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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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PEMODELAN FUNGSI TRANSFER DAN BACKPROPAGATION NEURAL NETWORK UNTUK PERAMALAN HARGA EMAS (Studi Kasus Harga Emas Bulan Juli 2007 sampai Februari 2019) Silvia Nur Rinjani; Abdul Hoyyi; Suparti Suparti
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The prestige of investment is increasingly rising as the people educates in managing finances. Gold is an alternative that most people tend to choose to invest. One of the important knowledge in gold investing is to predict the price in the future with factors that influence the price of gold. Therefore, in this research we made a model of gold prices based on crude oil prices. One method to forecast gold prices based on crude oil prices is the transfer function and backpropagation neural network. The results of transfer function model will be used as input for the backpropagation neural network method. The purpose of this research is to get the right forecasting method through the transfer function and backpropagation neural network model that can be used to predict gold prices. The results showed that the transfer function model with b = 0, r = [2], s = 0 and the ARMA noise model (0, [6]) is the best model to forecast the price of gold with the MAPE value of data out sample as 3,3507%. Keywords : Gold Price, Crude Oil Prices, Transfer Function,Backpropagation Neural Network, Forecasting

PENGELOMPOKAN PROVINSI-PROVINSI DI INDONESIA MENGGUNAKAN METODE WARD (StudiKasus: Produksi Tanaman Pangan di Indonesia Tahun 2018) Besya Salsabilla Azani Arif; Agus Rusgiyono; Abdul Hoyyi
Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cluster analysis is a technique for grouping objects or observations into homogeneous groups. Cluster analysis is divided into two methods, namely hierarchy and non-hierarchy. The hierarchy method generally involves a series of n-1 decisions (n is the number of observations) that combine observations into a tree-like structure or dendogram. Hierarchy is divided into two methods, namely agglomerative (concentration) and splitting (distribution). For non-hierarchical methods, the number of clusters can be determined by the researcher. Ward method is a hierarchical cluster analysis method that can maximize homogeneity in the cluster. The Sum-of-Square (SSE) formula is used in this method to minimize variations in the clusters that are formed. In this research, squared euclid distance is used to measure the similarity between object pairs. The data used in this study are secondary data on food crop production, namely rice, corn, soybeans, peanuts, green beans, sweet potatoes, and cassava in Indonesia 2018. To determine the cluster, the elbow method is used to form optimal clusters using WSS formula. Based on the analysis results, it was found that the optimal cluster is four clusters. The first cluster consists of 9 Province, the second cluster consists of 20 Province, the third cluster consists of 1 Province, the fourth cluster consists of 2 Province, and the fifth cluster consists of 2 Province.Keywords: Food Crop, Cluster Analysis, Ward Method, Squared Euclid, Elbow Method

PENGUKURAN PROBABILITAS KEBANGKRUTAN OBLIGASI KORPORASI DENGAN SUKU BUNGA VASICEK MODEL MERTON (Studi Kasus Obligasi PT Bank Lampung, Tbk) Kumo Ratih; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Bond is one of financial instrument that have lower investment risk than stock. One of investment risk is credit risk. Its refers to the risk due to unexpected changes in the credit quality of a counterparty or issuer on maturity date. There are two ways in the modelling of credit risk, structural model and reduced models. The structural model introduced by Black-Scholes (1973) and Merton (1974). On the Merton model assume that default occurs when the firm can not pay the coupon or face value at the maturity date. The interest rate on this model asssumed following Vasicek rate. An empirical study using corporate bond of PT Bank Lampung, Tbk with 300 billion face value. Value of Probability of Default 0,0000007910811% provethat PT Bank Lampung still can full their obigation at November 2012.

PENERAPAN METODE KORESPONDENSI BERSAMA UNTUK ANALISIS PERUBAHAN PERILAKU PENGGUNA SMARTPHONE Isowedha Widya Dewi; Mustafid Mustafid; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Competition is extremely tight in the technology sector including smartphones , the manufacturers compete to satisfy the desire of consumers with a variety of innovations. This study aims is form joint correspondence plot to determine whether consumers switch from one type to the other types of smartphones, as well as knowing what respondents consider when buying a smartphone . By adding a time variable data on methods of joint correspondence, changes in consumer behavior can be determined within a certain time . Time variables used was from 2011 to 2013 and smartphones that will be compared is Blackberry, Android and iOS. From the resulting graph can be seen that many kinds of smartphones used in each time variable and variables that affect the time of purchase . After doing research , showed that smartphone users in 2011, mostly used a Blackberry switched to Android in 2012 and 2013. Blackberry users at the time of puchase paid attention to the brand , color , design , and camera , but did not pay attention to prestige . Android users paid attention to completeness of the application , RAM , data capacity , color , resale price and network coverage . While iOS is not widely used by respondents from 2011 to 2013. iOS users considered the prestige , but did not consider the brand , design and battery life.

ANALISIS INTERVENSI FUNGSI STEP (Studi Kasus Pada Jumlah Pengiriman Benda Pos Ke Semarang Pada Tahun 2006 – 2011) Amelia Crystine; Abdul Hoyyi; Diah Safitri
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Data time series yang dipengaruhi oleh beberapa kejadian yang disebut intervensi akan mengakibatkan perubahan pola data pada satu waktu t. Analisis intervensi terdiri dari dua fungsi yaitu fungsi step dan fungsi pulse.Time series data that are influenced by several events called the intervention will lead to changes in the pattern of data at a t time. Analysis of intervention consists of two functions, that is the step function and pulse function. Intervention of step function represents an intervention that have long-term effects, whereas pulse function represents an intervention that takes place at a particular time. Step function intervention model was created based on the delay time of the intervention (b), the length of the intervention effect (s), and the pattern of intervention effects that was occured after b + s period (r). Intervention modeling was done after ARIMA (Autoregressive Integrated Moving Average) model was acquired. ARIMA model was used to determine the b, s, and r order of intervention. In this study, the step function intervention analysis was used to assess the amount of postage on the period January 2006 to February 2011. Based on the analysis, the ARIMA model produced was ARIMA (0,1,1). Based on intervention response obtained residual value b = 4, s = 0, r = 2 is used to form a model of intervention using the least squares method.

ANALISA FAKTOR-FAKTOR YANG MEMPENGARUHI KINERJA PERUSAHAAN MENGGUNAKAN PENDEKATAN PARTIAL LEAST SQUARE (Studi Kasus pada PT. Telkom Indonesia Divisi Regional Jawa Tengah-DIY dan Wilayah Telekomunikasi Semarang) Endah Cahyaningrum; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Persaingan dalam pasar global membawa banyak perubahan yang cukup dinamis pada semua aspek di suatu perusahaan. Hal ini menimbulkan trend baru dimana perusahaan yang berkelanjutan bergantung pada kemampuan perusahaan dalam merespon perubahan-perubahan yang ada secara efektif. Adanya sejumlah keunikan yang menjadi karakteristik sebuah perusahaan dan tidak dimiliki perusahaan lain dapat menciptakan faktor-faktor yang dapat meningkatkan suatu kinerja perusahaan. Faktor-faktor yang mempengaruhi kinerja perusahaan pada PT. Telkom Indonesia diungkapkan secara komprehensif dengan persamaan struktural berbasis komponen, Partial Least Square (PLS). PLS merupakan metode analisis yang tidak didasarkan pada banyak asumsi. Pada PLS tidak diperlukan asumsi normal multivariat, dapat menggunakan skala pengukuran nominal, ordinal, interval dan rasio serta ukuran sampel tidak harus besar. PLS mengestimasi model hubungan antar variabel laten dan variabel laten dengan indikatornya. Berdasarkan hasil analisis diperoleh kesimpulan bahwa kinerja perusahaan dipengaruhi oleh kinerja manajerial, keunggulan bersaing, Total Quality Management, kompensasi, sistem pengukuran kinerja dan budaya kualitas namun angkanya relatif kecil. Kata kunci : Partial Least Square, kinerja perusahaan

PENGUKURAN KINERJA PORTOFOLIO OPTIMAL SAHAM LQ45 MENGGUNAKAN METODE CAPITAL ASSET PRICING MODEL (CAPM) DAN LIQUIDITY ADJUSTED CAPITAL ASSET PRICING MODEL (LCAPM) Kristika Safitri; Tarno Tarno; 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.v10i2.29414

Investment is planting some funds to get profit and the stock is one of the type of investment in fincancial that the most interested for investors. To avoid the risk of investing, investors try to diversify their invesments by using portfolio. Stock portfolio is investment which comprised of various stocks from different companies, with the expect when the price of one stock decreases, while the other increases, then the investments do not suffer losses. Models that can be used to make a portfolio, one of them is Capital Asset Pricing Model (CAPM) and Liquidity Adjusted Capital Asset Pricing Model (LCAPM). CAPM is a model that connects expected return with the risk of an asset under market equilibrium condition. LCAPM is a method of new development of the CAPM model which is influenced by liquidity risk. To analyze whether the formed portfolio have a good performance or not, so portfolio perfomance assessment will be done by using The Sharpe Index. This research uses data from closing prices, transaction volume and volume total of LQ45 Index stock on period March 2016-February 2020 and then data of JCI and interest rate of central bank of the Republic of Indonesia. Based on The Sharpe Index, optimal portfolio is LCAPM model portfolio with 3 stock composition and the proportion investment are 32,39% for LPPF, 49,86% for SRIL and 17,75% for TLKM. Keywords: LQ45 Index, Portfolio, Capital Asset Pricing Model (CAPM), Liquidity Adjusted Capital Asset Pricing Model (LCAPM), The Sharpe Index.

PEMODELAN FUNGSI TRANSFER DENGAN DETEKSI OUTLIER UNTUK MEMPREDIKSI NILAI INFLASI BERDASARKAN BI RATE (Studi Kasus BI Rate dan Inflasi Periode Januari 2006 sampai Juli 2016) Firda Dinny Islami; Abdul Hoyyi; Dwi Ispriyanti
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation control is one of the important things in managing a country besides economic growth. Inflation received special attention in the economy of Indonesia. Every time there is a distortion in the society, politic or economic development, people always relate it to inflation. Low and stable inflation is a stimulator of economic growth. Inflation is also the final target in the monetary policy framework so the need for a central bank role to determine the policy direction. The BI Rate is one of the variables capable of controlling inflation. This study aims to forecast inflation based on the BI Rate using the transfer function model with outlier detection. The transfer function model depends on the parameters b, r, and s. The result of the analysis has been obtained the transfer function model with the value of b = 1, r = 0, s = 1 and the noise series ARMA (2,0). The addition of 16 outliers on the model yielded the best model with the AIC value is -868,56. The forecasting results show that the value of inflation has fluctuated, where in September 2016 it has decreased and then increased until December 2016.Keywords : Inflation, BI Rate, transfer function, outlier detection, AIC

PEMODELAN INDEKS HARGA KONSUMEN DI JAWA TENGAH DENGAN METODE GENERALIZED SPACE TIME AUTOREGRESSIVE SEEMINGLY UNRELATED REGRESSION (GSTAR-SUR) Mega Fitria Andriyani; Abdul Hoyyi; Hasbi Yasin
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.v7i4.28859

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 GSTAR-SUR(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

PERAMALAN PASANG SURUT AIR LAUT DI PULAU JAWA MENGGUNAKAN MODEL GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) (Studi Kasus : Ketinggian Pasang Surut Air Laut di Stasiun Pasang Surut Jakarta, Cirebon, Semarang dan Surabaya) Chyntia Arum Widyastusti; Abdul Hoyyi; Rita Rahmawati
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In daily life is often found time series data contains not only connection among the events in previous times, but also has a relationship between one location to another. Data with time series and location linkage is called space-time data. Generalized Space Time Autoregressive (GSTAR) model is one of the commonest used to make model and forecast space-time data. The purposes of this research are to get the best GSTAR model and the forecasting results for the data ocean tide heights at four stations of Java island, those are Stations of Jakarta, Cirebon, Semarang and Surabaya. The best model obtained is GSTAR(1;1)-I(1) which is using cross correlation normalization weight because its residuals fulfill white noise assumption with the smallest value of MAPE and RMSE. The best GSTAR model explains that the elevation ocean tide data in Stations of Cirebon and Semarang is only influenced by the earlier times, and not influenced by other locations but can affect the height of the tide at other locations. As for the elevation ocean tide data stations of Jakarta and Surabaya are influence each other. Keywords: GSTAR, Space-Time, Ocean Tide, MAPE and RMSE.

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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