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All Journal The Journal of Experimental Life Sciences (JELS) Jurnal Sosial Ekonomi Pertanian CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Statistik Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer JURNAL ILMIAH MATEMATIKA DAN TERAPAN PERFORMA : Media Ilmiah Teknik Industri BAREKENG: Jurnal Ilmu Matematika dan Terapan Proceeding Simposium Nasional Kelautan dan Perikanan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pertanian Agros Zero : Jurnal Sains, Matematika, dan Terapan ComTech: Computer, Mathematics and Engineering Applications Jurnal ABDINUS : Jurnal Pengabdian Nusantara Inferensi MATHunesa: Jurnal Ilmiah Matematika Pakem : Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Official Statistics ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat Journal of Community Empowerment International Journal of Informatics Engineering and Computing

Atiek Iriany

Universitas Brawijaya

Author-ID : 288480

Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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GSTAR-X-SUR Model with Neural Network Approach on Residuals Rosyida, Diana; Iiriany, Atiek; Nurjannah, Nurjannah
CAUCHY Vol 5, No 4 (2019): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

One of the models that combine time and inter-location elements is Generalized Space Time Autoregressive (GSTAR) model. GSTAR model involving exogenous variables is GSTARX model. The exogenous variables which are used in GSTAR model can be both metrical and non-metrical data. Exogenous variable that can be applied into the forecasting of precipitation is non-metrical data which is in a form of precipitation intensity of a certain location. Currently, precipitation possesses patterns and characteristics difficult to identify, and thus can be interpreted as non-linear phenomenon. Non-linear model which is much developed now is neural network. Parameter estimation method employed is Seemingly Unrelated Regression (SUR) model approach, which can solve the correlation between residual models. This current research employed GSTARX-SUR modelling with neural network approach on residuals. The data used in this research were the records of 10-day precipitations in four regions in West Java, namely Cisondari, Lembang, Cianjur, and Gunung Mas, from 2005 to 2015. The GSTARX-SUR NN modelling resulted in precipitation deviation average of the forecast and the actual data at 4.1385 mm. This means that this model can be used as an alternative in forecasting precipitation.

Cross-Covariance Weight of GSTAR-SUR Model for Rainfall Forecasting in Agricultural Areas Sulistyono, Agus Dwi; Hartawati, Hartawati; Suryawardhani, Ni Wayan; Iriany, Atiek; Iriany, Aniek
CAUCHY Vol 6, No 2 (2020): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

The use of location weights on the formation of the spatio-temporalÂ model contributes to the accuracy of the model formed. The location weights that are often used include uniform location weight, inverse distance, and cross-correlation normalization. The weight of the location considers the proximity between locations. For data that has a high level of variability, the use of the location weights mentioned above is less relevant. This research was conducted with the aim of obtaining a weighting method that is more suitable for data with high variability. This research was conducted using secondary data derived from 10 daily rainfall data obtained from BMKG Karangploso. The data period used was January 2008 to December 2018. The points of the rain posts studied included the rain post of the Blimbing, Karangploso, Singosari, Dau, and Wagir regions. Based on the results of the research forecasting model obtained is the GSTAR ((1), 1,2,3,12,36) -SUR model. The cross-covariance model produces a better level of accuracy in terms of lower RMSE values and higher R2 values, especially for Karangploso, Dau, and Wagir areas.

PEMODELAN AMMI DENGAN MENGGUNAKAN EMPAT INDEKS PENAMPILAN TANAMAN (IPT) UNTUK RESPON TANAMAN KEDELAI Fudianita, Citra; Iriany, Atiek
Jurnal Mahasiswa Statistik Vol 2, No 2 (2014)
Publisher : Jurnal Mahasiswa Statistik

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PERBANDINGAN PENSKALAAN DIMENSI GANDA NON-METRIK DENGAN MENGGUNAKAN TIGA JARAK (EUCLIDEAN, CHEBYSHEV dan MINKOWSKI) Yuliana, Mila; Iriany, Atiek
Jurnal Mahasiswa Statistik Vol 3, No 1 (2015)
Publisher : Jurnal Mahasiswa Statistik

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PENERAPAN METODE CONNECTED EM-AMMI UNTUK MENDUGA DATA HILANG Firdaus, Cahyani Jannah; iriany, atiek
Jurnal Mahasiswa Statistik Vol 4, No 1 (2016)
Publisher : Jurnal Mahasiswa Statistik

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ANALISIS FAKTOR KONFIRMATORI DALAM KESIAPAN USAHA KECIL MENENGAH KOTA MALANG MENGHADAPI MEA Dewi, Anggi Seftia; iriany, atiek
Jurnal Mahasiswa Statistik Vol 4, No 2 (2016)
Publisher : Jurnal Mahasiswa Statistik

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Spatio Temporal Modelling for Government Policy the COVID-19 Pandemic in East Java Iriany, Atiek; Aini, Novi Nur; Sulistyono, Agus Dwi
CAUCHY Vol 6, No 4 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v6i4.10639

COVID-19 has cursorily spread globally. Just in four months, its status altered into a pandemic. In Indonesia, the virus epicenter is identified in Java. The first positive case was identified in West Java and later spread in all Java. The Large-scale Social Restrictions are seemingly inefficient as the SARS-CoV-2 transmission remains. As such, the government is struggling to find anticipatory policies and steps best to mitigate the transmission. In this particular article, we used a Spatio-temporal model method for the total COVID-19 cases in Java and forecasted the total cases for the next 14 days, allowing the stakeholders to make more effective policies. The data we were using were the daily data of the cumulative number of COVID-19 cases taken from www.covid19.go.id. Data modelling was conducted using a generalized spatio-temporal autoregressive model. The model acquired to model the COVID-19 cases in Java was the GSTAR(1)(1,0,0) model.

Pelatihan Pembuatan Nugget Cumi dan Kelayakan Usahanya di Desa Air Bini, Kecamatan Siantan Selatan, Kabupaten Kepulauan Anambas Muhamad Firdaus; Bambang Dwi Argo; Atiek Iriany; Dhanny Septimawan Sutopo; Danang Ariyanto; Marhen Andan Prasetyo
Prosiding Simposium Nasional Kelautan dan Perikanan Vol. 8 (2021): PROSIDING SIMPOSIUM NASIONAL VIII KELAUTAN DAN PERIKANAN UNHAS
Publisher : Fakultas Ilmu Kelautan dan Perikanan (FIKP), Universitas Hasanuddin

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Perairan kepulauan Anambas terletak di Wilayah Pengelolaan Perikanan Laut Cina Selatan yang memiliki sumberdaya perairan pelagis dan demersal banyak, diantaranya adalah cumi-cumi. Desa Air Bini adalah sentra industri cumi kering di kabupaten Anambas. Pemanfaatan dan peningkatan nilai tambah komoditas ini di desa Air Bini masih terbatas pada pengolahan cumi asin kering. Produk ini utamanya dipasarkan dalam bentuk utuh ke Tanjung Pinang, Batam dan Jakarta. Cumi kering adalah produk yang dapat didiversifikasi menjadi nugget. Tujuan pengabdian kepada masyarakat ini adalah pelatihan pembuatan nugget cumi kepada ibu-ibu pengusaha dan pengolah cumi asin dan penilaian kelayakan usahanya. Kegiatan ini dilaksanakan di UKM Nadine Desa Air Bini, Kecamatan Siantan Selatan, Kabupaten Kepulauan Anambas, Kepulauan Riau. Metode yang digunakan dalam kegiatan ini adalah participatory rural appraisal (PRA). Data kegiatan didapat melalui observasi, wawancara, partisipasi aktif dan dokumentasi dalam proses pembuatan nugget cumi. Pengambilan data dimulai dari proses pengadaan bahan baku sampai pada produk akhir yang dihasilkan. Analisa usaha yang dianalisis terdiri dari biaya produksi, keuntungan, BEP, dan analisa R/C ratio. Tahapan pembuatan nugget cumi meliputi persiapan bahan baku, persiapan bahan tambahan, penggilingan cumi kering asin dengan bahan tambahan, pembuatan adonan, pengukusan, battering, breading dan penggorengan. Hasil analisis usaha menunjukkan bahwa usaha nugget cumi dalam setahun membutuhkan biaya total Rp 159.144.620,-, dengan keuntungan sebesar Rp 43.655.380,-, dan nilai pulang balik tiap kemasan sebesar Rp 7.136 atau terjual sebanyak 4.894 kemasan dan memiliki nilai R/C ratio 1,27.

Comparison of Adaptive Holt-Winters Exponential Smoothing and Recurrent Neural Network Model for Forecasting Rainfall in Malang City Novi Nur Aini; Atiek Iriany; Waego Hadi Nugroho; Faddli Lindra Wibowo
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 2 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i2.7570

Rainfall forecast is necessary for many aspects of regional management. Prediction of rainfall is useful for reducing negative impacts caused by the intensity of rainfall, such as landslides, floods, and storms. Hence, a rainfall forecast with good accuracy is needed. Many rainfall forecasting models have been developed, including the adaptive Holt-Winters exponential smoothing method and the Recurrent Neural Network (RNN) method. The research aimed to compare the result of forecasting between the Holt-Winters adaptive exponential smoothing method and the Recurrent Neural Network (RNN) method. The data were monthly rainfall data in Malang City from January 1983 to December 2019 obtained from a website. Then, the data were divided into training data and testing data. Training data consisted of rainfall data in Malang City from January 1983 to December 2017. Meanwhile, the testing data were rainfall data in Malang City from January 2018 to December 2019. The comparison result was assessed based on the values of Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The result reveals that the RNN method has better RMSE and MAPE values, namely RMSE values of 0,377 and MAPE values of 1,596, than the Holt-Winter Adaptive Exponential Smoothing method with RMSE values of 0,500 and MAPE values of 0,620. It can be concluded that the non-linear model has better forecasting than the linear model. Therefore, the RNN model can be used in modeling and forecasting trend and seasonal time series.

Perbandingan Akurasi Peramalan Curah Hujan dengan menggunakan ARIMA, Hybrid ARIMA-NN, dan FFNN di Kabupaten Malang Bestari Archita Safitri; Atiek Iriany; Ni Wayan Surya Wardhani
Seminar Nasional Official Statistics Vol 2021 No 1 (2021): Seminar Nasional Official Statistics 2021
Publisher : Politeknik Statistika STIS

Time series analysis is an observation that is built on time sequences. Time series analysis is useful in various fields, especially meteorology. One aspect of meteorology is rainfall, which can have an impact on human life. Rainfall has a complicated pattern to predict, so we need the best method for forecasting rainfall. There are several methods that can analyze the intensity of rainfall. Methods that can be used to predict rainfall are ARIMA method, Feed Forward Neural Network (FFNN) method, and hybrid ARIMA-NN. This study aims to obtain the best rainfall modeling and prediction based on the three methods above. The rainfall data used came from the Mini Weather Station (MWS) at Supiturang and Manggisari hamlets. Based on the results of the study, at Supiturang, the best model was ARIMA(1,1,1) with RMSE of 3.4326. At Manggisari, the best model is Hybrid ARIMA(1,1,1) FFNN(4-9-1) with RMSE of 3.1056.

Co-Authors Achmad Efendi Adji Achmad Rinaldo Fernandes Agung Sugeng Widodo Agus Dwi Sulistyono, Agus Dwi Alim, Viky Iqbal Azizul Amanda, Devi Veda Ani Budi Astuti Aniek Iriany Arditama Putra Rochmanullah Arianto, Danang Arifin Noor Sugiharto Aris Subagiyo Asaliontin, Lisa Ashari, Ayu Aisyah Ayunda Sovia, Nabila Bambang Dwi Argo Bestari Archita Safitri Budi Astuti, Ani Cecep Kusmana Chairunissa, Abela Danang Ariyanto Darmanto Darmanto David Forgenie Dewi, Anggi Seftia Dhanny Septimawan Sutopo Elok Waziiroh Eni Sumarminingsih Faddli Lindra Wibowo Fernandes, Adji Fernandes, Adji Achmad Rinaldo Firdaus, Cahyani Jannah Fudianita, Citra Hamdan, Rosita Haneinanda Junianto, Fachira Hartawati, Hartawati Heni Kusdarwati Henny Pramoedyo Hidayat, Kamelia Hidayatulloh, Moh. Zhafran Indrayani, Fahmi Iwan Setiawan Junianto, Fachira Haneinanda Kamelia Hidayat Khoiril Anam, Khoiril Maghfiro, Maulidya Maghfiro, Maulidya Maisaroh, Ulfah Marhen Andan Prasetyo Mellysa Isnaini Moh. Zhafran Hidayatulloh Muhamad Firdaus Muhamad Ridwan Ni Wayan Surya Wardhani NI WAYAN SURYA WARDHANI Nikmatul Khoiriyah Novi Nur Aini Novi Nur Aini, Novi Nur Nugroho, Arief Budi Nugroho, Salma Fitri Nur Silviyah Rahmi Oktavia , Nur Sofi Sely Ola, Petrus Kanisius Pramaningrum, Dea Saraswati Prayudi Lestantyo Putra, Arditama Putri, Henida Ratna Ayu Rahma Fitriani Ridlo, Mahmuddin Rinaldo Fernandes, Adji Achmad Riza, Sativandi Rosyida, Diana Rudiat Sekarsari, Cindy Sepriadi, Hanifa Solimun Solimun Solimun Solimun, Solimun Suci Astutik Sugiarto S Sukamto, Ika Sumiyarsi Suryawardhani, Ni Wayan Sutopo, Dhanny Septimawan Ullah, Mohammad Ohid Utomo, Candra Rezzining Wulat Sariro Weni Waego Hadi Nugroho Wardhani, Ni Wayan Surya Wigbertus Ngabu Yuliana, Mila

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