Fog is one of the atmospheric phenomena that affect airport operations. It can reduce visibility which impacts flight operations (taxiing, take-off, landing). Therefore, fog prediction is needed to support flight safety. The biggest challenge in making weather predictions is the chaotic and complicated process of the atmosphere. This research tries to use artificial intelligence (AI) to predict fog events at Wamena Airport. Design of model prediction using hourly synoptic data set from January 2015 till May 2018. Variables input such as dry ball temperature, wet ball temperature, dew point, relative humidity, cloud cover, wind direction, wind speed, visibility, and present weather for the past six hours ago are used to predict fog or no fog events. We performed a grid search parameter tuning on five algorithms such as Distributed Random Forest (DFR), Deep Learning (DL), Gradient Boosting Machine (GBM), Generalized Linear Model (GLM), and Extreme Randomized Tree (XRT). The best model is obtained from the ensemble model Stacked Ensemble (SE) with an accuracy of above 90% for the fog forecast from one to three hours later.
IntisariHujan lebat di Batam tanggal 30-31 Januari 2011 menyebabkan banjir. Nilai hujan akumulasi hasil obsevasi pada 31 Januari 2011 sebesar 414.5 mm, jauh melebihi ambang batas ekstrim untuk curah hujan yang hanya 50 mm/hari. Adanya hujan lebat tidak lepas dari dinamika parameter-parameter cuaca yang beraitan erat dengan proses konveksi dan pembentukan awan. Pada penulisan ini, analisa kondisi cuaca menggunkan Weather Research and Forecasting (WRF) satu domain dengan resolusi 6 kilometer (km) pada 1• LU dan 104• BT. Beberapa parameter cuaca seperti suhu udara, kelembaban tiap lapisan (RH), aliran massa udara (angin), dan curah hujan menunjukkan hasil yang sangat signifikan dimana nilai dari parameter-parameter tersebut mendukung adanya proses konveksi untuk membentuk awan konvektif (Cumulonimbus) secara terus menerus dengan masa hidup yang lama. WRF dengan setting-an default dan domain tanpa nesting ternyata sduah cukup mampu menggambarkan kondisi cuaca secara umum. Adanya perbedaan laju curah hujan hasil output model dengan observasi antara 6-12 jam pada awal data merupkan proses spin-up (pemanasan untuk mendapatkan data yang stabil pada hasil model). Data citra satelit MTSAT (Multi-functional Transport Satellite) digunakan sebagai pembanding hasil model, dimana pada gambar terdapat warna putih Coldest Dark Grey (CDG) yang mengindikasikan adanya awan dengan suhu puncak lebih rendah dari -80• C (Cb). Gambar ini semakin memperjelas bahwa pada kasus hujan lebat yang mengguyur Batam pada 30-31 Januari dengan cukup baik direpresentasikan oleh model WRF. ABSTRACTHeavy rain in Batam 30-31 January 2011 causes flood. The accumulation of rainfall until 31 January 2011 is 414.5 mm, it exceeds BMKG's threshold about intensity of extreme condition, that more than 50 mm/day. It is related to dynamic of weather's parameter, especially with convection process and clouds. In this case, weather condition analysis uses Weather Research and Forecasting (WRF) Model one domain with 6 kilometer (km) resolution on 1• N and 104 • E. Some weather's parameters show significant result. Their fluctuations prove there is a strong convection that produces convective cloud (Cumulonimbus) so that cloud has a long lifetime and produce rain. Default setting and without nesting on WRF Model show good output to represent weather's condition commonly. Difference between output rainfall rate of observation result and output of model around 6-12 hours is because spinning-up of processing. Satellite Images of MTSAT (Multifunctional Transport Satellite) are used as a verification data to prove the result of WRF. White color of satellite image is Coldest Dark Grey (CDG) that indicate there is cloud's top which temperature lower than -80• C. This image consolidate that the output of WRF is good enough to analyze Batam's condition when the case happened.
The Meteorology, Climatology and Geophysics Agency (BMKG) has a duty to provide weather information including rainfall. BMKG has several types of rainfall gauges, but these are not evenly distributed across regions. The solution to increase the density of rainfall observations is to use existing sources to obtain weather information. This research uses Closed Circuit Television (CCTV) that is spread across the Jakarta area to produce information on rainy conditions. The method used is the Convolutional Neural Network (CNN). The image from CCTV will be used for the training and testing process, so as to get the best accuracy model. The results of this model will be used for rain detection on CCTV digital images. The rain detection process is carried out automatically and in real time. The results of the rain detection process will be displayed on the map according to the location where the CCTV was installed. This research has succeeded in making a CNN model for rain detection with a training accuracy of 98.8% and a testing accuracy of 96.4%, as well as evaluating the BMKG observation data, so it has an evaluation accuracy of 96.7%.
The purpose of this study is to analyze the role of mediators in the me-diation process for efforts to settle civil cases and examine the obstacles faced by mediators in mediating efforts to resolve civil cases. This re-search is an empirical legal research because it identifies the role of mediator. The results show that the effectiveness of the mediator's role in the settlement of civil cases in the Pasuruan District Court has been running well. Mediators consisting of judges and substitute clerks can bridge, reconcile and mediate the problems of the two disputing parties. Based on data in the field, the obstacles that cause failures in the media-tion process are as follows: mediators are still not proactive in carrying out mediation tasks, among others; the disputing parties, outside medi-ators do not understand the mediation procedure in accordance with applicable regulations, there are often disagreements between the dis-puting parties because they focus on winning and losing alone, not a win-win solution for the common good. The mediator must really un-derstand his role as a mediator so that deadlocks or obstacles are not found in the mediation process.DOI: https://doi.org/10.26905/mlj.v2i1.6254
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