesia dimana pertumbuhan ekonomi anjlok, sistem perbankan lumpuh, diikuti dengan konsekuensi sosial dan politik yang pahit. Diyakini jika otoritas moneter daan pembuat kebijakan lainnya dapat mengantisipasi krisis tersebut, segala konsekuensi yang tidak diinginkan tersebut dapat dikurangi dan mungkin dihindari.Sistem pendeteksian dini untuk krisis rupiah diharapkan dapat memberi waktu para pembuat kebijakan untuk mengantisipasi datangnya krisis. Namun salah satu faktor sukses yang kritikal dalam pembentukan sistem tersebut adalah seleksi indikator.Penelitian ini menerapkan Indication & Warning Intelligence (I&W)untuk sistem pendeteksian dini krisis rupiah dengan produk akhir berupa set indikator yang dianggap efektif memprediksi krisis rupiah. Dengan I&W diseleksi lima indikator, yang selanjutnya diuji keefektifannya dengan metode regresi logit, yang menyatakan bahwa terdapat tiga indikator yang dapat memprediksi krisis rupiah secara signifikan yang adalah: 1) Real Effective Exchange Rate, 2) Deposit Money Bank?s Foreign Asset Growth, dan 3) Inflasi.

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ABSTRACTCurrency crisis in Indonesia that took place in 1997-1999 was a major shock to the economy which plunge the growth, collapse the banking system with its bitter social and political consequences. It is acknowledged that if the monetary authority could anticipate such shock, the result would not be as devastating, it could be far lessen, and hopefully avoided.Early warning system for currency crisis is crucial for policy makers to anticipate the coming crisis with enough preparation. One of the most important factor in framing that system is indicators selection.This research apply Indication & Warning Intelligence (I&W) to early warning system of rupiah crisis with indicator set as its end product. With I&W five indicators are selected, which underwent further significance test with logistic regression method. This method results in three indicators being the most effective in predicting rupiah crisis, namely: 1) Real Effective Exchange Rate, 2) Deposit Money Bank?s Foreign Asset Growth, and 3) Inflation.;Currency crisis in Indonesia that took place in 1997-1999 was a major shock to the economy which plunge the growth, collapse the banking system with its bitter social and political consequences. It is acknowledged that if the monetary authority could anticipate such shock, the result would not be as devastating, it could be far lessen, and hopefully avoided.Early warning system for currency crisis is crucial for policy makers to anticipate the coming crisis with enough preparation. One of the most important factor in framing that system is indicators selection.This research apply Indication & Warning Intelligence (I&W) to early warning system of rupiah crisis with indicator set as its end product. With I&W five indicators are selected, which underwent further significance test with logistic regression method. This method results in three indicators being the most effective in predicting rupiah crisis, namely: 1) Real Effective Exchange Rate, 2) Deposit Money Bank’s Foreign Asset Growth, and 3) Inflation., Currency crisis in Indonesia that took place in 1997-1999 was a major shock to the economy which plunge the growth, collapse the banking system with its bitter social and political consequences. It is acknowledged that if the monetary authority could anticipate such shock, the result would not be as devastating, it could be far lessen, and hopefully avoided.Early warning system for currency crisis is crucial for policy makers to anticipate the coming crisis with enough preparation. One of the most important factor in framing that system is indicators selection.This research apply Indication & Warning Intelligence (I&W) to early warning system of rupiah crisis with indicator set as its end product. With I&W five indicators are selected, which underwent further significance test with logistic regression method. This method results in three indicators being the most effective in predicting rupiah crisis, namely: 1) Real Effective Exchange Rate, 2) Deposit Money Bank’s Foreign Asset Growth, and 3) Inflation.]"