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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Jurnal Ilmu Dasar Kontinu: Jurnal Penelitian Didaktik Matematika Jurnal Teknologi Informasi dan Ilmu Komputer Indonesian Journal of Applied Statistics Journal of Mathematics and Mathematics Education (JMME) BAREKENG: Jurnal Ilmu Matematika dan Terapan Business Innovation and Entrepreneurship Journal TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Applied Data Sciences Jurnal Pengabdian kepada Masyarakat Journal of Informatics Management and Information Technology Konstelasi: Konvergensi Teknologi dan Sistem Informasi Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Prosiding Seminar Nasional Official Statistics Prosiding Simposium Nasional Multidisiplin (SinaMu) International Journal of Computing Science and Applied Mathematics-IJCSAM
Zukhronah, Etik
Universitas Sebelas Maret
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Journal : Indonesian Journal of Applied Statistics

 1 
Peramalan Data Inflow dan Outflow Uang Kartal Bank Indonesia Provinsi DKI Jakarta Menggunakan Model ARIMAX dan SARIMAX Atika Amalia; Etik Zukhronah; Sri Subanti
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.45673

Abstract

Abstract. DKI Jakarta Province plays a crucial role as the center of government and economy in Indonesia. The description of currency inflows and outflows is highly required before Bank Indonesia formulates the appropriate policies to control the circulation of money. The monthly data of currency inflow and outflow of Bank Indonesia of DKI Jakarta show a significant increase in each year particularly before, during, and after Eid al-Fitr. The determination of Eid al-Fitr does not follow the Gregorian calendar but based on the Islamic calendar. The difference in the use of the Gregorian and Islamic calendars in a time series causes a calendar variation. Thus, the determination of Eid al-Fitr in the Gregorian calendar changes as it goes forward eleven days each year or one month every three years. This study aims to obtain the best model and forecast currency inflows and outflows of Bank Indonesia DKI Jakarta using the ARIMAX and SARIMAX models. The study used in-sample data from January 2009 to December 2018 and out-sample data from January to October 2019. The best model was selected based on the smallest out-sample MAPE value. The result showed that the best forecasting model of inflow was ARIMAX (1,0,1). Meanwhile, the best forecasting model for outflow was SARIMAX (2,0,1)(0,0,1)12.Keywords: ARIMAX, calendar variation, forecasting, SARIMAX
Peramalan Banyak Pengunjung Pantai Pandasimo Bantul Menggunakan Regresi Runtun Waktu dan Seasonal Autoregressive Integrated Moving Average Exogenous Tito Tatag Prakoso; Etik Zukhronah; Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.45795

Abstract

Forecasting is a ways to predict what will happen in the future based on the data in the past. Data on the number of visitors in Pandansimo beach are time series data. The pattern of the number of visitors in Pandansimo beach is influenced by holidays, so it looks like having a seasonal pattern. The majority of Indonesian citizens are Muslim who celebrate Eid Al-Fitr in every year. The determination of Eid Al-Fitr does not follow the Gregorian calendar, but based on the Lunar calendar. The variation of the calendar is about the determination of Eid Al-Fitr which usually changed in the Gregorian calendar, because in the Gregorian calendar, Eid Al-Fitr day will advance one month in every three years. Data that contain seasonal and calendar variations can be analyzed using time series regression and Seasonal Autoregressive Integrated Moving Average Exogenous  (SARIMAX) models. The aims of this study are to obtain a better model between time series regression and SARIMAX and to forecast the number of Pandansimo beach visitors using a better model. The result of this study indicates that the time series regression model is a better model. The forecasting from January to December 2018 in succession are 13255, 6674, 8643, 7639, 13255, 8713, 22635, 13255, 13255, 9590, 8549, 13255 visitors.Keywords: time series regression, seasonal, calendar variations, SARIMAX, forecasting
Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator Nilai Tukar Riil Menggunakan Model SWARCH (2,3) Sugiyanto Sugiyanto; Etik Zukhronah; Dewi Retnosari
Indonesian Journal of Applied Statistics Vol 1, No 1 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i1.24082

Abstract

The financial crisis that hit Asia in mid-1997 began with the financial crisis in Thailand which then spread to Indonesia. The impact of the financial crisis in Indonesia is so severe that a crisis detection system is needed. The financial crisis detection system can be done by simple monitoring of macroeconomic indicators such as real exchange rate. Excessive real exchange rate is predicted to have a great chance of crisis.The result shows that the real exchange rate from January 1990 to June 2013 has heteroscedasticity effect and there are structural changes so it can be modeled using SWARCH model (2,3) with ARMA (1.0) as conditional average model and ARCH (3) as model conditional variance. The inferred probabilities value of the SWARCH (2,3) model in February 1998 of 1 and July 1998 of 0.9968 over 0.5 indicates that the period is in a high volatile condition indicating a crisis. The SWARCH model (2.3) based on the real exchange rate indicator was able to capture the high volatile conditions in February 1998 and July 1998 as the impact of the 1997 Asian financial crisis.Keywords : Deteksi, krisis keuangan, nilai tukar riil, SWARCH
Implementasi Text Mining Pada Analisis Sentimen Pengguna Twitter Terhadap Marketplace di Indonesia Menggunakan Algoritma Support Vector Machine Dyah Auliya Agustina; Sri Subanti; Etik Zukhronah
Indonesian Journal of Applied Statistics Vol 3, No 2 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i2.44337

Abstract

In this digital era, technology development has changed the behavior of society from buy offline to online. One of this behavioral changes is marked by the growth of global marketplace including in Indonesia. The big marketplaces in Indonesia that have received a lot of public response on social media are Tokopedia, Shopee, and Bukalapak. This research determines the public sentiment toward both the service and issues surrounding these three marketplaces on media social especially Twitter. Public opinion is classified into a positive or negative sentiment. The data used in this study is obtained from Twitter API (Application Programming Interface) using keyword Shopee, Tokopedia, and Bukalapak. Preprocessing texts are divided into five steps: cleansing, case folding, stemming, stopwords, and tokenizing. Training and testing data are divided using k-fold cross validation method, while visualization the characteristic of text is using word cloud. Research shows that public are posting tweet more positive sentiment than negative one. The perfomance of classification shows that the best G-mean and AUC value for Bukalapak testing data are 0.85 and 0.86 in the first fold. While the best G-mean and AUC value for Shopee testing data are 0.76 and 0.77 in the seventh fold and the best G-mean and AUC value for Tokopedia testing data are 0.82 and 0.83 in the sixth fold.Keywords : sentiment analysis, marketplace, support vector machine, twitter
Peramalan Banyaknya Pengunjung Pantai Glagah Menggunakan Metode Autoregressive Integrated Moving Average Exogenous (ARIMAX) dengan Efek Variasi Kalender Solikhah Novita Intan; Etik Zukhronah; Supriyadi Wibowo
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i2.26298

Abstract

Glagah Beach is one of the tourist destinations in Kulon Progo Regency, Yogyakarta which is the most visited by tourists. Glagah Beach visitors data show  that in the month of Eid Al-Fitr there was a significant increase. This shows that there is an effect of the calendar variation of Eid al-Fitr. Therefore, it is needed a method that can be used to analyze time series data which contains effects of calendar variations, that is ARIMAX method. The aim of this study are to find the best ARIMAX model and to predict the number of visitors to Glagah Beach in the future. The result shows that the best ARIMAX model was ARIMAX([24],0,0). Forecasting from January to September 2016 are 37211, 21306, 26247, 24148, 28402, 29309, 81724, 26029, and 23688 visitors. Keywords: Glagah Beach; variation of calendar; Eid al-Fitr; ARIMAX.
Model Variasi Kalender pada Regresi Runtun Waktu untuk Peramalan Jumlah Pengunjung Grojogan Sewu Etik Zukhronah; Winita Sulandari; Isnandar Slamet; Sugiyanto Sugiyanto; Irwan Susanto
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.47163

Abstract

Abstract. Grojogan Sewu visitors experience a significant increase during school holidays, year-end holidays, and also Eid al-Fitr holidays. The determination of Eid Al-Fitr uses the Hijriyah calendar so that the occurrence of Eid al-Fitr will progress 10 days when viewed from the Gregorian calendar, this causes calendar variations. The objective of this paper is to apply a calendar variation model based on time series regression and SARIMA models for forecasting the number of visitors in Grojogan Sewu. The data are Grojogan Sewu visitors from January 2009 until December 2019. The results show that time series regression with calendar variation yields a better forecast compared to the SARIMA model. It can be seen from the value of  root mean square error (RMSE) out-sample of time series regression with calendar variation is less than of SARIMA model.Keywords: Calendar variation, time series regression, SARIMA, Grojogan Sewu
Co-Authors Adi Wicaksono, Nanda Adigama Tri Nugraha Agung Setyabudi, Arriza Aji Susanto Aprilia, Nabila Churin Aryani, Fadhilatul Nida Atika Amalia Brilianto, Maximilianus Noel Dewi Retnosari Dina Rohmah Dyah Auliya Agustina Effendi, Arfiyansyah Rizki Fhadilla, Nahdatul Fransisca Trisnani Ardikha Putri Handajani, Sri Sulistijowati Hidayah, Nurrul Hizkia Yotant Pradana Husna Afanyn Khoirunissa Ilahi, Esa Permata Sari Putri Indra Raditya , Dionisius Irwan Susanto Isnaini, Bayutama Isnandar Slamet Isnandar Slamet Isnandar Slamet Isnandar Slamet Isnandar Slamet, Isnandar Kadar, Jimmy Abdel Kusuma, Erin Jihan Wahyu Martina Hilda Melati Anggiasari Muhammad Zidni Subarkah Nabila Churin Aprilia Nafi'udin, Fauzi Nugraha, Titis Jati Pardede, Hilman Ferdinandus pratiwi, hasih Pratiwi, Hasih S Sugiyanto Solikhah Novita Intan Sri Subanti Sri Sulistijowati Handajani Sugianto Sugianto Sugiyanto - Sugiyanto Sugiyanto Sugiyanto Sugiyanto Sugiyanto Sugiyanto Sugiyanto, Sugiyanto Sulandari, Winita Supriyadi Wibowo Susilotomoa, Dhestahendra Citra Tito Tatag Prakoso Winita Sulandari Winita Sulandari Winita Sulandari Yuliana Susanti Yuliana Susanti, Yuliana Yulvia Fitri Rahmawati