Judul: Estimation of Particulate Pollutant Source Contribution in Bandung City Area using HYSPLIT CWT Model
Abstrak: Kota Bandung, sebagai salah satu kota metropolitan dan pariwisata di Jawa Barat, berpotensi mengalami peningkatan aktivitas antropogenik yang dapat mempengaruhi kualitas udara. Salah satu parameter penting yang berpengaruh terhadap kesehatan masyarakat adalah partikulat. Penelitian ini bertujuan menganalisis karakteristik konsentrasi partikulat di Kota Bandung dan estimasi sumber emisi potensialnya menggunakan model HYSPLIT backward trajectory dan Concentration Weighted Trajectory (CWT). Hasil analisis menunjukkan rata-rata konsentrasi partikulat selama tahun 2020-2023 mengalami peningkatan, terutama pada tahun 2023. Konsentrasi rata-rata PM2.5 bahkan sudah melampaui nilai BMUA 1 tahun. Analisis antar musim menunjukkan bahwa konsentrasi partikulat pada musim hujan lebih rendah dibandingkan musim kemarau. Pola konsentrasi diurnal menunjukkan pola dua puncak dengan puncak pertama di pagi hari pada pukul 08.00 WIB dan puncak kedua di malam hari pada pukul 22.00 WIB¬. Konsentrasi maksimum pada pagi hari lebih tinggi dibandingkan konsentrasi maksimum pada malam hari. Berdasarkan analisis HYSPLIT CWT, persentase massa udara yang memasuki Kota Bandung pada musim hujan didominasi dari Purwakarta, Cianjur, Bandung Barat, dan Cimahi (24-44%). Sementara itu, pada musim kemarau persentase massa udara didominasi dari Sumedang, Garut, dan Kabupaten Bandung (36-98%). Aliran massa udara tersebut melalui sumber emisi potensial berupa kawasan industri, pariwisata, dan rute padat transportasi. Distribusi CWT selama musim kemarau menunjukkan konsentrasi PM10 mencapai 45-50 µg/m³, sedangkan konsentrasi PM2.5 mencapai 40-45 µg/m³. Sementara itu, distribusi CWT tertinggi pada musim hujan bernilai 25-30 µg/m³ untuk PM10 dan 20-25 µg/m³ untuk PM¬2.5., Bandung City, as one of metropolitan and tourism cities in West Java, has a potential to has an increase on anthropogenic activites that can affect air quality. One of crusial parameter for public health is particulate matter. This study aims to analyze the characteristics of particulate concentrations in Bandung City and estimate the potential emission sources using HYSPLIT backward trajectory and Concentration Weighted Trajectory (CWT) model. The analysis showed that the average of particulate concentration during 2020-2023 has increased, especially in 2023. The PM2.5 concentration has even exceeded the 1-year AQI value. Inter-seasonal analysis showed that particulate concentrations in the rainy season are lower than the dry season period. The diurnal concentration pattern showed a two peak pattern with the first peak in the morning at 8.00 AM and the second peak in the evening at 22.00 PM. The maximum concentration in the morning was higher than the maximum concentration at night. Based on the HYSPLIT CWT analysis, the air mass percentation that entered Bandung City in rainy season came from Purwakarta, Cianjur, West Bandung, and Cimahi (24-44%). Meanwhile, the air mass percentation in dry season came from Sumedang, Garut, and Bandung Regency (36-98%). Those air mass flowed through potential emission sources such as industrial area, tourism area, and heavy route transportation. CWT distribution during the dry season showed PM10 concentration reached 45-50 µg/m³, while PM2.5 concentration reached 40-45 µg/m³. Meanwhile, the highest CWT distribution during the rainy season was 25-30 µg/m³ for PM10 and 20-25 µg/m³ for PM2.5.
Keyword: backward trajectories, HYSPLIT, CWT, particulate matter

Judul: Contribution of Long-Range Transport Towards PM 2.5 Concentration (Study Case: Baranangsiang, Bogor)
Abstrak: Fenomena long-range transport (LRT), merupakan pengangkutan polutan dari daerah lain dengan jarak lebih dari 100 km. Perlu dilakukan identifikasi potensi sumber PM2.5 dan melihat fluktuasi konsentrasi PM2.5 di Kota Bogor. LRT dapat divisualisasikan menggunakan lintasan mundur HYSPLIT dan klustering. Selain itu, metode Potential source contribution function (PSCF) digunakan untuk menilai probabilitas dan metode Concentration weighted trajectory CWT untuk melihat nilai konsentrasi dominan. Sumber potensial dan tingkat konsentrasi dapat bervariasi berdasarkan musim di wilayah tersebut. Pada bulan kering sumber polutan dominan berasal dari arah timur-tenggara sebesar 57.7% dan pada bulan basah berasal dari arah barat-barat daya sebesar 67.1%. dan 32.9 %. Konsentrasi maksimum rataan bulanan PM2.5 di Kota Bogor terjadi pada bulan Juli dengan nilai sebesar 25 µg/??3 dan minimum pada bulan November sebesar 10 µg/ ??3 . Secara umum faktor kecepatan angin curah hujan, dan kelembaban memiliki hubungan yang negatif dengan PM2.5. Jika kecepatan angin tinggi maka polutan akan rendah, curah hujan tinggi maka konsentrasi menurun, dan kelembaban tinggi konsentrasi akan turun., The phenomenon of long-range transport (LRT) is that pollutants can be transported from other areas. Identify the potential source of PM2.5 in Bogor City and see the fluctuation of concentration of PM2.5in Bogor City. Transport distance with a backward trajectory using the HYSPLIT model, clustering. Use PSCF for knowing probability and knowing concentration using CWT method. It is important to understand potential sources and concentration levels may vary seasonally in the region, potential sources will follow the season of the area. The dry month was the dominant pollutant from east-southeast was 57.7% and in the wet month from the west-southwest 67.7%. Concentration of PM2.5in Bogor City maximum is 25 µg/??3 and the minimum is 10 µg/??3 in July. Because meteorology factors can impact, such as wind, humidity, and rainfall, they have a negative correlation. If humidity and wind increased the concentration will be decreased, rainfall increases the concentration will be decreased.
Keyword: Concentration weighted trajectory, Long-range transport, PM2.5, Potential Source Contribution Function

Judul: The Exploration of Discrete Logarithm over Finite Field GF(3m)
Abstrak: The security of many public~key algorithms is based on the problem of finding discrete logarithms. The generalized discrete logarithm problem is the following: given a finite cyclic group G of order n, a generator a of G, and an element fl E G, find the integer x, 0 ~ x ~ n - 1, such that 0: = fl. Algorithm for discrete logarithm problem focused on Menezes et al. (1997) that consist of exhaustive search algorithm, the baby-step giant-step algorithm, Pollard's rho algorithm, Pohlig-Hellman algorithm, and index-calculus algorithm. These algorithms are explorated to be used in discrete logarithm problem over finite field GF(3m ). The exploration also produces some algorithms, i.e. naif negative algorithm, baby-step mother-step algorithm, baby-step mother free-step algorithm, and baby-step free-step algorithm. All algorithms implemented using Maple 11. The Pohlig-Hellman and baby-step giant-step algorithms are efficient enough to be used in discrete logarithm problem over finite field GF(3m ) for m < 20.
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