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All Journal Jurnal Sains Dasar Indonesian Journal of Mathematics and Natural Sciences Abdimas Jurnal Penelitian Pendidikan Kreano, Jurnal Matematika Kreatif-Inovatif Lembaran Ilmu Kependidikan Scientific Journal of Informatics Jurnal TAM (Technology Acceptance Model) CARADDE: Jurnal Pengabdian Kepada Masyarakat JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Symmetry: Pasundan Journal of Research in Mathematics Learning and Education JISKa (Jurnal Informatika Sunan Kalijaga) Range : Jurnal Pendidikan Matematika Jurnal Statistika dan Matematika (Statmat) Primatika : Jurnal Pendidikan Matematika Jurnal PKM Manajemen Bisnis Unnes Journal of Mathematics Education Unnes Journal of Mathematics Edukasia: Jurnal Pendidikan dan Pembelajaran Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Jurnal Pendidikan MIPA Jurnal TAM (Technology Acceptance Model) Unnes Journal of Mathematics
Putriaji Hendikawati
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Negeri Semarang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Journal : Unnes Journal of Mathematics

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ANALISIS PREDIKSI QUICK COUNT DENGAN METODE STRATIFIED RANDOM SAMPLING DAN ESTIMASI CONFIDENCE INTERVAL MENGGUNAKAN METODE MAKSIMUM LIKELIHOOD Ulya, Siti Faiqotul; Sukestiyarno, YL; Hendikawati, Putriaji
Unnes Journal of Mathematics Vol 7 No 1 (2018)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v7i1.27385

Abstract

Tujuan penelitian untuk menganalisis prediksi quick count dengan pengambilan sampel, serta akurasi dan presisi pada Pilkada Jawa Tengah. Metode yang digunakan yaitu pemilihan masalah, merumuskan masalah, studi pustaka, pemecahan masalah, dan penarikan kesimpulan. Teknik Stratified Random Sampling oleh LSI pada Pilkada Jateng diperoleh ukuran sampel yang digunakan untuk prediksi kemenangan sebesar 3.8362 pemilih yang tersebar di 87 TPS, sehingga estimasinya menghasilkan rentang proporsi pemilih kandidat 1=0,1250<th<0,2963, kandidat 2=0,20552<th<0,39847, kandidat 3=0,3822< th <0,5923. Perhitungan proporsi kandidat 1= 21,07%, kandidat 2= 30,2%, dan kandidat 3= 48,73% . Karena urutan perolehan suara setiap kandidat sesuai antara KPU dan LSI, maka Pilkada Jateng memiliki akurasi tinggi dan selisih hasil perhitungan terletak pada batas ketelitian yang ditoleransi ini menandakan bahwa presisi yang tinggi. The purpose of this study was to analying the implementation of the quick count with sampling process through the process and analyze the accuracy and presicion on the local elections of central java. The method includes selecting problems, formulate problems, library research, problem solving, and conclusion. Stratified Random Sampling survey institution on the elections central java obtained a sample size proportionally level of 38.362 samples of voters spread over 87, TPS so the estimation produces a range proportion of voters candidate 1 is 0,1250<th <0,2963, candidate 2 is 0,20552<th <0,39847, candidate 3 is 0,3822< th<0,5923. Calculation of proportion for candidate 1 is 21,07% , candidate 2 is 30,2%, and candidate 3 is 48,73% The order of votes for each candidate are the same beteen the commission and the contens of the local elections of central java in had a high accuracy indicates that having high precision.
PERAMALAN CURAH HUJAN DENGAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE WITH EXOGENOUS INPUT (ARIMAX) Suryani, Andika Resti; Sugiman, Sugiman; Hendikawati, Putriaji
Unnes Journal of Mathematics Vol 7 No 1 (2018)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v7i1.27386

Abstract

Tujuan penelitian ini untuk mengetahui model ARIMAX terbaik dan hasil peramalan curah hujan menggunakan model terbaik. Berdasarkan hasil analisis diperoleh model ARIMAX terbaik adalah model dan diperoleh hasil peramalan curah Bulan Januari 2015 sebesar 384,25mm, Bulan Februari 208,04mm, Bulan Maret 233,94mm, Bulan April 214,14mm, Bulan Mei 183,79mm, Bulan Juni 169,18mm, Bulan Juli 123,49mm, Bulan Agustus 98,85mm, Bulan September 106,09mm, Bulan Oktober 153,04mm, Bulan November 308,52mm dan Bulan Desember 280,45mm. Hasil peramalan curah hujan menunjukkan pola yang sama dengan data yang sebenarnya dan diperoleh nilai eror sMAPE sebesar 1,045. Hal ini dapat diartikan bahwa metode ARIMAX dapat digunakan untuk melakukan peramalan curah hujan dengan SST El-Nino 3.4 sebagai variabel eksogen. The purpose of the study is to find out the best ARIMAX models and forecasting rainfall usingthe best model. Based on the results analysis obtained the best ARIMAX model is model and obtained forecasting rainfall in January 2015 amounted to 384,25mm; February 208,04mm; March 233,94mm; April 214,14mm; May 183,79mm; June 169,18mm; July 123,49mm; August 98,85mm; September 106,09mm; October 153,04mm; November 308,52mm; and December 280,45mm. Forecasting rainfall data show the same pattern with the actual data and obtained error sMAPE values 1.045. This may imply that ARIMAX method can be used for forecasting rainfall with the El-Nino 3.4 SST as exogenous.
PEMODELAN FUNGSI TRANSFER UNTUK MERAMALKAN TINGKAT INFLASI INDONESIA Paradita, Evelyn; Agoestanto, Arief; Hendikawati, Putriaji
Unnes Journal of Mathematics Vol 7 No 1 (2018)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v7i1.27387

Abstract

Analisis fungsi transfer merupakan salah satu model deret berkala yang menggabungkan pendekatan kausal dan runtun waktu. Tujuan penelitian ini yaitu menganalisis model fungsi transfer sehingga dihasilkan model terbaik untuk meramalkan tingkat inflasi Indonesia selama bulan November 2016 sampai Oktober 2017. Data yang digunakan adalah data bulanan pada Tingkat Inflasi Indonesia dan Indeks Harga Konsumen periode Januari 2005 sampai dengan Oktober 2016 yang diperoleh dari website Badan Pusat Statistika dan Bank Indonesia diperoleh model terbaik yang digunakan untuk data tingkat inflasi Indonesia untuk periode berikutnya dengan berbantuan program software SAS. Berdasarkan analisis fungsi transfer diperoleh bahwa model terbaik fungsi transfer yang digunakan dengan nilai orde b = 8, r = 0, s = 1 dan deret noise dengan nilai p = 1, q = 1. Hasil ramalan untuk bulan November 2016 sampai Oktober 2017 menunjukan bahwa nilai ramalan masih berada pada ambang batas 95% confident interval sehingga model masih dapat digunakan untuk peramalan. Analysis of the transfer function is one of a regular series model that incorporates a causal and time series. The main purpose of this research is to analyze the transfer function model that produced the best model to forecast inflation in Indonesia during the month of November 2016 until October 2017, in order to obtain the best model that is used for data Indonesian inflation rate for the next period withaided by software program SAS. Based on the transfer function analysis showed that the best model transfer function which is used with the value of the order of b = 8, r = 0, s = 1 and row noise with p = 1, q = 1. The result forecast for the months of November 2016 through October 2017 showed that value forecast is still at the threshold of 95% confident interval so that the model can still be used for forecasting.
TIME SERIES MODELLING OF STOCK PRICE BY MODWT-ARIMA METHOD 'Aina, Maula Qorri; Hendikawati, Putriaji; Walid, Walid
Unnes Journal of Mathematics Vol 8 No 2 (2019)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v8i2.30352

Abstract

MODWT-ARIMA is a time series modeling that combines the MODWT process and the ARIMA process. The MODWT process is used as pre-processing data while the ARIMA process as a time series modeling for data from MODWT decomposition. This study aims to show that time series modeling with a combined MODWT-ARIMA process provides more accurate forecast result compared to the ARIMA model. The modeled data is time series of daily stock price BBRI.JK started from January 2, 2015 to December 31, 2018. Accuracy measurement of the forecasting result is based on the RMSE value. The result is the MODWT-ARIMA model has a RMSE value which is smaller than the ARIMA model with RMSE , while the RMSE forecast results for 43 future periods is which is also smaller than the ARIMA forecast RMSE, . The diagnostic checking results if the ARIMA model for MODWT decompotition data, namely D1, D2, D3, and S3, indicate that the residual model is not white noise, while the ARIMA model for the time period of daily stock prices has white noise residuals. Theoritically, a model that has no white noise’s residual is considered to be less able to describe the properties of the observed data and further residual modeing should be done. However, this research is sufficient for the ARIMA model and it can be shown that the MODWT-ARIMA model is more effective for modelling time series that are not stationery compared to the ARIMA model.
Co-Authors 'Aina, Maula Qorri Abdurakhman Abdurakhman Ade Noorliza Niyamae AGUSTINA, SELY Ahmad Dzulfikar Amara Sweetya Auliya Ambarwati, Ratna Amin Suyitno Anggriningrum, Dwi Prisita Arief Agoestanto Asriani, Elisa Desi Assidiq, Addinul Astuti, Raras Setya Aviliana, Firna Bambang Eko Susilo Bambang Eko Susilo Bidayatul hidayah Budi Waluya David Mubarok, David Dewi, Heni Lilia Dwijanto Dwijanto, Dwijanto Edy Soedjoko Emi Pujiastuti Farkhan, Feri FAUSTINA, RIZA SILVIA Febrianto, Laeli Sidik Florentina Yuni Arini, Florentina Yuni Hapsari, Desy Trya Harwanti, Nur Achmey Selgi hengky tri ikhsanto, hengky tri ikhsanto Ismail, Abid Khoirul Isnaeni, Ari Juwita, Puspa Karomah, Yuliyanti Kartono, Kartono Khanifah Khanifah Khunaeni, Sirilivia Kiswandi, Kiswandi Kristina Wijayanti Kurniana Bektiningsih Larasati, Enggar Niken Lestari, Pinta Dian Mashuri - Mashuri Mashuri Masrukan Masrukan Mohammad Asikin Much Aziz Muslim Muhammad Kharis Muna, Trimurtini, Nur Aizatun Nafiul Anam, Nafiul Nitoviani, Nindy Dwi Nofiyah, Noni Nur Hidayati Nur Hidayati Nuriana Rachmani DN Nuriana Rachmani DN, Nuriana Rachmani Nurkaromah Dwidayati, Nurkaromah Nurlazuardini, Novia Nilam Nursiwi Nugraheni Paradita, Evelyn Prabowo, Ardi Pramesti, Santika Lya Diah Pramesti Pratama, Alfian Adi Pratidina, Inung Pratiwi, Yuninda Diah Purbowo, Gallant Alim Purnawan, Dedy Rahayu Budhiati Veronika Rahayu Budhiyati Rahman, Erik Riza Arifudin Ruliana Ruliana, Ruliana Saefurrochman, Wisatsana Roychan Santika Lya Diah Pramesti Sanusi, Ratna Nur Mustika Saraswati, Andhina Sari, Ratna Novita Scolastika Mariani Setiani, Ida St. Budi Waluya Subanar . Sugiman Sugiman Sukestiyarno Sukestiyarno Sunarmi Sunarmi Supriyono Supriyono Suryani, Andika Resti Tarno Tarno Ulya, Siti Faiqotul Veronica, Rahayu Budhiati Veronica, Rahayu Budhiati Walid Walid Walid, Walid Wardono Wardono Wardono Widayanti, Christina Zaenal Abidin Zaenuri Mastur Zahra, Mega Dea Zoraida, Desti Anisa