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All Journal PROSIDING SEMINAR NASIONAL Media Statistika SAINS DAN MATEMATIKA Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang E-Dimas: Jurnal Pengabdian kepada Masyarakat Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) EKO-REGIONAL JURNAL PENGEMBANGAN EKONOMI WILAYAH

Abdul Hoyyi

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 3131506

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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PENDEKATAN REGRESI LINIER MULTIVARIAT UNTUK PEMODELAN INDEKS PEMBANGUNAN MANUSIA (IPM) DAN PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH Abdul Hoyyi; Diah Safitri; Sugito Sugito; Alan Prahutama
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 2 (2018): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Model regresi multivariat merupakan model regresi yang dibangun dari beberapa variabel independen dan mempunyai variabel dependen lebih dari satu dengan setiap variabel dependen saling berkorelasi. Pada penelitian ini variabel dependennya adalah Indeks Pembangunan Manusia (IPM) dan jumlah penduduk miskin, sedangkan variabel independennya adalah upah minimum regional dan kepadatan penduduk. Data yangdigunakan adalah data sekunder yang diperoleh dari Badan Pusat Statistika (BPS) Propinsi Jawa Tengah. Parameter pada model diestimasi dengan metode kuadrat terkecil. Berdasarkan hasil dan pembahasan, pada taraf signifikansi 5 % diperoleh hasil bahwa variabel IPM dan persentase penduduk miskin berdistribusi normal multivariat.Pengujian parameter model diperoleh bahwa koefisien variabel upah minimum regional dan kepadatan penduduk signifikan terhadap model. Pengujian asumsi normalitas, homoskedastisitas dan nonautokorelasi memberikan kesimpulan eror berdistribusi normal multivariate, tidak terjadi autokorelasi dan varian dari eror homogen. Hasil akhir memberikan kesimpulan bahwa variabel upah minimum regional dan kepadatanpenduduk dapat menjelaskan Indeks Pembangunan Manusia dan persentase penduduk miskin sebesar 70,11 %. Kata kunci : Regresi multivariat, IPM, BPS.

ANALISIS ANTREAN DENGAN SISTEM JUMLAH KEDATANGAN BERDISTRIBUSI BETA, WEIBULL, NORMAL, DAN ERLANG (STUDI KASUS GERBANG TOL MUKTIHARJO) Sugito Sugito; Erna Musri Arlita; Diah Safitri; Abdul Hoyyi; Rita Rachmawati
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 1 (2018): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Semarang is the capital city of Central Java Province so that development in Semarang City progressed very rapidly, this requires transportation facilities and infrastructure that good, smoothly and efficiently. One of the important transport infrastructure for Semarang City is a toll road. Muktiharjo toll gate is one of the exiting toll gate in Semarang City. Muktiharjo toll gate provides two types of service namely booths toll booths, a regular and automated toll booths. The existances two types of toll booths that provided the analysis needs to be done, then the line to find out how the system line that is in Muktiharjo toll gate. The research result obtained the model line at the Muktiharjo toll gate (BETA / G / 3) :( GD / ¥ / ¥) for regular toll road of Surabaya-Semarang direction, (WEIB / G / 1) :( GD / ¥ / ¥) for the Surabaya-Semarang automatic toll booth, (NORM / G / 2) :( GD / ¥ / ¥) for the regular toll road of Semarang-Surabaya and (ERLA / G / 2) :( GD / ¥ / ¥) Semarang-Surabaya automatic toll road. Based on simulation using Arena software, the addition of substations can reduce the waiting time of vehicles in line, while substation reduction can extend the waiting time of vehicles in line.Keyword : Queue theory, Queue simulation, Regular toll gate, Automatic toll gate, Arrival, Service.

PEMODELAN INDEKS HARGA KONSUMEN DI JAWA TENGAH DENGANMETODE GENERALIZED SPACE TIME AUTOREGRESSIVE SEEMINGLY UNRELATED REGRESSION (GSTAR-SUR) Mega Fitria Andriyani; Abdul Hoyyi; Hasbi Yasin
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 2 (2018): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

The Generalized Space Time Autoregressive (GSTAR) model with Seemingly Unrelated Regression (SUR) estimation method or often called GSTAR-SUR is more efficient to be used for residual correlation than Ordinary Least Square (OLS) estimation method. The SUR estimation method utilizes residual correlation information to improve the estimated efficiency resulting in a smaller standard error. The purpose of this research is to get the GSTAR-SUR model according to Consumer Price Index (CPI) data in four regencies or cities in Central Java namely Purwokerto, Surakarta, Semarang, and Tegal. Based on the assumed white noise assumption, the smallest MAPE and RMSE averages, the best model chosen in this research is the GSTARSUR(11)I(1) model with the heavy of normalized cross-correlation with the average MAPE value of 0.4455% and RMSE value of 0.80582. The best model obtained explains that the CPI data in Purwokerto, Semarang, and Tegal not only influenced by the previous time but also influenced by the locations. Meanwhile, the CPI data in Surakarta is only influenced by the previous time, but it is not affected by other locations. Keywords : SUR, OLS, Consumer Price Index

MANAJEMEN PRODUKSI PENGOLAHAN IKAN BANDENG DI KABUPATEN PATI UNTUK PENGEMBANGAN PRODUK EKSPOR Sugito -; Alan Prahutama; Abdul Hoyyi
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: PROSIDING IMPLEMENTASI PENELITIAN PADA PENGABDIAN MENUJU MASYARAKAT MANDIRI BERKEMAJUAN
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (228.871 KB)

Central Java as one of the regions in Indonesia which has various food preparations. One typical souvenirs Semarang, which is the capital of Central Java province is milkfish presto, milkfish brains, chips and shredded milkfish milkfish. Aquaculture fish of the largest in Central Java is located in Pati regency. One of the famous places that serve as souvenirs of milkfish is Juwana area, Pati. Many SMEs (Small and Medium Enterprises) in Pati engaged in the processing of aquaculture fish, one of which is milkfish presto. In this paper, the researchers took two of SMEs as a form of field studies engaged in the processing of fish. SMEs are SMEs milkfish Presto twin source of fortune and SMEs banding without thorns excellent. Both of us empower SMEs for the development of export products. In the first year field study outcome shows that the manufacture of standard operating procedures (SOP) and product diversification is the first step the product criteria ekspor. Also marketing techniques is an important factor in the expansion of the market.Keywords: Processed milkfish; Diversification of products; marketing Management; SOP; SME in Pati.

REGRESI KOMPONEN UTAMA ROBUST S-ESTIMATOR UNTUK ANALISIS PENGARUH JUMLAH PENGANGGURAN DI JAWA TENGAH Jeffri Nelwin J. O. Siburian; Rita Rahmawati; Abdul Hoyyi
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Robust principal component regression s-estimator is principal component regression that applies robust approach method at principal component analysis and s-estimator at principal component regression analysis. The aim of robust principal component regression s-estimator is to overcome multicollinearity problems in multiple linier regression Ordinary Least Square (OLS) and to overcome outlier problems in principal component regression so get the most effective model. Minimum Volume Ellipsoid (MVE) is one of the robust approach methods that applied when doing principal component analysis and S-Estimator is one of the estimation methods that applied when doing principal component regression analysis. The case in this study is the factors that influence the Number of Unemployment in Central Java in 2017. The model that provides the most effective result to handling multicolliniearity and ouliers in the case study Number of Unemployment in Central Java in 2017 is using robust principal component regression MVE-(S-Estimator) with Adjusted R2 value of 0.9615 and RSE value of 0.4073. Keywords: Robust Principal Component Regression S-Estimator, Multicollinearity, Outliers, Minimum Volume Ellipsoid (MVE), Number of Unemployment.

ANALISIS KEPUASAN DAN LOYALITAS PELANGGAN DALAM PEMESANAN TIKET PESAWAT SECARA ONLINE MENGGUNAKAN PENDEKATAN PARTIAL LEAST SQUARE (PLS) Trisnawati Gusnawita Berutu; Abdul Hoyyi; Sugito Sugito
Jurnal Gaussian Vol 7, No 4 (2018): 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.v7i4.28863

Technology advances are bring rapid changes, thus bringing the world to the information society. From this technological progress thus e-commerce emerged, as a means to meet the needs of goods and services through internet access (online). This is what the airlines utilized by cooperating with various internet service providers (online), to provide convenience and comfort of airplane passengers in buying tickets without having to come directly to the place and through intermediaries. To provide the best service, need to know what factors that influence customer satisfaction in ordering airline tickets online. Appropriate modeling for this problem using structural equation modeling, with Partial Least Square (PLS) approach. The PLS approach is chosen because it is not based on several assumptions, one of these is the normal multivariate assumption. In this research, the exogenous latent variables used are performance, access, security, sensation, information, and web design, while the endogenous latent variables are satisfaction and loyalty. Based on the results of the analysis it can be concluded that the latent variables of access, security, sensation, information, and web design are able to explain the latent satisfaction variable of 70.32% while the satisfaction latent variable is able to explain the latent variable of loyalty by 36.02%.

PENDEKATAN METODE SERVQUAL DAN KLASTER FUZZY K-MEANS UNTUK MENGANALISIS INDEKS KEPUASAN NASABAH BANK X Dewi Erliana; Mustafid Mustafid; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Servqual (service quality) is a method for measuring the service quality of each dimension attribute. Servqual dimensions include tangibles, empathy, responsiveness, reliability, and assurance. Cluster analysis is a technique for classifying objects that have the same characteristics in a relatively homogeneous group. One method of cluster is Fuzzy k-Means (FKM). Classification object with FkM, the existence each data point in a cluster is determined by the degree of membership. Determination of the optimum number of clusters using the accuracy measure Xie Beni index (XB). XB index calculation depends on the objective function or distance data to each cluster center, the distance between the center of the cluster, and weighted (fuzzifier). Based on the optimum number of clusters, then will be calculated percentage of Customer Satisfaction Index (CSI). This research is based on a case Bank X customers through questionnaires of customer satisfaction based on the servqual dimension. Result of the research showed the optimum number of cluster 4 and weight 1.1. Customers in cluster 1 was 84.36 % very satisfied with most of the service quality Bank X. Customer in cluster 2 was 72.79 % satisfied, but they think there was nothing more conspicuous of service quality in Bank X. Customer in cluster 3 are satisfied with the value of 77.66 % satisfaction primarily to the ease in submitting a complaint.

METODE LENTH PADA RANCANGAN FAKTORIAL FRAKSIONAL 3^(k-p) DENGAN ESTIMASI EFEK ALGORITMA YATES Mutiara Ardin Rifkiani; Rita Rahmawati; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Factorial design often is used in experiments on various fields to identify the influence of main factors and interaction factors to respons were observed. A design which has k factors with three levels for each factor called factorial design. For a large number of factors, fractional factorial design is an effective alternative because it has less combination of treatment than factorial design, but it still has important needed information. In experiments conducted without repetition, determining factors that influence towards response is difficult to be analyzed if using analysis of variance. It was due to the the average of squared error absence, where error variance estimation is based on the variability of the data obtained from repeated observations. To overcome this, we use Lenth Method to identify the factors that affect the response. Lenth method uses the value of the statistic margin of error (ME) test for the main factor, and simultaneous margin of error (SME) for the interaction factor. The calculation of the statistic test ME and SME values are based on the estimated effects of each treatment. Yates algorithm is used to calculate the effect’s estimation for each treatment. To clarify the discussion about this matery is given an example of fractional factorial design application with 27 experiments on combustion boiler. The results indicate that treatment factors are influenced towards the response are , , , dan . Keywords: three-level fractional factorial, factorial without replication, Lenth Methods, Yates Algorithm

STRUCTURAL VECTOR AUTOREGRESSIVE UNTUK ANALISIS DAMPAK SHOCK NILAI TUKAR RUPIAH TERHADAP DOLAR AMERIKA SERIKAT PADA INDEKS HARGA SAHAM GABUNGAN Annisa Rahmawati; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Instability and depreciation of the rupiah be a motivating factor for investors to pull out a portfolio in Indonesia. The weakening of rupiah led to a decline in investor demand for stocks. Measurement of stock price fluctuations or portfolio using the Composite Stock Price Index (CSPI). The exchange rate and CSPI is a sensitive macroeconomic variables affected by shock and it takes restriction of macroeconomic structural model. Based on this, Structural Vector Autoregressive (SVAR) model is used. The purpose of this thesis is to analyze the impact of the exchange rate shock on CSPI through the description of Structural Impulse Response Function and Structural Variance Decomposition modeling based on a restriction on SVAR. SVAR also called the theoretical VAR used to respond to criticism on the VAR model where necessary the introduction of restrictions on economic models. By using daily data exchange rate of the rupiah against the US dollar and CSPI from January 2013 to December 2016 acquired the VAR model is stable and meets the white noise assumption as the basis for modeling residual SVAR and has a short-term restriction. The response of CSPI from the impact of the shock rupiah exchange rate is likely to experience an increase, while the response to the shock CSPI itself is fluctuating but tends to decrease. Patterns proportion shock effect on the exchange rate is increasingly rising stock index in the period of time, whereas the effect of the shock CSPI itself getting down on each period of time. Keywords : exchange rate, CSPI, SVAR, Structural Impulse Response Function, Structural Variance Decomposition

PEMODELAN KURS RUPIAH TERHADAP DOLLAR AMERIKA SERIKAT MENGGUNAKAN REGRESI PENALIZED SPLINE BERBASIS RADIAL Kartikaningtiyas Hanunggraheni Saputri; Suparti Suparti; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Exchange rate is the price of a currency from a country that is measured or expressed in another country's currency. A country's currency exchange rate has fluctuated due to exchange rate determined by the demand and supply of the currency. One of method that can be used to predict the exchange rate is the classical time series analysis (parametric). However, the data exchange rate that fluctuates often do not fulfill the parametric assumptions. Alternative used in this research is penalized spline regression which is nonparametric regression and not related to the assumption of regression curves. Penalized spline regression is obtained by minimizing the function Penalized Least Square (PLS). To handle the numerical instability and changing data then used radial basis at Penalized spline estimator. Selection of the optimal models is rely heavily on determining the optimal lambda and optimal knot point that is based on the Generalized Cross Validation (GCV) minimum. Using data daily exchange rate of the rupiah against the US dollar in the period of June 2, 2014 until February 27, 2015, the optimal penalized spline bases on radial model in this study is when using 2 order and 13 knots point, those points are 11625; 11669; 11728; 11795; 11911; 11974; 12069; 12118; 12161; 12372; 12452; 12550; 12667 with GCV = 3904.8.Keywords: exchange rate, penalized spline, radial bases, penalized least square, generalized cross validation

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

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