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All Journal Jurnal Matematika Specta Journal of Technology Indonesian Journal of Statistics and Its Applications
Muhammad Azka
Institut Teknologi Kalimantan
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Environmental Science Mathematics Other

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Estimasi Dampak Jangka Panjang Kebijakan Penurunan Emisi Terhadap Pertumbuhan Ekonomi Kalimantan Timur Nurul Ilma Hidayanty; Riki Herliansyah; Muhammad Azka
Jurnal Matematika Vol 9 No 1 (2019)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2019.v09.i01.p109

Abstract

Deforestation and forest degradation issue due to economic activity is a major problem in East Borneo. The results of data analysis from Environmental Agency stated East Borneo produced the biggest ammount of CO2 emissions after the Central Borneo and Riau. These emissions mostly come from land-based business sector, industry and transportation. In other side, these sectors are the highest contributor to the total number of Gross Domestic Regional Product (GDRP). The aim of this research is to identify the effect of the goverment policy to decrease CO2 emissions towards economic growth. The data in this research were analyzed using Principal Component Analysis (PCA) and Path Analysis (PA). The results showed that the decrease in the amount of CO2 emissions resulting in decrease in the amount of GDRP. Keywords: CO2 Emissions, Gross Domestic Regional Product (GDRP), Principal Component Analysis, Path Analysis.
Frekuensi Hari Hujan Menurut Bulan di Kota Balikpapan dengan Rantai Markov Waktu Diskrit Muhammad Azka
SPECTA Journal of Technology Vol. 1 No. 2 (2017): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.862 KB) | DOI: 10.35718/specta.v1i2.75

Abstract

The problem proposed in this research is about the amount rainy day per a month at Balikpapan city and discretetime markov chain. The purpose is finding the probability of rainy day with the frequency rate of rainy at the next month if given the frequency rate of rainy at the prior month. The applied method in this research is classifying the amount of rainy day be three frequency levels, those are, high, medium, and low. If a month, the amount of rainy day is less than 11 then the frequency rate for the month is classified low, if a month, the amount of rainy day between 10 and 20, then it is classified medium and if it is more than 20, then it is classified high. The result is discrete-time markov chain represented with the transition probability matrix, and the transition diagram.
Comparison of Short-Term Load Forecasting Based on Kalimantan Data Syalam Ali Wira Dinata; Muhammad Azka; Primadina Hasanah; Suhartono Suhartono; Moh Danil Hendry Gamal
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p243-259

Abstract

This paper investigates a case study on short term forecasting for East Kalimantan, with emphasis on special days, such as public holidays. A time series of load demand electricity recorded at hourly intervals contains more than one seasonal pattern. There is a great attraction in using a modelling time series method that is able to capture triple seasonalities. The Triple SARIMA model has been adapted for this purpose and competitive for modelling load. Using the least squares method to estimate the coefficients in a triple SARIMA model, followed by model building, model assumptions and comparing model criteria, we propose and demonstration the triple Seasonal Autoregressive Integrated Moving Average model with AIC 290631.9 and SBC 290674.2 as the best model for this study. The Triple seasonal ARIMA is one of the alternative strategy to propose accurate forecasts of electricity load Kalimantan data for planning, operation maintenance and market related activities.
Co-Authors Moh Danil Hendry Gamal Nurul Ilma Hidayanty Primadina Hasanah Riki Herliansyah Suhartono Suhartono Syalam Ali Wira Dinata