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Prediksi Emisi CO2 dengan Analisis Runtun Waktu Hasanah, Primadina; Fitria, Irma
SPECTA Journal of Technology Vol 1 No 1 (2017): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v1i1.72

Global warming is caused by various factors, one of them is the emission of CO2. Time series data of CO2 emission will be analyzed using moving average and exponential smoothing to forecast the CO2 emission of the period ahead. Both models provide estimates of forecasting based on the average value of the previous data and can be used for forecasting time series data containing trend component. The best models are selected based on the smallest error value based on the criteria of MAPE, MSD, and MAD

Penerapan Algoritma Kalman Filter dalam Prediksi Kecepatan Angin di Kota Balikpapan Fitria, Irma; Hasanah, Primadina
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 | DOI: 10.35718/specta.v1i2.78

One of the climate?s elements that has an influence on daily activities is the wind speed. Wind is a movement of air that flows from high pressure to low pressure region. In the shipping and aviation, wind speed is a very important thing to predict. This is due to the wind speed is very influential on the process of the transportation activities. A strong wind can disturb the fluency of transportation. Therefore, information regarding the wind speed prediction is very important to know. In this paper, Kalman Filter algorithm is applied in the wind speed prediction by taking the case in Balikpapan. In this case, the Kalman Filter algorithm is applied to improve the result of ARIMA prediction based on error correction, so we get the prediction result, called ARIMA-Kalman Filter. Based on the simulation result in this study, it can be shown that the prediction result of ARIMA-Kalman Filter is better than ARIMA?s. This is known from the level of accuracy from ARIMA-Kalman Filter, which increased about 65% from ARIMA result.

Potensi Sumber Energi Terbarukan dari Biomassa yang Berasal dari Sumber Daya Alam di Balikpapan Febrianti, Nia; Filiana, Firilia; Hasanah, Primadina
Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Vol 17, No 3 (2020): November 2020
Publisher : Universitas Diponegoro

Biomass energy sources have several advantages, such as being used as a renewable energy source so that the energy source from biomass can provide a sustainable energy source. One of the first steps to determine the potential of energy resources that can be developed into renewable energy sources is by collecting data. The data collection carried out in this study focuses more on the biomass found in Balikpapan. The biomass potential in Balikpapan needs to be known by collecting and classifying the biomass data based on products from agriculture and plantations. The data that has been collected from secondary data and from surveys are then mapped to see the greatest biomass potential found in Balikpapan. The largest percentage of crop yields per year is found in North Balikpapan Subdistrict, which is 31% compared to five other sub-districts. The potential of biomass from Balikpapan City's natural resources, which the greatest amount of harvest, is the cassava food plant in North Balikpapan sub-district of 7,259 tons / year. In the type of fruit, snakefruit (salak) has the highest number of yields per year, which is about32,945 tons / year. The potential for waste from food plants, cassava waste originating from tree trunks, is 5,807.2 tons / year, and cassava skin is 1,088.8 tons / year

PERAMALAN SUHU UDARA DAN DAMPAKNYA TERHADAP KONSUMSI ENERGI LISTRIK DI KALIMANTAN TIMUR Susanti, Lisa; Hasanah, Primadina; Winarni, Winarni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 3 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : MATHEMATIC DEPARTMENT, FACULTY OF MATHEMATICS AND NATURAL SCIENCES, UNIVERSITY OF PATTIMURA

The increase in air temperature due to climate change and global warming has become a major concern for policy makers, one of which is the government of East Kalimantan. Electric energy consumption has a close relationship with economic development in East Kalimantan. So it is necessary to forecast the temperature of air in order to predict the consumption of electrical energy in the future. The purpose of this study was to determine the forecasting of air temperatures in East Kalimantan, namely the cities of Balikpapan, Samarinda and Berau and to determine the relationship between air temperature and electricity consumption in East Kalimantan. In this study, the method used is the ARIMA (Autoregressive Integrated Moving Average) and multiple linear regression methods. The results of the analysis using the ARIMA method obtained the best models for the cities of Balikpapan, Samarinda and Berau respectively, namely ARIMA(1,1,1), ARIMA(1,1,1) and ARIMA(3,1,0). Based on the results of multiple linear regression obtained R-square value of 39%, which mean that the influence of air temperature on the consumption of electrical energy is 39%. From the results of the t test and F test, it is known that air temperature has a significant effect on the increase in electricity consumption in East Kalimantan

Gold Return Volatility Modeling Using Garch Primadina Hasanah; Siti Qomariyah Nasir; Subchan Subchan
Indonesian Journal of Mathematics Education Vol 2, No 1 (2019): Indonesian Journal of Mathematics Education
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/ijome.v2i1.1222

This research aims to resolve the heteroscedasticity problem in time series data by modeling and analyzing volatility the gold return using GARCH models. Heteroscedasticity means not the constant variance of residuals. The sample data is a return data from January 1, 2014 to September 23, 2016. The data analysis technique used is a stationary test, model identification, model estimation, diagnostic check, heteroscedasticity test, GARCH model estimation, and evaluation. The results showed that ARIMA (3,0,3)-GARCH (1.1) is the best model.

Analisis Volatilitas Harga Saham Sekor Minyak dan Gas di Indonesia pada Masa Pandemi Covid-19 dengan Metode ARIMA-GARCH Septiana, Nanda; Primadina Hasanah; Annisa Rahmita Soemarsono
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 2 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

Pandemi Covid-19 memberi dampak yang signifikan terhadap berbagai sektor industri di Indonesia salah satunya saham sektor pertambangan Minyak Mentah dan Gas Bumi (MIGAS). Hal ini ditunjukkan pada penurunan harga minyak yang turun di bawah $40 USD dan aktivitas eksplorasi di Indonesia menurun lebih dari 40% dibanding sebelum pandemi Covid-19. Selama pandemi, harga saham sektor pertambangan MIGAS mengalami volatilitas yang cukup tinggi sehingga cukup meresahkan sektor investasi di Indonesia. Oleh karena itu, diperlukan suatu prediksi volatilitas harga saham sektor pertambangan MIGAS agar mampu memberikan informasi terhadap investor untuk melakukan manajemen portofolio. Pada penelitian ini, dianalisis volatilitas harga saham empat perusahaan pertambangan MIGAS, yaitu PT. Apexindo Pratma Duta (APEX), PT. Elnusa (ELSA), PT. Medco Energi Internasional (MEDC), dan PT. Radiant Utama Interinsco (RUIS) pada tanggal 01 Maret 2020 - 28 Februari 2021 dengan metode ARIMA-GARCH. Pada proses analisis, digunakan RStudio dengan pembentukan model ARIMA dilakukan terlebih dahulu kemudian dilanjutkan pembentukan model ARIMA-GARCH jika model ARIMA terdapat gejala heteroskedastisitas. Hasil dari penelitian ini, pada saham APEX, ELSA, dan RUIS terdapat gejala heteroskedastisitas pada model ARIMA dan didapatkan model ARIMA GARCH untuk perusahaan APEX, ELSA dan RUIS serta model ARIMA untuk perusahaan MEDC. Berdasarkan hasil analisis, diperoleh bahwa terdapat asumsi autokorelasi, normalitas, dan heteroskedastisitas yang belum terpenuhi pada uji diagnostik. Niilai MAPE untuk APEX, ELSA, MEDC, dan RUIS, yaitu , , , dan . Dari hasil akurasi peramalan yang didapatkan, terdapat nilai MAPE di atas 10%, yaitu pada model APEX dan ELSA sehingga model tersebut belum dapat dikatakan baik untuk peramalan. Kata kunci : ARIMA, GARCH, Volatilitas Harga Saham

Penerapan Permainan matematika di SDN 008 Balikpapan Utara Kota Balikpapan untuk Meningkatkan Minat Siswa dalam Belajar Matematika Muhammad Azka; Primadina Hasanah; Sigit Pancahayani; Indira Anggriani
Buletin Pembangunan Berkelanjutan Vol. 4 No. 2 (2020)
Publisher : UIR Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Pada tingkat dasar, siswa mempelajari dasar-dasar operasi hitung matematika yang meliputi penjumlahan, pengurangan, perkalian dan pembagaian baik pada operasi bilangan bulat maupun pecahan yang seringkali membuat siswa bingung dan kurang berminat mempelajarinya. Kondisi ini perlu diwaspadai dikarenakan masih sering dijumpai siswa tingkat menengah yang tidak memahami operasi hitung pecahan. Di lain pihak, stigma yang terjadi di masyarakat Indonesia pada umumnya adalah matematika merupakan pelajaran yang paling sulit. Untuk mengatasi permasalahan tersebut, maka perlu dilakukan upaya pengembangan suatu metode pembelajaran dengan mengimplementasikan suatu bentuk permainan pada pembelajaran matematika. Metode permainan yang digunakan dalam meningkatkan pemahaman dan minat belajar matematika ini diadopsi dari permainan ular tangga dan kartu UNO, yang mana permainan-permainan ini sudah dikenal oleh anak-anak. Berdasaran kegiatan yang telah dilaksanakan dapat diambil kesimpulan bahwa metode permainan sangat disukai oleh siswa SDN 008 Balikpapan Utara dalam meningkatkan minat belajar matematika.

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

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.

Analisis Volatilitas Harga Saham Sekor Minyak dan Gas di Indonesia pada Masa Pandemi Covid-19 dengan Metode ARIMA-GARCH Nanda Septiana; Primadina Hasanah; Annisa Rahmita Soemarsono
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 2 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

Pandemi Covid-19 memberi dampak yang signifikan terhadap berbagai sektor industri di Indonesia salah satunya saham sektor pertambangan Minyak Mentah dan Gas Bumi (MIGAS). Hal ini ditunjukkan pada penurunan harga minyak yang turun di bawah $40 USD dan aktivitas eksplorasi di Indonesia menurun lebih dari 40% dibanding sebelum pandemi Covid-19. Selama pandemi, harga saham sektor pertambangan MIGAS mengalami volatilitas yang cukup tinggi sehingga cukup meresahkan sektor investasi di Indonesia. Oleh karena itu, diperlukan suatu prediksi volatilitas harga saham sektor pertambangan MIGAS agar mampu memberikan informasi terhadap investor untuk melakukan manajemen portofolio. Pada penelitian ini, dianalisis volatilitas harga saham empat perusahaan pertambangan MIGAS, yaitu PT. Apexindo Pratma Duta (APEX), PT. Elnusa (ELSA), PT. Medco Energi Internasional (MEDC), dan PT. Radiant Utama Interinsco (RUIS) pada tanggal 01 Maret 2020 - 28 Februari 2021 dengan metode ARIMA-GARCH. Pada proses analisis, digunakan RStudio dengan pembentukan model ARIMA dilakukan terlebih dahulu kemudian dilanjutkan pembentukan model ARIMA-GARCH jika model ARIMA terdapat gejala heteroskedastisitas. Hasil dari penelitian ini, pada saham APEX, ELSA, dan RUIS terdapat gejala heteroskedastisitas pada model ARIMA dan didapatkan model ARIMA GARCH untuk perusahaan APEX, ELSA dan RUIS serta model ARIMA untuk perusahaan MEDC. Berdasarkan hasil analisis, diperoleh bahwa terdapat asumsi autokorelasi, normalitas, dan heteroskedastisitas yang belum terpenuhi pada uji diagnostik. Niilai MAPE untuk APEX, ELSA, MEDC, dan RUIS, yaitu , , , dan . Dari hasil akurasi peramalan yang didapatkan, terdapat nilai MAPE di atas 10%, yaitu pada model APEX dan ELSA sehingga model tersebut belum dapat dikatakan baik untuk peramalan. Kata kunci : ARIMA, GARCH, Volatilitas Harga Saham

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

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.

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