Judul: The Phenomenon of Pollution Haze and Its Relationship with PM2.5 Concentration Fluctuations in Urban Areas (Case Study: Jakarta)
Abstrak: Fenomena haze di DKI Jakarta menjadi masalah besar karena berdampak terhadap gangguan jarak pandang dan peningkatan risiko penyakit pernapasan. Pengaruh emisi antropogenik menghasilkan partikel udara kering yang dapat bercampur dengan gas-gas di atmosfer dan membentuk haze atau udara kabur. Penelitian ini bertujuan untuk menganalisis hubungan antara kejadian haze dan tingkat konsentrasi PM2.5, serta ketinggian lapisan inversi sebagai faktor pendukung. Data yang digunakan merupakan data luaran model ECMWF konsentrasi PM2.5, kode SYNOP haze, arah angin, curah hujan, dan tinggi lapisan inversi pada bulan September 2021 sampai Agustus 2023 yang dianalisis melalui visualisasi grafik, korelasi, dan regresi linier serta menggunakan Minitab 20 dan RStudio 4.2.0. Analisis ini menggunakan data pada wilayah Stasiun Meteorologi Soekarno-Hatta dengan asumsi dapat mewakili kondisi wilayah dan studi kasus di DKI Jakarta. Hasil penelitian menunjukkan frekuensi kejadian haze semakin intensif ketika ketinggian lapisan inversi terjadi di bawah 200 m bersamaan dengan tingkat konsentrasi PM2.5 di atas 60 µg/m3. Analisis hubungan keeratan kejadian haze menggunakan regresi linier berganda memiliki koefisien determinasi (R2) sebesar 65%, namun hasil p-value tinggi lapisan inversi tidak signifikan dengan kejadian haze (p-value>0,05), sedangkan konsentrasi PM2.5 signifikan kaitannya dengan kejadian haze (p-value<0,05)., The haze phenomenon in Jakarta has become a major problem due to its impact on visibility disturbances and the increased risk of respiratory diseases. The influence of anthropogenic emissions produces dry air particles that can mix with gases in the atmosphere and form haze. This study aims to analyze the relationship between haze events and PM2.5 concentration levels, as well as the height of the inversion layer as a supporting factor. The data used includes PM2.5 concentration output from the ECMWF model, SYNOP haze code, wind direction, rainfall, and inversion layer height from September 2021 to August 2023, which are analyzed through graphical visualization, correlation, and linear regression using Minitab 20 and RStudio 4.2.0. This analysis uses data from the Soekarno-Hatta Meteorological Station with the assumption that it can represent the conditions in Jakarta. The results show that the frequency of haze events becomes more intensive when the inversion layer height is below 200 m along with PM2.5 concentration levels above 60 µg/m3. The relationship analysis using multiple linear regression has a coefficient of determination (R2) of 65%, but the p-value for the inversion layer height is not significant with haze events (p-value>0.05), whereas the PM2.5 concentration is significantly related to haze events (p-value<0.05).
Keyword: antropogenik, atmosfer, jarak pandang, lapisan inversi, signifikan

Judul: Influence of Meteorological Factors on PM2.5 and PM10 Concentration Fluctuation (Case Study: Jakarta)
Abstrak: Jakarta sebagai ibukota negara Indonesia merupakan salah satu kota dengan aktivitas penduduk, transportasi dan industri yang tinggi. Hal ini mendorong semakin tingginya pencemaran udara di Jakarta. Terdapat berbagai faktor yang mempengaruhi pencemaran udara, salah satunya faktor meteorologi. Faktor meteorologi dapat mempengaruhi fluktuasi konsentrasi polutan di udara, seperti suhu udara, kelembaban, curah hujan, radiasi, kecepatan dan arah angin. Penelitian ini bertujuan untuk mengetahui fluktuasi konsentrasi PM2.5 dan PM10 di Jakarta serta interaksi antara faktor meteorologi dengan konsentrasi partikulat. Interaksi antara faktor meteorologi dan konsentrasi partikulat ditunjukkan melalui korelasi pearson dan menggunakan package openair di RStudio. Hasil penelitian menunjukkan konsentrasi PM2.5 dan PM10 di Jakarta memiliki puncak pada siang hari, menurun saat menuju sore hari dan kembali meningkat pada saat menuju malam hari. Interaksi antara faktor meteorologi dengan konsentrasi PM2.5 dan PM10 di Jakarta berkorelasi positif dengan suhu dan radiasi, serta berkorelasi negatif dengan kelembaban, curah hujan dan kecepatan angin. Secara bulanan konsentrasi PM di bulan kering lebih tinggi daripada di bulan basah., Jakarta as the capital city of Indonesia is one of the cities with high population, transportation, and industrial activity. This has led to higher air pollution in Jakarta. There are various factors that influence air pollution, one of which is meteorological factors. Meteorological factors will affect the fluctuation of pollutant concentrations in the air, such as air temperature, humidity, rainfall, radiation, wind speed and wind direction. This study aims to see the fluctuation of PM2.5 and PM10 concentrations in Jakarta and the interaction between meteorological factors and PM concentrations. The interaction between meteorological factors and PM concentrations was shown through Pearson correlation and using the openair package in RStudio. The results showed that the concentrations of PM2.5 and PM10 in Jakarta had a peak during the day, decreases towards the afternoon and increases towards the evening. The interaction between meteorological factors and concentrations of PM2.5 and PM10 in Jakarta has a positive correlation with temperature and radiation, and negatively correlates with humidity, rainfall and wind speed. On a monthly basis, PM concentration will increase in dry months and decrease in wet months.
Keyword: concentration, correlation, meteorology, PM2.5, PM10

Judul: Construction of Strongly Optimal Binary Linear Code with Minimum Distance 9 and 11
Abstrak: A binary linear code of length n over q F is a subspace of n q F . A code has three parameters that attached to it, namely length, dimension, and minimum distance. A code with length n, dimension k and minimum distance d is often called [n, k, d ]-code. Usually, when two parameters are given, then we want to find a code that has the best value for the last parameter. Based on Gilbert- Varshamov bound, if a [n, k, d ]-code exists and can not be expanded, we call it a strongly optimal code. In this paper, we construct strongly optimal code with minimum distance 9 and 11. In constructing the code, we created a theorem and algorithm based on Gilbert-Varshamov bound before we implement the algorithm to MAPLE programming language. Because of computational limitations, the program can only construct up to k = 10 for d = 9 and k = 12 for d = 11.
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