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"Sistem pemantauan cuaca otomatis (AWS), telah dibuat untuk memantau cuaca di stasiun cuaca. Sistem dilengkapi oleh 4 buah sensor, yaitu : MPXAZ4115A untuk mengukur tekanan udara, SHT11 untuk mengukur suhu udara dan kelembaban relatif, serta optocoupler untuk mengukur kecepata angin. Data dari sensor kemudian akan diolah di dalam mikrokontroler, lalu ditampilkan secara real time melalui GUI (Graphic User Interface) dengan bahasa pemrograman Python 2.6. Mikrokontroler yang digunakan dalam sistem ini yaitu H8-3069F. Akses atau pengiriman data dilakukan menggunakan kabel yang terhubung ke komputer yang terletak di stasiun cuaca terdekat. Setiap data yang masuk akan tersimpan dalam bentuk file csv (comma, separated, values).

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A weather monitoring system has been designed to enable observers to monitor weather parameters in weather station. This system is commonly referred to as AWS (Automatic Weather Station), which is an amalgamation of several of the sensors. This study used four sensors namely : air pressure, temperature, air humidity and wind speed. Data from sensors will then be processed in the microcontroller, and then displayed in real time via the GUI (Graphic User Interface) with Python 2.6 programming language. Microcontroller used in this system is H8-3069F. Access or data transfer can be done using cable that has been connected to the computer that placed in the nearest weather station. Each incoming data is stored in the form of a csv file (comma, separated, values)."

"Bidirectional Long-Short Term Memory (BiLSTM) yang merupakan perpanjangan dari LSTM dimana dapat meningkatkan efisiensi model dan akurasi pada skenario klasifikasi berdasarkan time series data atau data deret waktu yang lebih panjang secara berulang. Penelitian ini menggunakan algoritma BiLSTM untuk membangun model prakiraan cuaca harian di Bandar Udara Internasional Soekarno-Hatta. Set data yang digunakan adalah data parameter cuaca udara permukan (synoptic) per jam Stasiun Meteorologi Kelas 1 Soekarno-Hatta periode Januari 2018 – Desember 2022. Terjadi ketidakseimbangan pada set data maka digunakan teknik SMOTE dan ADASYN untuk menangani masalah tersebut. Output penelitian ini adalah kondisi cuaca yang dikategorikan menjadi cerah, cerah berawan, berawan, hujan ringan, hujan sedang, hujan lebat, dan hujan petir. Hasil yang diperoleh akan melalui verifikasi dan evaluasi model dengan mencari nilai akurasi dengan membandingkan prakiraan cuaca hasil output model dengan data cuaca aktual menggunakan tabel kontingensi multikategori. Setelah mendapatkan hasil perbandingan akurasi masing-masing model, diperoleh Model BiLSTM – ADASYN mendapatkan nilai akurasi rata-rata tertinggi dibandingkan model lainnya, yaitu sebesar 83,2%. Penelitian ini diharapkan dapat diimplementasikan dan mampu menaikan nilai verifikasi prakiraan cuaca Bandar Udara Soekarno-Hatta demi mendukung keselamatan penerbangan di Indonesia.

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Bidirectional Long-Short Term Memory (BiLSTM) which is an extension of LSTM which can improve model efficiency and accuracy in classification scenarios based on time series data or longer time series data repeatedly. This study uses the BiLSTM algorithm to build a daily weather forecast model at Soekarno-Hatta International Airport. The data set used is hourly synoptic weather parameter data for Class 1 Soekarno-Hatta Meteorological Station for the period January 2018 – December 2022. There was an imbalance in the data set, so the SMOTE and ADASYN techniques were used to deal with the problem. The output of this research is weather conditions which are categorized into sunny, sunny, cloudy, cloudy, light rain, moderate rain, heavy rain, and thunderstorms. The results obtained will go through model verification and evaluation by looking for accuracy values ​​by comparing the weather forecast output model results with actual weather data using multi-category contingency tables. After getting the results of comparing the accuracy of each model, it was obtained that the BiLSTM – ADASYN model had the highest average accuracy value compared to other models, which was 83.2%. This research is expected to be implemented and able to increase the value of weather forecast verification at Soekarno-Hatta Airport in order to support flight safety in Indonesia."

"Weird weather : tales of astronomical and atmospheric anomalies is about strange, unusual, and apparently inexplicable observations of the air and sky. Primarily these are in the earth's atmosphere, but there are corresponding phenomena in the atmospheres of other planets of the solar aystem, lightning on venus, jupiter, and saturn, whirlwinds and dust storms of mars, and auroras on jupiter. Topics include anomalous lights, anomalous sounds, spectacular effects of cloud illumination by the Sun or Moon, lightning phenomena, electrophonic sounds of lightning, aurora and meteors, tornado and whirlwind phenomena on Earth and Mars, usual atmospheric effects, mirages, and the possible astronomical influences on cloud and climate."