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All Journal Jurnal Matematika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI EIGEN MATHEMATICS JOURNAL Jurnal Gema Ngabdi Jurnal Varian Jurnal Pengabdian Masyarakat Sains Indonesia (Indonesian Journal Of Science Community Services) Jurnal Dinamika Sosial Ekonomi Journal of Mathematics: Theory and Applications Prosiding Konferensi Nasional PKM-CSR Kajian Sastra Nusantara Linggau ( KASTRAL) Jurnal Karya Pengabdian Teknik Mesin Jurnal Pepadu Jurnal Intelek Insan Cendikia Indonesian Journal of Islamic Religious Education (INJIRE) Indonesian Science Education Journal (ISEJ) AL-Ikhtiar : Jurnal Studi Islam Lontar Komputer: Jurnal Ilmiah Teknologi Informasi International Journal of Computing Science and Applied Mathematics-IJCSAM

Nurul Fitriyani

Department Of Mathematics, Faculty Of Mathematics And Sciences, University Of Mataram Mataram, Indonesia

Author-ID : 2638910

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Small Area Estimation dengan Metode Hierarchical Bayes pada Proporsi Destinasi Objek Wisata Halal Kabupaten Lombok Barat Husnul Arini; Desy Komalasari; Nurul Fitriyani
Eigen Mathematics Journal In Press Desember 2018
Publisher : University of Mataram

Research using Hierarchical Bayes (HB) applied to Small Area Estimation (SAE) was conducted with the aim to estimate the proportion of halal tourism destination in West Lombok Regency. The development of halal taourism object in West Lombok that has been done by the Departement of Culture and Tourism, has not been fully able to do direct estimation on a small area, such as at the sub-district level. One way of obtaining estimation data up to the sub-district level is by increasing the sample size. However, increasing the sample size will cost time and money. Therefore, SAE method can be used to solve the poblem of data optimization. Furthermore, the HB method is used in the process of finding the expected alleged value. The prediction process was performed using Markov Chain Monte Carlo (MCMC) by applying the conditional Gibbs Algorithm of Metropolis-Hasting. Indirect modeling using HB method on SAE is based on the Fay-Herriot model for the area level with the help of supporting variables. The estimation results were then compared with the direct estimates with the value of the variance statistic as a benchmark. The results showed that the estimation using HB gave in a smaller average of variance value score of 0.021, compared with direct estimates with an average of variance value of 0.042. This showed that indirect estimation using HB method gave better result than using direct estimation method.

Estimasi Parameter Distribusi Mixture Eksponensial dan Weibull dengan Metode Bayesian Markov Chain Monte Carlo Ulfa Destiarina; Mustika Hadijati; Desy Komalasari; Nurul Fitriyani
Eigen Mathematics Journal Vol. 2 No. 1 Juni 2019
Publisher : University of Mataram

Dalam estimasi parameter, kadangkala terdapat beberapa permasalahan yang menuntut penyelesaian dengan suatu distribusi mixture atau distribusi campuran. Penelitian ini bertujuan untuk menerapkan estimasi parameter distribusi mixture eksponensial dan Weibull pada data simulasi dengan metode estimasi Bayesian Markov Chain Monte Carlo (MCMC). Hasil yang diperoleh menunjukkan bahwa perhitungan analitik estimasi parameter lebih akurat dibandingkan perhitungan dengan bantuan perangkat lunak, apabila dipandang dari segi kesesuaian teori serta proses integrasinya

Model Regresi Semiparametrik Spline Hasil Produksi Padi di Kabupaten Lombok Timur Bidayani Bidayani; Mustika Hadijati; Nurul Fitriyani
Eigen Mathematics Journal Vol. 2 No. 1 Juni 2019
Publisher : University of Mataram

Beras merupakan suatu sumber bahan makanan pokok penting yang harus tetap terjaga ketersediannya sepanjang tahun. Namun untuk tahun-tahun terakhir ini Indonesia yang dikenal dengan kekayaan alamnya, menjadi salah satu negara pengimpor beras. Hal ini dikarenakan konsumsi beras di indonesia terus meningkat setiap tahunnya, sedangkan produksi beras yang dihasilkan kurang mencukupi konsumsi masyarakat Indonesia. Penelitian ini dilakukan dengan tujuan untuk menentukan model regresi semiparametrik spline pada analisis faktor-faktor yang mempengaruhi hasil produksi padi di Kabupaten Lombok Timur tahun 2014, serta mengetahui faktor-faktor apa saja yang mempengaruhi hasil produksi padi tersebut. Metode yang digunakan adalah regresi semiparametrik spline dengan pemilihan titik knot optimum menggunakan Generalized Cross Validation. Hasil yang diperoleh menunjukkan bahwa variabel yang secara signifikan mempengaruhi hasil produksi padi adalah ketinggian wilayah dari permukaan laut, dengan nilai koefisien determinasi sebesar 99,71% dan nilai Root Mean Square Error of Prediction sebesar 41,65.

Analisis Dependensi Faktor Makroekonomi terhadap Tingkat Harga Emas Dunia dengan Pendekatan Copula Sri Wati Agustini; Mustika Hadijati; Nurul Fitriyani
Eigen Mathematics Journal Vol. 2 No. 2 Desember 2019
Publisher : University of Mataram

Gold is a precious metal that used many times as an alternative investment. Before investing, every investor requires relevant information to make profitable investment decisions. Relevant information can be obtained by looking at the dependency relationship between variables. In identifying the relationship between variables, a Copula approach could be used, since it is not tight against the assumption of normality, which is common in macroeconomic variables. Copula used were Archimedean Copula family, such as Clayton, Frank, and Gumbel. The results of this study indicated that the Archimedean Copula of the Frank family is the best Copula models to explain the structure of dependencies between gold and each composite stock price index and exchange rate, with each parameter obtained were 2.286 and -2.2390, respectively, while Clayton Copula family was the best Copula models to explain the structure of dependencies between gold and oil, with parameter obtained was 3.4090.

Pengaruh Kurs Dolar Amerika Serikat, Inflasi, dan Tingkat Suku Bunga Terhadap Indeks Harga Saham Gabungan Dengan Vector Error Correction Ni Luh Putu Dewi Wikayanti; Qurratul Aini; Nurul Fitriyani
Eigen Mathematics Journal Vol. 3 No. 1 Juni 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i1.58

Pergerakan Indeks Harga Saham Gabungan (IHSG) dipengaruhi oleh situasi politik dan perekomian global, serta adanya faktor seperti Kurs Dolar Amerika Serikat, Inflasi, dan Tingkat Suku Bunga, yang apabila melemah dapat mengakibatkan perekonomian terguncang. Penelitian ini bertujuan mengkonstruksi model Vector Error Correction Model (VECM) yang merupakan pengembangan model Vector Autoregressive pada runtun waktu yang tidak stasioner dan memiliki hubungan kointegrasi. Selain itu, penelitian ini bertujuan untuk menganalisis hubungan jangka panjang maupun jangka pendek antara faktor-faktor yang mempengaruhi IHSG yaitu Kurs Dolar Amerika Serikat, Inflasi, dan Tingkat Suku Bunga serta menentukan hasil peramalan IHSG berdasarkan faktor yang mempengaruhinya. Model VECM yang diperoleh yaitu VECM(2), yang menunjukkan bahwa perubahan variabel Kurs Dolar Amerika Serikat memiliki pengaruh positif terhadap IHSG, sedangkan Inflasi dan Tingkat Suku Bunga memberikan pengaruh negatif terhadap perubahan IHSG. Hal ini berlaku untuk pengaruh jangka panjang maupun jangka pendek. Hasil peramalan diperoleh dengan menggunakan VECM(2) pada bulan Juli dan Agustus 2019 yaitu sebesar 6424,68 dan 6488,88 dengan nilai MAPE sebesar 1,534%. Nilai MAPE menunjukkan bahwa hasil peramalan dengan model VECM(2) memberikan hasil yang sangat baik.

Peramalan Indeks Harga Konsumen Kota Mataram Menggunakan Vector Autoregressive Integrated Moving Average Moudy Puspita Ayudhiah; Syamsul Bahri; Nurul Fitriyani
Eigen Mathematics Journal Vol. 3 No. 1 Juni 2020
Publisher : University of Mataram

Penelitian ini bertujuan untuk meramalkan data Indeks Harga Konsumen (IHK) sub-kelompok padi-padian, umbi-umbian dan hasilnya serta sub-kelompok bumbu-bumbuan di Kota Mataram. Data yang digunakan adalah data tahun 2014 sampai dengan tahun 2017, yang digunakan untuk meramalkan nilai IHK pada tahun 2018. Metode yang digunakan dalam penelitian ini adalah metode Vector Autoregressive Integrated Moving Averageatau disebut VARIMA. Hasil penelitian menunjukkan bahwa model terbaik yang diperoleh adalah model VARIMA (1,1,0) dengan akurasi model untuk IHK padi-padian, umbi-umbian dan hasilnya berdasarkan nilai MAPE sebesar 0,7359% yang menyatakan bahwa hasil peramalan dapat dikategorikan sangat baik, sedangkan akurasi model untuk IHK bumbu-bumbuan berdasarkan nilai MAPE sebesar 10,6736% yang menyatakan bahwa hasil peramalan dapat dikategorikan baik.

Penerapan Model Vector Autoregressive Integrate Moving Average dalam Peramalan Laju Inflasi dan Suku Bunga di Indonesia Jusmawati Jusmawati; Mustika Hadijati; Nurul Fitriyani
Eigen Mathematics Journal VOL. 3 NO. 2 DESEMBER 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i2.62

The inflation and interest rates in Indonesia have a significant impact on the country's economic development. Indonesian inflation and interest rates data are multivariate time series data that show activity over a certain period of time. Vector Autoregressive Integrated Moving Average (VARIMA) is a method for analyzing multivariate time series data. This method is a simultaneous equation modeling that has several endogenous variables simultaneously. This study aimed to model the inflation and interest rates data, from January 2009 to December 2016 and predict inflation and interest rates by using VARIMA method. The model obtained was the VARIMA(0,2,2) model, with estimated parameters using the maximum likelihood method. The choice of the VARIMA(0,2,2) model was based on the smallest AIC value of -4,2891, with a MAPE value for the inflation and interest rates forecasting were 6,04% and 1,84%, respectively, which indicates a very good forecast results.

Analisis Rotasi Ortogonal pada Teknik Analisis Faktor Menggunakan Metode Procrustes Himayati Himayati; Ni Wayan Switrayni; Desy Komalasari; Nurul Fitriyani
Eigen Mathematics Journal Vol. 3 No. 1 Juni 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i1.66

Factor analysis is a multivariate statistical method that tries to explain the relationship between a number of independent variables by grouping these variables into factors. With this grouping, the existing variables will be easier to interpret. In increasing the power of factor interpretation, a matrix loading factor transformation must be performed. The transformation can be done by choosing the method that is in orthogonal rotation, the varimax or quartimax or equamax method. In order to find out which rotation techniques is the most appropriate, the minimum square distance values () generated from the procrustes method used. In this study three data were used from the results of the questionnaire, for data I obtain the value of the minimum distance squared with a varimax rotation that is with ; for data II obtain the value of the minimum distance squared with a quartimax rotation that is with ; for data III obtain the value of the minimum distance squared with a varimax rotation that is with .

Regresi Nonparametrik Kernel Gaussian pada Pemodelan Angka Kelahiran Kasar di Provinsi Nusa Tenggara Barat Deni Pratiwi; Lalu Abd Azis Mursy; Muhammad Rizaldi; Nurul Fitriyani
Eigen Mathematics Journal VOL. 3 NO. 2 DESEMBER 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i2.78

This study aims to model Crude Birth Rates (CBR) in West Nusa Tenggara Province. The nonparametric regression method was used in this research by considering data distribution patterns that do not show a linear relationship between variables. In this case, the kernel nonparametric regression using the Gaussian function and the Nadaraya-Watson estimator. The results showed optimal bandwidths of 0.55542837, 1.29042927, 0.94706041, and 0.92278896 with a value of minimum Generalized Cross-Validation (GCV) of 0.000000000432613511, which was minimized by the simulated annealing algorithm. The resulting model's accuracy can be seen from the coefficient of determination (R2) of 99.23% and the Mean Absolute Percentage Error (MAPE) of 0.007049%.

Peramalan Jumlah Siswa Baru Madrasah Aliyah (MA) Manhalul Ma’arif Darek-Lombok Tengah Lisa Harsyiah; Nurul Fitriyani; Salwa Salwa
Eigen Mathematics Journal VOL. 3 NO. 2 DESEMBER 2020
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v3i2.88

This study aimed to forecast the new student number at Madrasah Aliyah (MA) Manhalul Ma'arif Darek. The data used in this study was the annual time series data of new students who enrolled in the school, from the 1998/1999 academic year to 2016/2017. Based on the data obtained, it shows that the number of new students who enroll in Madrasah Aliyah (MA) Manhalul Ma'arif Darek tends to fluctuate. This fluctuating pattern is a problem faced by Madrasah Aliyah (MA) Manhalul Ma'arif Darek in determining strategic and policy steps related to planning the provision of school facilities / infrastructure. Therefore we need a forecasting method in accordance with the data pattern. The forecasting method used is the Fuzzy Time Series Cheng method. This method uses fuzzy principles as the basis of the forecasting process. The forecasting process results obtained the Mean Square Error (MSE) value of 101.5009 and the Mean Absolute Percentage Error (MAPE) value of 18.49%. The results showed that the Fuzzy Time Series Cheng method performed well in predicting the number of new students at Madrasah Aliyah (MA) Manhalul Ma'arif Darek.

Co-Authors Abdillah Rizki Tanjung Agus Kurnia Akhmed Syarifatul Raflus Alfira Sofia Rahayu Amalia Chairunissa Atma Utami Sawitri Baiq Urfa Justitiaski Bidayani Bidayani Dalmeri Deni Pratiwi Desy Komalasari Dini Wijayanti Ema Syaidah Ena Setiawana Erry Esa Aprilliansyah Harsyiah, Lisa Himayati Himayati Husnul Arini I Gde Ekaputra Gunartha I Gede Ekaputra Gunartha I Nyoman Budiantara Irwansyah Irwansyah Jamaluddin Joji Ardian Pembargi Jurnal Pepadu Jusmawati Jusmawati Komarudin Lailia Awalushaumi Lailia Awalushaumi Lalu Abd Azis Mursy Misrah Moudy Puspita Ayudhiah Muhamad Aditio Apriesta Suharto Muhammad Rijal Alfian Muhammad Rizaldi Muhammad Sopian Sauri Muhammad Sopian Sauri Mustika Hadijati Mustika Hadijati Ni Luh Putu Dewi Wikayanti Ni Wayan Switrayni Nisa Syahrani Nurhafizah Oca Qurratul Aini Riski Aprilia Rosanti W. ahidatussolihah Salwa Salwa Sapurah Sapurah Siti Wulandari Sri Wati Agustini Syamsul Bahri Syamsul Bahri T. Lailan Safinah Tanjung, Abdillah Rizki Ulfa Destiarina Zulhan Widya Baskara

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Journal : EIGEN MATHEMATICS JOURNAL