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"Rice fields located in Citarum Hilir watershed of Karawang district are more and more affected by growth of residential and industrial areas. This resulted in the need to have supporting rice fields elsewhere including in the upstream region. ln Citarum Hulu watershed, 19,5% fiom the existing rice fields is non-irrigated with 32,l9% of population work in the agriculture sector. But productivity of' non-irrigated rice fields of Citanim Hulu watershed is still low, which is below 25 kwintal/ha. One of the efforts to increase its productivity is to look at the local climate model. The low productivity may also be caused by factors such as slope and altitude, which are used as variables in Wilayah Tanah Usaha (WTU). Sandy (1985) wrote that growth and death of any plant in Indonesia depend on water. Awarding to Chang (1968) every process in a plant is affected by water. Furthermore, FAO believed that the growth requirement of a rice plant is also depended on water availability. Mohr, Schimdt-Ferguson, and Oldeman made climate classifications based on rainfall in relation with plant needs of irrigation. Spatial climate model and planting time/season are important factors in management of non-irrigated rice fields in Citarum Hulu watershed. These rice fields are nou-unifonnly found in the center down to the south. Rice production varies from 22 to 4l kw/ha where the majority produces 30-40 kw/ha. Productivity model for the northem part is varied, and to the south is more stable with productivity of 30-40 kw/ha. The annual average rainfall in Citarum Hulu watershed is 1770-3458 mm/yr where the majority of the region has in the range of 2000-3000 mm/yr. Maximum monthly rainfall is 558 mm and a minimum of 6 mm on average. Rainfall is high in the months of November to April and dry period is fiom June to August. Mol-rr?s climate classification is around class III - Vb where the majority is in class III-IV. Schmidt-Ferguson?s climate classification for this area is type C to type A, where the majority is in the wet type (A). 0Ideman?s climate classification varies from D3 to Bl where the majority ofthe region is in climate group C-B (humid-wet). ln general, climate model for Citarum Hulu watershed is as follows: in the center (around the city of Bandung) is almost always drier than its surrounding areas, specifically in the northem and southem parts that are mountainous. The distribution of non-irrigated rice fields has a strong correlation with the annual rainfall model of Schimdt-Ferguson and Oldeman, because as an area has more precipitation there tend to be non-irrigated rice fields. But it is not true with Mohr climate. A strong correlation in productivity of non-irrigated rice fields with rainfall model, Mohr, Schmidt-Ferguson, and Oldeman climate models mean that as a region receives more precipitation then 'there is a tendency of higher rice productivity. But there is also a tendency that if an area is extremely wet, the productivity will decrease. Planting season in the Citarum Hulu watershed is from October and May with 4 planting time models: October/February, October/March, November/March, and December/April. In the November/March, planting time is dominant in almost all of the watershed area. Part of the non-irrigated rice fields in Citarum Hulu watershed are still according to the WTU conception, that is 65,87%, which the majority is in the center. As for the rest of this region, they should be converted into protected forest areas (especially in the south) and hard plant agriculture (in the cast). Keywords: DAS Citarum Hulu, non-irrigated rice fields, rainfall, climate model, Mohr, Schmidt-Ferguson, Oldeman, WTU conception, planting time."

"Klasifikasi curah hujan sangat membantu masyarakat dan instansi terkait dalam mengambil kebijakan seperti pengelolaan sumber daya air, transportasi, pertanian dan pencegahan bencana. Model yang sudah pernah digunakan dalam melakukan klasifikasi curah hujan yaitu XGBoost, telah terbukti mampu melakukan klasifikasi dengan efektif, namun masih memerlukan tuning pada hyperparameter-nya untuk meningkatkan performa model. Penelitian ini bertujuan untuk merancang metode klasifikasi curah hujan dengan model XGBoost dan menemukan nilai learning rate terbaik untuk klasifikasi curah hujan. Parameter max depth, dan n estimator ditetapkan berdasarkan penelitian yang sudah pernah dilakukan. Model ini dibangun berdasarkan data historis curah hujan selama 3 bulan setiap jam, yang telah dikumpulkan oleh peralatan Automated Weather Observed System (AWOS) di Stasiun Meteorologi Kota Pontianak. Pencarian hyperparameter menggunakan metode coarse to fine, yaitu pencarian kasar ke pencarian halus. Pencarian kasar menggunakan RandomizedSearchCV, sedangkan pencarian halus dengan GridSearchCV. Model dievaluasi dengan metrik Accuracy, precision, recall, dan F1-score. Evaluasi menunjukkan bahwa model memilki metrik evaluasi yang baik dengan persentase diatas 80% untuk setiap kasus pembagian data. Nilai learning rate terbaik dengan akurasi tertinggi yang didapatkan pada model dengan 2040 data set adalah pada kasus klasifikasi biner, yaitu sebesar 0.043 dengan akurasi pada data latih 90.19%.

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The classification of rainfall is very helpful for the community and related agencies in making policies such as managing water resources, transportation, agriculture, and disaster prevention. The model that has been used to classify rainfall, namely XGBoost, has proven to be able to classify effectively but still requires tuning its hyperparameters to improve model performance. This study aims to design a rainfall classification method using the XGBoost model and find the best learning rate for rainfall classification. The max depth and n estimator parameters are determined based on research that has been done. This model was built based on historical rainfall data for 3 months every hour, which has been collected by the Automated Weather Observed System (AWOS) equipment at the Pontianak City Meteorological Station. The hyperparameter search uses the coarse-to-fine method, which is a coarse-to-fine search. The coarse search uses RandomizedSearchCV, while the fine search uses GridSearchCV. The model is evaluated with Accuracy, precision, recall, and F1-score metrics. The evaluation shows that the model has good evaluation metrics with percentages above 80% for each case of data sharing. The best learning rate value with the highest accuracy obtained in the model with the 2040 dataset is in the binary classification case, which is equal to 0.043 with an accuracy of 90.19% of the training data."

"Keamanan dan keselamatan adalah sesuatu yang sangat penting dalam kehidupan manusia dan panting dalam mendorong pembangunan suatu bangsa, baik secara sosial-ekonomi; peningkatan produksi pangan; mengurangi akibat dari bencana alam; keselamatan operasi transportasi laut, udara dan darat; perlindungan alam dan lingkungan, maka informasi meteorologi dan geofisika adalah merupakan informasi yang paling mendasar yang digunakan baik secara nasional, regional maupun global. Badan Meteorologi dan Geofisika-BMG, adalah lembaga pemerintah non departemen (LPND) yang bertanggungjawab terhadap proses monitor dan pencatatan data hasil observasi meteorologi dan geofisika di Indonesia selama 24 jam sehari 7 hari seminggu, serta mempersiapkan informasi meteorologi dan geofisika yang diperlukan sesuai untuk kepentingan dan keperluan pemakainya.Melihat pada kinerja operasi Badan Meteorologi dan Geofisika saat ini, maka diperlukan upaya-upaya perbaikan. Upaya peningkatan kinerja maupun perbaikan dapat dilakukan, setelah sebelumnya dilakukan langkah-langkah sesuai dengan manajemen strategis, yaitu melalui : analisa dan evaluasi strategis terhadap jaringan komunikasi data meteorologi dan geofisika yang digunakan untuk pengumpulan data observasi dari stasiun pengamatan dan distribusi pelayanan informasinya kepada masyarakat melalui pusat-pusat pelayanan informasi nasional. Peningkatan kinerja ini secara khusus akan dilihat pula dari aspek cost benefit.

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Security and safety are something important in human life and important in pushing national development, either through sosio-economic aspect; improvement of food production; reduction effect of natural disaster; safety operation for sea, land and air transportation; environmental and natural protection, therefore meteorological and geophysical information represent the basic information which used by national, regional and global community. Badan Meteorologi dan Geofisika-BMG, is a non department government agency (LPND) which is responsible to do the monitoring process and keeping of the data result of meteorological and geophysical observation in Indonesia during 24 hours a day and 7 days a week, and also provide the meteorological and geophysical information for the customers.

Look at the operation and performance of Badan Meteorologi dan Geofisika at this time, so it needed evaluation efforts. The performance improvement and repairs efforts can be conducted, after previously the strategic management has been done, that is : conduct the strategic analysis and evaluation to identify problems of meteorological and geophysical data communication network. This data communication network will be used to collect the observation data from basic station and to distribute the information to the public via public services station. Improvement of the performance primarily will be seen from benefitial cost aspect."

"Penelitian ini dilakukan untuk mempelajari karakteristik dan variabilitas angin yang membangkitkan gelombang laut di perairan selat Karimata dan laut Jawa. Data yang digunakan adalah arah dan kecepatan angin ketinggian 10 meter pengamatan tiap 6 jam tahun 2005 - 2010. Berdasarkan hasil analisis menunjukkan bahwa arah dan kecepatan angin dominan saat musim barat di selat Karimata dari baratlaut - utara, kecepatan angin antara 5 - 10 knots, puncak gelombang tertinggi antara 4 - 5 meter. Sedangkan di laut Jawa, angin dominan dari barat - baratlaut, kecepatan berkisar antara 10 - 15 knots dengan puncak gelombang tertinggi mencapai 3,5 - 4 meter, puncak tertinggi terjadi di bulan Desember - Januari dan terendah bulan April. Saat musim angin timur di selat Karimata, angin dominan dari tenggara - selatan, di laut Jawa dominan dari timur - tenggara, kecepatan angin di kedua wilayah ini antara 10 - 15 knots. Puncak gelombang tinggi di musim ini terjadi bulan Juli - Agustus dengan gelombang tertinggi mencapai 2,5 - 3 meter dan puncak terendah terjadi bulan Nopember. Frekuensi tinggi gelombang  2 meter 20 - 30% di laut Jawa bagian timur dan selat Karimata bagian utara terjadi bulan Januari.

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This study was conducted to study the characteristics and variability of wind generating waves in the ocean waters of the Karimata strait and Java sea. The data utilized here are the 10 meters direction and wind speed observation height in every 6 hours in 2005 to 2010. The analysis results indicate that the dominant wind direction and speed during the wind west season in the Karimata strait is from northwest - north, with the wind speed ranged between 50 - 10 knots, the highest peak of the wave is between 4 - 5 meters. While in Java Sea, the dominant winds is from the west - northwest, with the velocity ranged between 10 - 15 knots and the highest wave peaks reaching 3.5 to 4 meters, the highest peak occurred on December-January and the lowest was on April. As the east wind season in the east Karimata strait, the dominant winds is from the southeast - south, in the Java Sea the dominant winds is from east - southeast, the wind speed in the second region between 10 - 15 knots. The wave height peak of the season occurs in July - August with the highest wave reached 2.5 - 3 meters and the lowest peak occurred in November. High-frequency waves  2 meters 20 - 30% in eastern Java Sea and the northern part of the Karimata strait occurred in January."

"Berdasarkan tinjauan fisis dan hasil analisis klimatologi pola sebaran suhu muka laut, suhu udara permukaan dan curah hujan di wilayah daratan Sumatera Barat, menunjukkan bahwa lautan memiliki peran dalam pembentukan sistem cuaca di wilayah Sumatera Barat. Namun, ini masih harus dibuktikan dengan melibatkan pola sebaran angin di perairan timur Samudera Hindia dan sekitar Sumatera Barat serta penelitian lebih lanjut tentang pengaruh kondisi lokal terhadap pembentukan hujan di Sumatera Barat. Indeks penguapan laut dapat dihitung dari besarnya kecepatan angin, serta selisih antara suhu muka laut dan suhu udara permukaan. Perhitungan dilakukan dengan menggunakan data meteorologi permukaan bulanan selama periode 30 tahun (1971-2000) yang diperoleh dari NCEP Realtime Marine Data di perairan timur Samudera Hindia. Analisis hubungan indeks penguapan dengan curah hujan di Sumatera Barat menggunakan regresi linear yang dinyatakan dari nilai koefisien korelasinya. Hasil perhitungan menunjukkan rata-rata indeks penguapan bulanan bagian selatan ekuator Samudera Hindia lebih tinggi dibandingkan bagian utara ekuator dan makin ke arah pantai indeks penguapan semakin rendah. Di bagian utara peningkatan indeks penguapan terjadi pada bulan April dan Oktober hingga puncaknya November, sedangkan di bagian selatan peningkatan terjadi mulai bulan Juni hingga Agustus. Sumatera Barat memiliki 4 pola hujan dengan sebaran curah hujan tertinggi di pesisir barat dan wilayah perbukitan sebelah barat Bukit Barisan, sedangkan ke arah wilayah perbukitan tersier sebelah timur Bukit Barisan curah hujan semakin rendah. Pada kondisi normal, bulan Maret dan November merupakan bulan dengan nilai curah hujan yang paling tinggi. Indeks penguapan laut di sekitar ekuator Samudera Hindia umumnya berkorelasi kuat dan positif dengan curah hujan bulanan di pesisir barat dan wilayah perbukitan sebelah barat Bukit Barisan. Semakin dekat jaraknya ke arah pantai nilai koefisien korelasinya lebih tinggi. Koefisien korelasi indeks penguapan dengan hujan bulanan pada bulan yang sama lebih tinggi dibanding menggunakan indeks penguapan satu bulan sebelumnya."

"ABSTRACTIce accretion pada sayap menjadi salah satu penyebab kecelakaan pesawat terbang karena akan merusak aliran udara pada sayap. Bentuk ice accretion yang terjadi dapat diinvestigasi melalui beberapa cara seperti flight test, eksperimen wind tunnel, dan simulasi numerik. Flight test dan eksperimen wind tunnel dapat menentukan bentuk es yang akurat namun tidak praktis dan memakan banyak biaya. Kode LEWICE digunakan untuk memprediksi geometri es yang akan terbentuk pada sayap pesawat N219 dalam kondisi atmosfir icing. Kondisi atmosfir icing ini telah sesuai dengan kebutuhan sertifikasi icing yang tertera dalam 14 CFR part 25.1419, Appendix C. Pada penelitian ini didapatkan 2 kategori es yang terbentuk pada leading edge sayap pesawat N219 yaitu horn ice dan streamwise ice. Degradasi performa airfoil yang terjadi didapatkan menggunakan XFLR5. Perubahan performa airfoil ini digunakan untuk mencari perubahan landing distance pesawat N219 saat es terbentuk. Dari hasil penelitian didapatkan bahwa degradasi performa airfoil paling besar terjadi disebabkan oleh horn ice. Namun, degradasi performa airfoil yang didapatkan tidak terlalu mempengaruhi perubahan landing distance pesawat N219 saat terjadi icing. Perubahan landing distance yang terjadi karena adanya ice accretion berkisar antara sampai.

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ABSTRACTIce accretion on a wing is one of the accident factor in aviation because it will interrupt the flow over the wing. The shape of ice accretion can be investigated through filght test, wind tunnel experiment, and numerical simulation. Flight test and wind tunnel experiment will determine the shape of ice accurately but usually too expensive and not practical. Therefore, numerical simulation is used to predict the shape of ice accretion because it is economic and can simulate the icing process and provide a relatively exact evaluation of ice accretion. LEWICE code is used to predict the geometry of ice that will accrete on the leading edge of the aircraft wing in atmospheric icing condition. This atmospheric icing condition is based on icing certification in 14 CFR part 25.1419, Appendix C. Two category of ice accretion, horn ice and streamwise ice, were obtained on the leading edge. The degradation of airfoil performance then obtained form XFLR5. The change of the airfoil performance will affect the landing distance of the aircraft when the ice accretion happened. The most degradation of airfoil performance is caused by horn ice. But, the degradation of airfoil performance not really have big effects on the change of the aircraft landing distance. The landing distance that change because of ice accretion is within range of and."