Abdul Hoyyi
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

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ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUASAN MAHASISWA DALAM PEMILIHAN JURUSAN MENGGUNAKAN STRUCTURAL EQUATION MODELING (SEM) (Studi Kasus di Jurusan Statistika Universitas Diponegoro Semarang) Allima Stefiana Insani; Abdul Hoyyi; Rita Rahmawati
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.92 KB) | DOI: 10.14710/j.gauss.v3i4.7961

Abstract

University is an institution that provide educational service which has a wide variety of majors. Image of the university would affect the interest of new students in decision making process, as this will affect student satisfaction through the course. Many factors influence students decision in determining their aim majors, such as service quality, curriculum, environment and academic ability. These factors are latent variables then Structural Equation Modeling (SEM) used to determine factors effect that affect student satisfaction in selection of majors. The research conducted at Diponegoro University in Statistics Department. Overall model fit test obtain Goodness Of Fit on model with the value of GFI = 0,875 and         RMSEA = 0,084 are indicative of a good fit. In concluding the analysis, the factors that affect student satisfaction in decision to choose Statistics Department can be measured by academic ability, curriculum, and service quality. Students decision in choosing Statistics Department can be explained by the academic ability of students, the curriculum which is owned by Statistics Department and quality of service that is owned by the department of statistics at 96,9%. Statistics students satisfaction can be explained by academic ability of  students and student decision after choosing Statistics Department of 68,8%. Key words: Decision in choosing major, students satisfaction, Structural Equation Modeling
VERIFIKASI MODEL ARIMA MUSIMAN MENGGUNAKAN PETA KENDALI MOVING RANGE (Studi Kasus : Kecepatan Rata-rata Angin di Badan Meteorologi Klimatologi dan Geofisika Stasiun Meteorologi Maritim Semarang) Kiki Febri Azriati; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (619.071 KB) | DOI: 10.14710/j.gauss.v3i4.8081

Abstract

Forecasting method Box-Jenkins ARIMA (Autoregressive Integrated Moving Average) is a forecasting method that can provide a more accurate forecasting results. To verify the model obtained using the one Moving Range Chart. The control charts are used to determine the change in the pattern of file seen from the residual value (the difference between the actual file and the file forecasting). File used in this study the average wind speed in the Tanjung Emas harbor during January 2008 to December 2013. The best of Seasonal ARIMA model is ARIMA (0,0,1) (0,0,1) 12. The results of the verification using the Moving Range Control Chart on the model showed that all residual values are within control limits to the length of the shortest interval, means of verification results show that the model is a good model used for forecasting future periods. Forecasting is generated during the period of the next 15 shows the seasonal pattern. This is shown in the figure forecast 2014 average wind speeds are highest in January, as well as forecasting the 2015 figures the average speed of the highest winds also occurred in January. Forecasting results reflect past file, because the actual file used also showed a seasonal pattern with the same seasonal period is annual, where the numbers mean wind speeds are highest in January. Keywords : Seasonal ARIMA, Moving Range Control Chart, Mean wind speeds.
PENERAPAN SEASONAL GENERALIZED SPACE TIME AUTOREGRESSIVE SEEMINGLY UNRELATED REGRESSION (SGSTAR SUR) PADA PERAMALAN HASIL PRODUKSI PADI Leni Pamularsih; Mustafid Mustafid; Abdul Hoyyi
Jurnal Gaussian Vol 10, No 2 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i2.29435

Abstract

Ordinary Least Square (OLS) is general method to estimate Generalized Space Time Autoregressive (GSTAR) parameters. Parameter estimation by using OLS for GSTAR model with correlated residuals between equations will produce inefficient estimators. The method that appropriate to estimate the parameter model with correlated residuals between equations is Generalized Least Square (GLS), which is usually used in Seemingly Unrelated Regression (SUR). This research aims to build the seasonal GSTAR SUR model as model of rice yield forecasting in three locations by using the best weighting. Weights used are binary weights, inverse distance and normalization of cross correlation. Data which used in this research are the data of rice yield per quarter in three districts in Central Java, namely Banyumas, Cilacap and Kebumen. The data from the period of January 1981 to December 2014 as training data and the period of January 2015 to December 2018 as validation data. The resulting is a model that has a seasonal effect with the autoregressive order and the spasial order limited to 1 so the model formed is SGSTAR (41)-I(1)(1)3. The best model produced is the SGSTAR SUR (41)-I(1)(1)3 model with inverse distance weighting because it fulfills both assumptions, residuals white noise and residuals normally multivariate distribution. Additionally, it has the smallest MAPE value when compared the other weighting, that is 20%. This MAPE value indicates  that the accuracy rate of forecast is accurate.Keywords: Rice yield, Seasonal, GSTAR, SUR.
REGRESI ROBUST ESTIMASI-M DENGAN PEMBOBOT ANDREW, PEMBOBOT RAMSAY DAN PEMBOBOT WELSCH MENGGUNAKAN SOFTWARE R Aulia Desy Deria; Abdul Hoyyi; Mustafid Mustafid
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (583.535 KB) | DOI: 10.14710/j.gauss.v8i3.26682

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Robust regression is one of the regression methods that robust from effect of outliers. For the regression with the parameter estimation used Ordinary Least Squares (OLS), outliers can caused assumption violation, so the estimator obtained became bias and inefficient. As a solution, robust regression M-estimation with Andrew, Ramsay and Welsch weight function can be used to overcome the presence of outliers. The aim of this study was to develop a model for case study of poverty in Central Java 2017 influenced by the number of unemployment, population, school participation rate, Human Development Index (HDI), and inflation. The result of estimation using OLS show that there is violation of heteroskedasticity caused by the presence outliers. Applied robust regression to case study proves robust regression can solve outliers and improve parameter estimation. The best robust regression model is robust regression M-estimation with Andrew weight function. The influence value of predictor variables to poverty is 92,7714% and MSE value is 370,8817. Keywords: Outliers, Robust Regression, M-Estimator, Andrew, Ramsay, Welsch
Diversifikasi Olahan Ikan Bandeng oleh UKM Primadona dalam Program Pengabdian IbPE 2016-2018 Sugito Sugito; Alan Prahutama; Tarno Tarno; Abdul Hoyyi
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 10, No 1 (2019): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v10i1.3556

Abstract

Ikan bandeng merupakan bahan makanan yang tinggi akan protein, vitamin dan mineral. Salah satu cara untuk meningkatkan pemasaran adalah mix marketing, salah satunya adalah mix marketing produk. Mix marketing produk yang dapat dilakukan adalah dengan diversifikasi produk. Olahan ikan bandeng yang terkenal adalah di kabupaten Pati. UKM Primadona merupakan UKM yang bergerak pada olahan ikan bandeng dan merupakan salah satu UKM binaan dari Universitas Diponegoro dalam program pengabdian Ipteks bagi Produk Ekspor (IbPE) 2016-2018. Dalam binaan tersebut, yang menjadi salah satu program adalah diversifikasi produk UKM Diversifikasi produk yang dilakukan oleh UKM Primadona atas binaan tim pengabdi adalah keripik kulit dan abon duri ikan bandeng. Kulit ikan bandeng merupakan hasil filet dari daging ikan bandeng. Kulit ikan bandeng dicampur dengan tepung beras, tepung tapiokan dan rempah-rempah lainnya untuk diolah menjadi keripik kulit yang renyah. Tekstur keripik kulit ikan bandeng adalah renyah, mempunyai pola sisik ikan. Kandungan protein, vitamin dan mineral keripik kulit ikan bandeng juga cukup tinggi. Untuk abon duri ikan bandeng sangat berkhasiat karena kandungan kalsiumnya cukup tinggi.
Sosialisasi Pengelolaan Limbah Industri Batik pada Program IbPUD Kerajinan Batik Bakaran di Kabupaten Pati Jawa Tengah Abdul Hoyyi; Sugito Sugito; Hasbi Yasin
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 9, No 2 (2018): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v9i2.1785

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Batik Bakaran merupakan batik tulis khas Kabupaten Pati yang berasal dari Desa Bakaran, Kecamatan Juwana Jawa Tengah. Proses pembuatan batik tulis tidak terlepas dari apa yang dinamakan limbah. Limbah industri batik terdiri atas limbah cair, limbah padat dan limbah gas. Pengelolaan limbah yang kurang baik akan mengakibatkan pencemaran lingkungan dan bisa merusak ekosistem sekitarnya. Oleh karenanya perlu dilakukan sosialisasi pengelolaan limbah terhadap UKM-UKM Batik di Desa Bakaran Juwana Pati dengan narasumber dari Balai Besar Kerajinan dan Batik (BBKB) Yogyakarta. Metode pelaksanaan dilakukan dengan paparan materi dan diskusi aktif dengan UKM. Penanganan limbah bisa dilakukan melalui tahapan proses yaitu proses Kimia, proses Fisika dan proses Biologi. Dalam sosialisasi ini dibahas beberapa teknik pengelolaan limbah, dan lebih difokuskan kepada proses pada IPAL batik BBKB Yogyakarta. Tahapan prosesnya adalah: penyisihan lilin, pengendapan, koagulasi dan flokulasi, proses Biologi dan absorbsi arang aktif. Kegiatan ini diakhiri dengan kunjungan langsung dari BBPK ke lokasi pembuangan limbah industri batik.
Empowerment of Fruits Management through the Increasing Economic Value of Local Product on the Red Guava Cluster Abdul Hoyyi; Darwanto Darwanto
EKO-REGIONAL Vol 12, No 1 (2017)
Publisher : Jurusan Ilmu Ekonomi dan Studi Pembangunan Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1141.958 KB) | DOI: 10.20884/1.erjpe.2017.12.1.990

Abstract

EXPECTED SHORTFALL DENGAN SIMULASI MONTE-CARLO UNTUK MENGUKUR RISIKO KERUGIAN PETANI JAGUNG Rita Rahmawati; Agus Rusgiyono; Abdul Hoyyi; Di Asih I Maruddani
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.428 KB) | DOI: 10.14710/medstat.12.1.117-128

Abstract

In risk management, risk measurement plays an important role in allocating capital as well as in controlling (and avoiding) worse risk. Estimating the risk value can be done by using a risk measure. The most popular method for evaluating risk is Value at Risk (VaR). But VaR does not fulfill the coherency as a measure of risk effectiveness. In this paper, we propose Expected Shortfall (ES) which has coherency nature. ES is defined as the conditional expectation of losses beyond VaR of the same confidence level over the same holding period. For measuring ES, we use Monte-Carlo Simulation Method. This method is applied for measuring risk that will be faced by corn’s farmers due to the changes in corn prices in Pemalang city. The results show that the ES value is 0.085472 at 95% confidence level and one-month holding period. This number means that a farmer will face 8.5472% of investment as maximum loss exceeding of VaR.
Co-Authors Abdurakhman Abdurakhman Afifah Alrizqi Agus Rusgiyono Agus Somantri Ahmat Dhani Riau Bahtiyar Alan Prahutama Alan Prahutama Alifah Zahlevi Allima Stefiana Insani Alvi Waldira Alwi Assegaf Amelia Crystine Anggit Ratnakusuma Anggita, Esta Dewi Anik Nurul Aini Annisa Intan Mayasari ANNISA RAHMAWATI Ari Fakhrus Sanny Arief Rachman Hakim Arya Huda Arrasyid Aulia Desy Deria Avia Enggar Tyasti Bella Cynthia Devi Besya Salsabilla Azani Arif Bisri Merluarini Bitoria Rosa Niashinta Budi Warsito Budi Warsito Candra Silvia Chyntia Arum Widyastusti Cindy Wahyu Elvitra Darwanto Darwanto Dea Manuella Widodo Deby Fakhriyana, Deby Dede Zumrohtuliyosi Deden Aditya Nanda, Deden Aditya Dedi Rosadi Dermawanti Dermawanti Desriwendi Desriwendi Dewi Erliana Dewi Setya Kusumawardani Dhea Kurnia Mubyarjati Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Diah Safitri Diah Wulandari Dilla Retno Deswita Dwi Ispriyanti DWI RAHMAWATI Emyria Natalia br Sembiring Endah Cahyaningrum Erna Musri Arlita Esti Pratiwi Faiqotul Himmah Fiki Farkhati Firda Dinny Islami Fitra Ramdhani Gayuh Kresnawati Hasbi Yasin Hasbi Yasin Henny Setyowati Herwindhito Dwi Putranto Ikha Rizky Ramadani Indri Puspitasari Irfan Afifi Isowedha Widya Dewi Issabella Marsasella Christy Jeffri Nelwin J. O. Siburian Juli Sekar Sari, Juli Sekar Kartikaningtiyas Hanunggraheni Saputri Khotimatus Sholihah Khusnul Umi Fatimah Kiki Febri Azriati Koko Arie Bowo Kristika Safitri Kumo Ratih Leni Pamularsih Maidiah Dwi Naruri Saida Malik Hakam Mega Fitria Andriyani Mega Fitria Andriyani Mia Anastasia Sinulingga Moch. Abdul Hoyyi Moch. Abdul Mukid Moch. Abdul Mukid MUHAMMAD HARIS Mustafid Mustafid Mustafid Mustafid Mutiara Ardin Rifkiani Nadya Kiki Aulia Nandang Fahmi Jalaludin Malik Novika Pratnyaningrum Nurissalma Alivia Putri Nurul Fauziah Ovie Auliya’atul Faizah Priska Rialita Hardani Purina Pakurnia Artiguna Rita Rachmawati Rita Rahmawati Rita Rahmawati Rizki Pradipto Widyantomo Rizky Oky Ari Satrio Rukun Santoso Saputri, Ani Funtika Saraswati, Mei Sita Shaumal Luqman Silvia Nur Rinjani SITI NURLATIFAH Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suparti Suparti Suparti Suparti Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Tatik Widiharih Titis Nur Utami Tresno Sayekti Nuryanto Triastuti Wuryandari Triastuti Wuryandari Trisnawati Gusnawita Berutu Ubudia Hiliaily Chairunnnisa Ulfah Sulistyowati Yosi Dhyas Monica Yuciana Wilandari Yuciana Wilandari Yudia Yustine Yunisa Ratna Resti Yustian Dwi Saputra