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Primadina Hasanah
Institut Teknologi Kalimantan
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Journal : Specta Journal of Technology

 1 
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

Abstract

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

Abstract

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.
Prediksi Emisi CO2 dengan Analisis Runtun Waktu Primadina Hasanah; Irma Fitria
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 | Full PDF (864.217 KB) | DOI: 10.35718/specta.v1i1.72

Abstract

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 Irma Fitria; Primadina Hasanah
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 (1078.786 KB) | DOI: 10.35718/specta.v1i2.78

Abstract

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.
Penerapan Regresi Cox Proportional Hazard pada Lama Masa Tunggu Alumni Institut Teknologi Kalimantan Mendapatkan Pekerjaan Shadrina Khairani Arinda; Primadina Hasanah; Nashrul Millah
SPECTA Journal of Technology Vol. 6 No. 2 (2022): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (299.303 KB) | DOI: 10.35718/specta.v6i2.701

Abstract

Berdasarkan data survei angkata kerja yang dilakukan oleh Badan Pusat Statistik pada Februari 2020 diperoleh bahwa tingkat pengangguran lulusan sarjana di Indonesia tercatat sebesar 6,11%. Saat ini, lama masa tunggu alumi untuk mendapat pekerjaan telah menjadi salah satu indikator akreditasi Perguruan Tinggi. Oleh karena itu, melalui penelitian ini akan dianalisis faktor-faktor yang berpengaruh terhadap lama masa tunggu alumni mendapat pekerjaan. Data penelitian diambil dari data masa tunggu alumni Institut Teknologi Kalimantan (ITK) pada tahun kelulusan 2016-2019. Pada penelitian ini dilakukan analisis dengan pendekatan Regresi Cox Proportional Hazard. Variabel yang diduga berpengaruh pada lama masa tunggu alumni mendapatkan pekerjaan antara lain IPK, program studi, organisasi, jenis kelamin, serta kursus. Berdasarkan hasil analisis, didapatkan variabel yang berpengaruh terhadap lama alumni mendapatkan pekerjaan adalah variabel organisasi dan IPK. Model regresi terbaik yang didapatkan adalah hdimana variable  merupakan variabel IPK dan  merupakan variabel aktif organisasi. Interpretasi dari model regresi yang telah didapatkan adalah semakin tinggi IPK alumni, maka semakin besar kesempatan alumni untuk mendapatkan pekerjaan, jika kenaikan IPK alumni 0,1 satuan, maka akan meningkatkan kesempatan 1,0977 kali untuk mendapatkan pekerjaan, sedangkan untuk alumni yang aktif organisasi memiliki kesempatan 3,3387 kali lebih besar untuk mendapatkan pekerjaan dibandingkan alumni yang tidak aktif organisasi.
Co-Authors Achmad, Adha Karamina Anggriani, Indira Annisa Rahmita Soemarsono Annisa Rahmita Soemarsono Auliya, Annisa Nur Chindy Alvionita Sari Eka Qadri Nuranti Filiana, Firilia Fitria, Irma Hargiani, Fransisca Xaveria Ida Ayu Putu Sri Widnyani Indira Anggriani Irma Fitria Isnaniah, Ukhti Nurul Lisa Susanti, Lisa Luh Made Wisnu Satyaninggrat Moh Danil Hendry Gamal Muhammad Azka Muhammad Azka Muhammad Azka Naili Suri Intizhami Nanda Septiana Nashrul Millah NIA FEBRIANTI, NIA Nurjanah, Desi Sasikirana, Sabina Shadrina Khairani Arinda Sigit Pancahayani Siti Qomariyah Nasir Subchan, Subchan Suhartono Suhartono Syalam Ali Wira Dinata Syalam Ali Wira Dinata Winarni Winarni