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Journal : JAMBURA JOURNAL OF PROBABILITY AND STATISTICS

PENGGUNAAN RESAMPLING DALAM PENGGAMBARAN QUICK COUNT ADI SETIAWAN
Jambura Journal of Probability and Statistics Vol 1, No 1 (2020): Jambura Journal of Probability and Statictics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v1i1.5643

Abstract

In this paper a descriptive statistical analysis of the results of the 2019 presidential election was presented related to the quick count result. Descriptive statistical analysis was also conducted on the results of the 2019 presidential election in Salatiga City (Central Java province), Solok City (West Sumatra province) and Rejang Lebong Regency (Bengkulu province). The resampling method is used to illustrate how the quick count method can be explained for finite populations in Salatiga City, Solok City and Rejang Lebong Regency. By using resampling, the percentage obtained by the Jokowi-Amin pair in Salatiga, Solok and Rejang Lebong are 78.05%, 87.86% and 56.85%, whereas the reality for the three cities in a row is 78.03%; 87,79% and 56.36%.
PERBANDINGAN HASIL PERAMALAN JUMLAH WISATAWAN MANCANEGARA DENGAN METODE BOX-JENKINS DAN EXPONENTIAL SMOOTHING SARI, EMMA NOVITA; SUSANTO, BAMBANG; SETIAWAN, ADI
Jambura Journal of Probability and Statistics Vol 2, No 1 (2021): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v2i1.9181

Abstract

Forecasting the number of tourist visits is needed by tourism businesses to provide an overview of the number of tourists in the future so that problems that might occur can be overcome properly. This study aims to compare the results of forecasting the number of foreign tourists using the Box-Jenkins and Exponential Smoothing methods. There are two data used, namely data on the number of foreign visitors visiting Indonesia from January 2008 to December 2017 (Data I) and Bali according to the entrance of Ngurah Rai Airport from January 2009 to March 2020 (Data II). The best forecast results are obtained by comparing the Root of Mean Square Error (RMSE) values. The comparison of forecasting results in Data I shows that the Holt-Winters Exponential Smoothing method is more appropriate to predict the number of foreign tourists visiting Indonesia because it has a smaller RMSE value. While, the results of forecasting periods 2 and 3 in Data II show results that are far different from the original data. After tracking, it turns out this is caused by an unexpected factor, the Covid-19 pandemic which caused the number of tourists to drop significantly during this period.
Prediksi Laju Inflasi dengan Metode Long Short-Term Memory (LSTM) Berdasarkan Data Laju Inflasi dan Pengeluaran Kota Ternate masipupu, Frangky Aristiadi; setiawan, Adi; Susanto, Bambang
Jambura Journal of Probability and Statistics Vol 6, No 1 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i1.30627

Abstract

Inflation is one of the main indicators that reflect the economic stability of a region. Ternate City, as one of the cities in North Maluku Province, exhibits fluctuating inflation dynamics from year to year. This study aims to forecast the inflation rate in Ternate using the Long Short-Term Memory (LSTM) method, which is a neural network architecture well-suited for processing time series data. The data used consists of monthly Consumer Price Index (CPI) figures for Ternate from 2016 to 2023, obtained from the Central Bureau of Statistics (BPS). The LSTM model was trained using monthly CPI changes as the basis for calculating inflation. The model evaluation results show a Root Mean Square Error (RMSE) of 0.9275, Mean Absolute Error (MAE) of 0.8369, and Mean Absolute Percentage Error (MAPE) of 20.13%. These results indicate that the LSTM model performs well in forecasting inflation in Ternate City and can be utilized as a decision-support tool in regional economic planning and policymaking.   
Co-Authors Adella Septiana Mugirahayu Aldian Umbu Tamu Ama Alfida Tegar Nurani Alicia Anggelia Lumbantoruan ALOYSIUS JOAKIM FERNANDEZ Ariani, Dwi Setya Atina Rahmatalia Bambang Susanto Baskoro Arie Nugroho Bayu Wijayanto Beni Utomo Christiana Hari Soetjiningsih Christina Maya Indah Susilowati D. B. Nugroho, D. B. Daivi Wardani, Daivi Delsylia Tresnawaty Ufi Denny Indrajaya Denny Indrajaya Deswita, Yenny Dewi Anisa Istiqomah Dewi Lukitasari Didit Budi Nugroho Djoko Hartanto E. D. Saputri, E. D. Eko Sediyono Elsa Septyana Endang Sulistyaningsih Faldy Tita Fika Widya Pratama Florentina Tatrin Kurniati Haay, Happy Alyzhya Hanna Arini Parhusip Hari Slamet Trianto Hari Slamet Trianto Hariyanto Hariyanto Hartiningsih, Tri Hasibuan, Zulfikar Henderi . Henry Junus Wattimanela I Nyoman Suartha Ignatius Agus Supriyono Ilham Hizbuloh Irwan Sembiring Iwan Setiawan Iwan Setyawan Joko Siswanto Joni Murti Mulyo Aji JT Lobby Loekmono Keo, Jitro Jemryes Khan, Nani Siska Putri Kholifah, Izzah Nurul Kurniawan, Johanes Dian Kurniawan, Titus Antonius David Leipary, Harfely Leonardo Refialy Leonardo Refialy, Leonardo Leopoldus Ricky Sasongko Lilik Linawati Lindin Anderson Luh Made Sudimartini Luh Putu Suciati Lukman Hakim Lydia Soepriyani Fallo masipupu, Frangky Aristiadi Meydelina, Gloria Migunani Migunani Mitha Febby R. Donggori Mitha Febby R. Donggori Modjo, Marchella Ellena Mohammad Ridwan Muhammad Muhammad Nafisah Riskya Hasna Ni Nyoman Werdi Susari Ninda Lutfiani Olivia Rumahpasal Pariama, Aprillia Mauren Pradani, Wynona Adita Priatna , Wowon Purbaratri, Winny Purwoko, Agus Putu Devi Jayanti Qurotul Aini Rachayu, Laras Andriani Rachel Wulan Nirmalasari Wijaya Ramadhana, Varotama Putra Riana Dewi Riskina, Shafira Romauli Basaria Roy Rudolf Huizen Rudhito, Andy Salomina Patty Saputri, Cut Rahmah SARI, EMMA NOVITA Setivani, Febi Sri Suwartiningsih Sulistio Sulistio Suryasatriya Trihandaru Sutarto Wijono Tamaela, Jemaictry Theo Sarita, Fetriks Theopillus J. H. Wellem Tri Wahyuningsih Tundjung Mahatma Umbu Tamu Ama, Aldian Untung Rahardja Untung Rahardja Vikky Aprelia Windarni Vikky Aprelia Windarni Vincentia Pawestri Wahyuni Kristinawati Waney, Natalia Christy Wattimanela, Henry Junus Wibowo, Mars Caroline Wijayanti, Yunita Puput Windarni, Vikky Aprelia Wisnu Anendya Sekti Yenusi, Yuni naomi Yulius Yusak Ranimpi