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"Hydrology plays important role in urban development thus hydrologic event that occurs has to be accurately estimated in order to satisfy the needs of the area in infrastructure. The advance technology has helped the engineers to model the event which should lead into better decisionmaking and visualisation in undertaking most hydrological cases. This thesis reviews four urban hydrological modelling softwares and discusses the essential components of the modelling that includes catchment model, loss model, storage discharge relations, and its input parameters. The aim of the review is to provide basic understanding of the hydrology processes by using modeling software in accordance to the basic theory and standard design. The review does not seek to be a comprehensive technical of urban hydrology management and modelling."

"ABSTRACTWater Sensitive Urban Design WSUD systems have the potential prevent the hydrologic disturbance and water quality concern associate with storm water runoff due to land change from urban development. WSUD have been strongly recommended to be used and new developments in every city in Australia are regulated. However, Indonesia still developing the rule but not deeply studied the idea and concept of WSUD. The objective of this research is to comparing available system in sustainable city of case study to the concept that is used in Australia. The main idea of why it is applied in Australia is due to most of the land use are impervious area which is increase in runoff peak and develop industrialize region.

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ABSTRAKWater Sensitive Urban Design WSUD system memiliki potensi mencegah gangguan dan menambah kualitas air dari limpasan air hujan akibat perubahan lahan dari pembangunan perkotaan. WSUD telah disarankan untuk digunakan dalam perkembangan baru di Australia. Indonesia masih mengembangkan aturan tetapi tidak mendalam mempelajari ide dan konsep WSUD. Tujuan dari penelitian ini adalah untuk membandingkan sistem yang tersedia di kota yang berkelanjutan dari studi kasus dengan konsep yang digunakan di Australia. Ide utama mengapa konsep WSUD diterapkan di Australia adalah karena industrialisasi sebagian besar penggunaan lahan hijau berubah dan mengakibatkan puncak limpasan besar."

"The fusion of algebra, analysis and geometry, and their application to real world problems, have been dominant themes underlying mathematics for over a century. Geometric algebras, introduced and classified by Clifford in the late 19th century, have played a prominent role in this effort, as seen in the mathematical work of Cartan, Brauer, Weyl, Chevelley, Atiyah, and Bott, and in applications to physics in the work of Pauli, Dirac and others. One of the most important applications of geometric algebras to geometry is to the representation of groups of Euclidean and Minkowski rotations. This aspect and its direct relation to robotics and vision will be discussed in several chapters of this multi-authored textbook, which resulted from the ASI meeting. Moreover, group theory, beginning with the work of Burnside, Frobenius and Schur, has been influenced by even more general problems. As a result, general group actions have provided the setting for powerful methods within group theory and for the use of groups in applications to physics, chemistry, molecular biology, and signal processing. These aspects, too, will be covered in detail. With the rapidly growing importance of, and ever expanding conceptual and computational demands on signal and image processing in remote sensing, computer vision, medical image processing, and biological signal processing, and on neural and quantum computing, geometric algebras, and computational group harmonic analysis, the topics of the book have emerged as key tools. The list of authors includes many of the world's leading experts in the development of new algebraic modeling and signal representation methodologies, novel Fourier-based and geometric transforms, and computational algorithms required for realizing the potential of these new application fields."

"[Tesis ini menganalisis pemaknaan dan reaksi manusia gerobak terhadap ruang urban Jakarta. Pemaknaan terhadap ruang urban Jakarta oleh manusia gerobak dan reaksi mereka terhadap regulasi di ruang urban Jakarta menjadi pertanyaan dalam tesis ini. Data diperoleh melalui pendekatan etnografi dengan wawancara mendalam kepadamanusia gerobak di Jakarta Selatan, dan observasi kegiatan manusia gerobak. Tesis ini menggunakan konsep urban dan hegemoni untuk menjawab rumusan masalah. Hasil penelitian menunjukkan manusia gerobak memaknai ruang urban Jakarta dengan eksistensi melalui mobilitas mereka untuk dapat bertahan di ruang urban Jakarta.Manusia gerobak menunjukkan reaksi berupa resistensi terhadap regulasi di ruang urban Jakarta. Mereka menunjukkan resistensi dengan tidak memiliki Kartu Tanda Penduduk, menolak bekerja dalam sektor formal dengan memilih menjadi manusia gerobak, dan tidak ingin menempati rumah tinggal seperti yang diberikan oleh pemerintah. Resistensi ini menjadi bentuk gerakan untuk menuntut hak mereka atas kota dalam konteks Jakarta sebagai ruang urban;This thesis analyses how manusia gerobak makes meaning out of the urban space ofJakarta. It evaluates manusia gerobak’s meaning making process and how they react to the urban regulation in Jakarta. The main research method is utilizing ethnographic tools which consist of in-depth interviews and observations of manusia gerobak in South Jakarta. In analyzing the data, the concepts of urban and hegemony are used toanswer the research questions. Research findings reveal that the meaning making process is done within the manusia gerobak’s mobility as a way to reflect in their existence in Jakarta. At the same time, manusia gerobak show their resistance to regulation by rejecting to have Jakarta’s identity card, refusing to work in formal sector by choosing to be a manusia gerobak as their job, and not wanting to stay in formal settlements, such as houses provided by the government. All of these represent their resistance in claiming their rights to the city in the context of Jakarta as an urban space, This thesis analyses how manusia gerobak makes meaning out of the urban space ofJakarta. It evaluates manusia gerobak’s meaning making process and how they react tothe urban regulation in Jakarta. The main research method is utilizing ethnographictools which consist of in-depth interviews and observations of manusia gerobak inSouth Jakarta. In analyzing the data, the concepts of urban and hegemony are used toanswer the research questions. Research findings reveal that the meaning makingprocess is done within the manusia gerobak’s mobility as a way to reflect in theirexistence in Jakarta. At the same time, manusia gerobak show their resistance toregulation by rejecting to have Jakarta’s identity card, refusing to work in formal sectorby choosing to be a manusia gerobak as their job, and not wanting to stay in formalsettlements, such as houses provided by the government. All of these represent theirresistance in claiming their rights to the city in the context of Jakarta as an urban space]"

"Jakarta merupakan ibukota Indonesia yang berfungsi sebagai pusat pemerintahan dan ekonomi, dimana urbanisasi menjadi masalah di Jakarta yang memiliki laju pertumbuhan penduduk yang mencapai 0,86% menurut Badan Pusat Statistik. Dengan pertumbuhan penduduk yang masih terus bertambah, pengelolaan sumber air menjadi aspek yang krusial dalam tata kota dan urban planning. Salah satu aspek utama dalam pengelolaan tersebut adalah mengelola hubungan curah hujan-limpasan permukaan pada daerah tersebut. Salah satu cara dalam pengelolaan tersebut adalah melalui metode pemodelan dimana metode ini dapat memberikan analisis secara mendalam serta kemampuannya dalam memprediksi yang berguna untuk pengelolaan sumber air. Terdapat berbagai cara dalam memodelkan hubungan curah hujan-limpasan permukaan dimana salah satunya adalah pemodelan berbasis data. Salah satu metode pemodelan tersebut adalah melalui deep learning dimana pada penelitian ini penulis mengunakan metode Long Short-term Memory (LSTM). Penelitian ini akan menggunakan LSTM sebagai alat untuk memodelkan data curah hujan dari tiga stasiun pengukuran dan data debit sungai dari tiga stasiun pengukuran dengan rentang waktu sepanjang 12 tahun (2009-2020). Hasil dari prediksi menunjukkan bahwa model LSTM memiliki performa yang buruk dalam dataset curah hujan dimana nilai R² tertinggi yang mencapai 0.09 dengan nilai MAE dan RMSE yang masing-masing berada pada 9,7 mm dan 18,14 mm. Performa pada dataset limpasan permukaan menunjukkan bahwa LSTM memiliki performa yang cukup baik dimana masing-masing rata-rata nilai R², MAE dan RMSE tertinggi berada pada 0,58, 4,15 m³/s dan 8 m³/s. Berdasarkan dari hasil evaluasi tersebut, penulis menyimpulkan bahwa meskipun dengan nilai akurasi yang rendah, model LSTM masih memiliki potensi untuk dikembangkan secara lebih lanjut apabila melihat nilai MAE dan RMSE yang berada pada kisaran yang cenderung lumayan sehingga LSTM dapat dikembangkan dengan penambahan data masukan.

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Jakarta is a capital city which functioned as both a governmental and economic centre in Indonesia, which makes urbanization a problem in Jakarta, on which Jakarta itself has a population growth rate of 0.86% according to Statistic Indonesia. As Jakarta is still growing in terms of its population, managing water resources in the city is such a critical aspect of its urban planning. ­One of the key aspects of water resources management is managing the rainfall-runoff relationship in the area. One of the ways of managing it is through modelling the relationship itself which can give an in-depth analysis and its capability for forecasting which can be valuable in water resources management. Various approaches to modelling rainfall-runoff have been developed over the years, which data-driven modelling is one of them. One of the methods is through deep learning, which in this study we will use long short-term memory (LSTM) neural network. This study will use LSTM neural network as a tool to model 9 years (2009-2020) of rainfall data from three rain gauge stations and three discharge gauge stations to train the model. Results from the prediction shows that the LSTM model performed terribly on rainfall datasets, which the highest from the R² values are 0.09 with MAE and RMSE are on 9.7 mm and 18.4 respectively. Performance on runoff datasets shows that LSTM performed on a decent level, which mean from the R², MAE and RMSE are on 0.58, 4.15 m³/s and 8 m³/s respectively. Based on the evaluation results, author suggests that despite of its low level of accuracy, models based on LSTM still have some room for improvement based on their MAE and RMSE value that at least are on a respectable level shown that they could benefit from adding more data as an input for better performance of the model."