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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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KLASIFIKASI PERUBAHAN HARGA OBLIGASI KORPORASI DI INDONESIA MENGGUNAKAN METODE NAIVE BAYES CLASSIFICATION Khotimatus Sholihah; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Bond is a medium-long term debt securities which can be sold and contains a pledge from the issuer to pay interest for a certain period and repayment of the principal debt at a specified time to the bonds buyer. Bonds price changes any time, it could be beneficial or give disadvantage to investors. Investors should know the best conditions to buy bonds on a discount, or sell them at a premium price. By classify the changing of bonds price, it could help investors to gain optimum return. One method is Naive Bayes classification. In theory, It has the minimum error rate in comparison to all other classifiers. Bayes is a simple probabilistic-based prediction technique which based on the application of Bayes theorem with strong independence assumptions. Before classifying, preprocessing data is required as a stage feature selection. In this case, the Mann Whitney test can be done to choose the independent features of each class. Validation technique in use is k-fold cross validation. Based on analysis, we gained average accuracy at 78,52% and 21,8% error. With high accuracy and quite low error, it means that the Naïve Bayes method works quite well on classifying the corporate bonds price changes in Indonesia. Keywords: bonds, classification, k-fold cross validation, Naive Bayes

VECTOR AUTOREGRESSIVE STABILITY CONDITION CHECK UNTUK PEMODELAN DAN PREDIKSI SUMBER PENERIMAAN PABEAN BELAWAN Mia Anastasia Sinulingga; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Customs Intermediate are an institution that is responsible for regulating the flow of export and import trade activities in the Customs Area with the revenue coming from import duties and export duties. The time series data from the customs acceptance component import dan export which have a relationship between variables. Vector Autoregressive is a statistical method used in predicting and evaluating interrelationships between variables. The purpose of this study is to obtain a model for predicting import and export by using the VAR model and detecting the stability of the model. Model requirements are said to be stable if all modulus values from roots characteristic of coefficient matrices ≤ 1 that the predicted results can be verified. The data is divided into in sample data starting from January 2010 to June 2018 and out sample data starts from July 2018 until December 2018. The results of data analysis in this study, the model obtained for prediction is the VAR model (4) and there is a direct relationship between both variables. The VAR (4) residual model fulfills the assumption of white noise, while the assumption of multivariate normality is not fulfilled. Based on out sample the value of MAPE for import variables 18.42%, export 12.94% shows the VAR model (4) has good predictive capabilities that can be used for predicting future periods. Predicted results on import show fluctuations during the period of January to December 2019 while in the export shows increase during the period of January to December 2019.

PENDEKATAN SISTEM PERSAMAAN SIMULTAN DALAM PEMODELAN PRODUK DOMESTIK REGIONAL BRUTO (PDRB) PROPINSI JAWA TENGAH TAHUN 2000-2010 Rizky Oky Ari Satrio; Tatik Widiharih; Abdul Hoyyi
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Gross Domestic Product (GDP) is general indicator used to identify the economical development in a region. The condition of economy in Central Java Province is categorized as stable condition since it has GDP value developed rapidly year by year. Refer to model used by Bappenas,the simultaneous equation model between GDP is influenced by number of employee and government spending.Identification of the model in this study using the ordercondition of indetification on the basis of the result of the overidentified taken the GDP of agriculture, mining, electricity, gas and water sector and trade. Therefore, the parameter evaluation used is 2SLS method (Two Stage Least Square). After fulfilled assumption of independent, identical and normal distribution, the most valued toward model of GDP in Central Java Province is GDP sector of agriculture.

ANALISIS PEMBENTUKAN PORTOFOLIO OPTIMAL SAHAM DENGAN PENDEKATAN OPTIMISASI MULTIOBJEKTIF UNTUK PENGUKURAN VALUE AT RISK Fiki Farkhati; Abdul Hoyyi; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 3 (2014): 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.v3i3.6448

Mean Variance Efficient Portfolio (MVEP) is theory of portfolio which purposed to standard investor because approach has only one objective that minimize portfolio risk. Portfolio with multi-objective optimization that simultaneously maximize portfolio return and minimize portfolio risk with various weighting coefficient k represents risk aversion index. The purpose of this research is analyze proportion each stock in order that is formed optimal portfolio approach multi-objective optimization and analyze expected return and risk that suitable with preference investor. This research is based on cases stocks ASII, TLKM, SMGR, UNVR and LPKR. As a specific example investment Rp 50.000.000,00 in 20 days with 95% degree of confidence. Optimal portfolio for risk seeker investor is portfolio with k = 0,01 with expected profit Rp 1.547.392,00 and risk estimation Rp 33.832.562,00. Optimal portfolio for risk indifference investor is portfolio with 1 ≤ k ≤ 100 with expected profit Rp 965.678,00 until Rp 1.435.038,00 and risk estimation Rp 19.500.464,00 until Rp 25.513.351,00. Optimal portfolio for risk averse investor is portfolio with k = 10000 with expected return Rp 950.414,00 and risk estimation Rp 19.495.116,00.

ANALISIS SISTEM ANTRIAN PESAWAT TERBANG DI BANDARA INTERNASIONAL AHMAD YANI SEMARANG Anggit Ratnakusuma; Abdul Hoyyi; Sugito Sugito
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Long queuing is not expected by anyone, because it’s taking much time and tiresome. However, this situation is not avoidable in public area, for example Ahmad Yani International Airport Semarang. Aircraft queuing that will take off and landed resulted in increasing of the queuing of passengers to aboard. The suitable queuing system model for Ahmad Yani Internasional Airport Semarang to solve its air traffic is using (M/M/6):(GD/∞/∞), with six aprons as server of reguler commercial flight. Moreover, based on the result of system performance measure, service system in Ahmad Yani Internasional Airport Semarang report is good enough. The result of system performance measure said that average number of aircraft in the system (Ls) was 1,0716 aircraft per hour, average number of aircraft in the queue (Lq) was 0,0002 aircraft per hour, average time aircraft spends in the system (Ws) was 0,4977 from an hour, and average time aircraft spends in the queue (Wq) was 0,0001 from an hour. The simulation showed that by using four operating server or adding two more arrival additionals in every hour, the service system is quite effective. Keywords: Queuing System Model, Ahmad Yani International Airport Semarang

ANALISA FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN DAN KEPUASAN KONSUMEN PADA LAYANAN INTERNET SPEEDY DI KOTA SEMARANG MENGGUNAKAN PARTIAL LEAST SQUARE (PLS) Bella Cynthia Devi; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Persepsi konsumen terhadap tuntutan kebutuhan layanan internet Speedysangat beragam. Terdapat beberapa faktor yang dipertimbangkan konsumen sebelum menggunakan layanan akses internet, faktor tersebut diantaranya harga, merek dan kualitas. Di lain pihak, konsumen akan merasa puas jikalayanan internet Speedy melebihi harapan konsumen. Faktor-faktor yang mempengaruhi keputusan pembelian dan kepuasan layanan internet Speedy diungkapkan secara komprehensif dengan persamaan struktural berbasis komponen, Partial Least Square (PLS). PLS mengestimasi model hubungan antar variabel laten dan antar variabel laten dengan indikatornya. Dari hasil analisis diperoleh kesimpulan bahwa keputusan pembelian layanan internet Speedy dipengaruhi oleh harga, merek dan kualitas, sedangkan kepuasan konsumen dipengaruhi oleh keputusan pembelian dan kualitas. Kata kunci : Partial Least Square, Speedy, keputusan pembelian, kepuasanANALISA FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN DAN KEPUASAN KONSUMEN PADA LAYANAN INTERNET SPEEDY DI KOTA SEMARANGMENGGUNAKAN PARTIAL LEAST SQUARE (PLS)

PEMODELAN VOLATILITAS RETURN PORTOFOLIO SAHAM MENGGUNAKAN FEED FORWARD NERURAL NETWORK (Studi Kasus :PT Bumi Serpong Damai Tbk. Dan PT H.M Sampoerna Tbk.) Rizki Pradipto Widyantomo; Abdul Hoyyi; Tatik Widiharih
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Time series analysis is an analysis used to predict a time-observed data, one of which is the ARIMA model. ARIMA model assumes a constant residual variance (homogeneous). While financial data usually produce ARIMA model with variance error that is not constant. If the assumption of homogeneity of the residual variance is not met, then the method that can be used is ARCH or GARCH model. Another method that can be used on the data assuming the homogeneity of the variance error is not met is the Neural Network model. In this model we use Neural Network model with variance and residual as the input variables that obtained from ARCH / GARCH model. The data used are BSDE and HMSP asset portfolio returns from November 14, 2016 to January 18, 2018. In this study the selected input variables are from ARIMA (1.0.1) GARCH (1,1) model. The best Neural Network model obtained is Neural Network model with 10 hidden layers with MSE value 6.58 x10-10 with model train evaluation which is MAPE value 1.14441%.Keywords: Time series Analysis, ARCH / GARCH, Neural Network, Return.

PERHITUNGAN BIAYA TAMBAHAN DENGAN METODE ACCRUED BENEFIT COST PADA PENDANAAN PROGRAM PENSIUN MANFAAT PASTI Siti Nurlatifah; Sudarno Sudarno; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Supplemental costs in funding pension plan is a cost to be issued by the employer to the pension fund in case shortage of funds (deficit) in the funding of defined benefit plans. There are several methods can be used, one of them is accrued benefit cost method. This research explained about the calculation of the supplemental costs on defined benefit plans with a case study on BMKG Semarang. The data used 34 BMKG employee salaries who had not attained 50 years old in 2015. The calculation is done by concern the beginning of an employee salary, interest rate, period of employment, and increase of salary rate. Supplemental costs that must be issued by BMKG in 2015 is Rp. 81.748.084. That cost can sufficient the pension benefits that will be received by the employee if the funding was deficit. If the funding pension had a surplus, that cost can be used as an investment company. Keywords: supplemental cost, defined benefit plans, accrued benefit cost.

PENINGKATAN PRODUKTIVITAS BENANG POLYESTER COTTON 45 MELALUI ANALISIS TOTAL QUALITY CONTROL (Studi kasus di PT Panca Bintang Tunggal Sejahtera) Afifah Alrizqi; Yuciana Wilandari; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

PT Panca Bintang Tunggal Sejahtera is a company which operate in textill and garment. The main product is polyester cotton 45 yarn. In the production activity, still failed product. To determine what factors caused the failure of polyester cotton 45 yarn, used the analysis of Total Quality Control to control devices such as check sheet, stratification, bar chart, control chart, cause and effect diagrams, Pareto charts, and scatter plot. From the results of the check sheet, stratification and histogram obtained the highest type of failure is uneven sliver, which is as much as 1871 kg for a month. From the individual unit control chart, indicated that the activities of the production process there are deviations which are beyond the limits of product controllers that need improvement. A cause and effect diagram result show that the biggest factor causing the failure of the product due to labor factor due to lack of training and supervision. Therefore, the company can make improvements with priority on the labor factor.

PEMILIHAN INPUT MODEL ADAPTIVE FUZZY INFERENCE SYSTEM (ANFIS) BERBASIS LAGRANGE MULTIPLIER TEST DILENGKAPI GUI MATLAB (Aplikasi pada Data Harga Beras Kualitas Rendah di Indonesia Periode Januari 2013 – Februari 2019) Khusnul Umi Fatimah; Tarno Tarno; Abdul Hoyyi
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Adaptive Neuro Fuzzy Inference System (ANFIS) is a method that uses artificial neural networks to implement fuzzy inference systems. The optimum ANFIS model is influenced by the selection of inputs, number of membership and rules. In general, the selection of ANFIS input is based on Autoregressive (AR) unit as a result of ARIMA preprocessing. Thus it requires several assumptions. In this research, an alternative selection of ANFIS input based on Lagrange Multiplier Test (LM Test) is used to test hypothesis for the addition of one input. Preprocessing is conducted to obtain the value of partial autocorrelation against Zt. The input lag variable which has the highest partial autocorrelation is the first input ANFIS. The next input selection is selected based on LM test for adding one variable. To test the performance of LM Test, an empirical study of two groups of generated data and low quality rice prices is conducted as a case study. Generating data with stationary and non-stationary criteria has a good performance because it has very good forecasting ability with MAPE out sample for each characteristic are 5.6785% and 9.4547%. In the case study using LM Test, the selected input are and with the number of membership 2. The chosen model has very good forecasting ability with MAPE outsampel 6.4018%. Keywords : ANFIS, ANFIS Input, LM-Test, Low Quality Rice Prices, Forecasting

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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