El Nino is a global climate phenomenon caused by the warming of sea surface temperatures in the eastern Pacific Ocean. El Nino has a powerful effect on the intensity of rainfall in several areas in Indonesia. El Nino impacts can be minimized by predicting the El Nino index from the sea surface temperature in the Nino 3.4 area. Therefore, many researchers have tried to predict sea surface temperature, and many prediction data are available, one of which is ECMWF. But, in reality, the ECMWF data still contains systematic errors or bias towards the observations. Consequently, El Nino predictions using ECMWF data are less accurate. For that reason, this study aims to correct the ECMWF data in the Nino 3.4 area using statistical bias correction with a quantile mapping approach. This method uses ECMWF data from 1983-2012 as training data and 2013-2018 as testing data. For this case, the results showed that 60% of El Nino's predictions on the testing data had improved the mean value. Also, all of El Nino's predictions on the testing data have improved the standard deviation value. Moreover, data testing's expected error can be corrected for all months in the 1st to 4th lead times. But, in the 5th to 7th lead times, only November-June can be corrected.
Rainfall patterns in Kalimantan are generally divided into 2 types, namely monsoonal and equatorial. The pattern can be determined by analyzing the 6-month frequency of rainfall signal. This analysis has been carried out on general data in Indonesia, but no one has yet examined it in detail in Kalimantan. Therefore, this study will analyze the 6-month frequency signal and rainfall patterns spatially and temporally in Kalimantan using TRMM 3B42RT as the main data. The Fast Fourier Transform (FFT) method is applied to analyze the 6-month frequency of rainfall signal, while the Empirical Orthogonal Function (EOF) method is applied to reduce data and obtain the main pattern of rainfall in Kalimantan. The results of FFT analysis in 15 cities of Kalimantan show that the rainfall pattern in Samarinda, Sendawar, Tarakan, Tanjungselor, Malinau, Pangkalanbun, Pontianak, Ketapang, and Sintang are an equatorial type, while a monsoonal type appear in Balikpapan, Palangkaraya, Purukcahu, Banjarmasin, Kotabaru and Barabai. Moreover, based on the results of FFT and EOF analysis, most areas in West, East and North Kalimantan have an equatorial rainfall pattern. Meanwhile, most areas in Central and South Kalimantan have a monsoonal rainfall pattern.
Article is written using microsoft word, A4 paper, one column, Times New Roman font (14 size for title and 12 size for body text), single spacing. Upper/bottom/right margin is 3 cm and left margin is 4 cm (mirrored margin). No more than 20 pages.Abstract is written in English or Indonesian, no more than 250 words.
This paper considers the effect of a hard-wall beach on the downstream side of submerged parallel bars in a breakwater. In previous research, it was assumed that the beach can absorb all of the transmitted wave energy, when an optimal dimension for a submerged parallel bar is obtained and the wave amplitude is reduced as more bars are installed. However, for a hard-wall beach there are waves reflected from the beach that change the long-term wave interaction. We adopt the linear shallow water equations in Riemann invariant form and use the method of characteristics, in a procedure applicable to various formations of submerged rectangular bars. The distance from the parallel bar (or bars) to the beach determines the phase differences between right running waves in the beach basin and whether they superpose destructively or constructively before hitting the beach, to define the safest and the most dangerous cases. Our numerical calculations for one bar, two bars and for periodic rectangular bars confirm the analytical formulae obtained.
In this paper, we predicted whether a student succeed to pass their higher education on time or not based on Grade Point Average (GPA) and several indicators related to final year project activities. It was also analysed which indicator that is dominant based on its resulted weight. The process was conducted by using perceptron method, while the data was taken from students of Department of Mathematics, IPB University, enrolled in 2013, 2014 and 2015. Furthermore, the results showed that learning proses accuracy stand at 80.5 % and all mentioned indicators give a positive contribution to students in pursuing on-time graduation except supervised by the lecturer whose field of interest is in line with the student. Additionally, based on the resulted weight for each indicator, student’s GPA has a bigger impact for student to graduate on time.
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