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All Journal Media Statistika SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Jurnal Gaussian Jurnal Transportasi Al-Ahwal: Jurnal Hukum Keluarga Islam JOIV : International Journal on Informatics Visualization Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika Jurnal el-Qanuniy: Jurnal Ilmu-Ilmu Kesyariahan dan Pranata Sosial Al-Qadha: Jurnal Hukum Islam dan Perundang-Undangan Al-Manhaj: Jurnal Hukum dan Pranata Sosial Islam Infotek : Jurnal Informatika dan Teknologi Journal of Islamic Law STRATEGY : Jurnal Inovasi Strategi dan Model Pembelajaran El-Izdiwaj: Indonesian Journal of Civil and Islamic Family Law Syarah: Jurnal Hukum Islam dan Ekonomi Yurisprudentia: Jurnal Hukum Ekonomi Jurnal Sultan : Riset Hukum Tata Negara Jurnal Fakta Hukum (JFH) Al-Zayn: Jurnal Ilmu Sosial & Hukum El-Sirry: Jurnal Hukum Islam dan Sosial Indonesian Journal of Humanities and Social Sciences Al-battar: Jurnal Pamungkas Hukum

Mustafid Mustafid

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 326275

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Public Health Social Sciences Transportation Other

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SEGMENTASI PELANGGAN E-MONEY DENGAN MENGGUNAKAN ALGORITMA DBSCAN (DENSITY BASED SPATIAL CLUSTERING APPLICATIONS WITH NOISE) DI PROVINSI DKI JAKARTA Windy Rohalidyawati; Rita Rahmawati; Mustafid Mustafid
Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Customer segmentation is one effective way of marketing to determine the most potential target market. Increasing of E-money usage in DKI Jakarta and more banks are providing E-money products. One way to be able to compete in the global market, banks can segment customers. Determining potential customers of E-money users in DKI Jakarta can form segments by applying the DBSCAN (Density Based Spatial Clustering Application with Noise) algorithm. The quality of segments was measured by using the Silhouette Coefficient. In this study, E-money customers were grouped by reason of using the bank used, transaction activities, number of transactions, nominal balance, and frequency of top-up. The results of this study were using the density radius of 2 and minimum 3 objects that enter the density radius forming 2 segments and 17 noises. The segment quality value of 0.26. The most potential segment was the segment that has an average greater than the average of all data.

PENERAPAN DIAGRAM KONTROL MULTIVARIATE EXPONENTIALLY WEIGHTED MOVING AVERAGE (MEWMA) PADA PENGENDALIAN KARAKTERISTIK KUALITAS AIR (Studi Kasus: Instalasi Pengolahan Air III PDAM Tirta Moedal Kota Semarang) Anastasia Arinda; Mustafid Mustafid; Moch. Abdul Mukid
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Water treatment is intended to change the original water quality that does not fulfill the health requirements become a water for human consumption and must comply with the levels of certain parameters. Quality control can be done by forming a Multivariate Exponentially Weighted Moving Average (MEWMA) control chart. In the Multivariate Exponentially Weighted Moving Average (MEWMA) control charts with λ = 0.25 and UCL = 13.92658 seen that process controlled statistically. Once the process is under control, it can be done analysis of the ability of the process to determine whether the process fulfill the specifications or not. In the calculation process capability univariate each characteristics and multivariate process capability index values obtained more than 1 means that the process is going well. Keywords: water quality, Multivariate Exponentially Weighted Moving Average (MEWMA), process capability.

IMPLEMENTASI ALGORITMA MODIFIED GUSTAFSON-KESSEL UNTUK CLUSTERING TWEETS PADA AKUN TWITTER LAZADA INDONESIA Ratna Kencana Putri; Budi Warsito; Mustafid Mustafid
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Online social media is a new kind of media which is steadily growing and has become publicly popular. Due to its ability to spread informations rapidly and its easiness to access for internet users, social media provides new alternative to conduct advertising and product segmentation. Twitter is one of the most favored social media with 19.5 million users in Indonesia to the date. In this research, the application of text mining to cluster tweets from the @LazadaID Twitter account is done using the Modified Gustafson-Kessel clustering algorithm. The clustering process is executed five times with the number of cluster starts from two to six cluster. The results of this research indicate that the optimum number of clusters formed based on the Partition Coefficient and Classification Entropy validation index are three clusters. Those three clusters are tweets containing electronic stuff offers, discounts, and prize quizes. Tweets with the most retweets and likes are prize quiz tweets. PT Lazada Indonesia could use this kind of tweet to conduct advertising on social media Twitter because the prize quiz tweets are liked by the @LazadaID Twitter account followers.Keywords: Twitter, advertising, Lazada Indonesia, Gustafson-Kessel Clustering algorithm, validation index

PENERAPAN SIX SIGMA DALAM RANCANGAN PERCOBAAN FAKTORIAL UNTUK MENENTUKAN SETTING MESIN PRODUKSI AIR MINERAL Muhammad Nugroho Karim Amrulllah; Mustafid Mustafid; Sugito Sugito
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Machine setting is one of the factors which affects the high defects of mineral water cup. The determination of the optimal machine setting is needed to reduce the defects that occur. Six Sigma DMAIC (define, measure, analyze, improve, control) method in the factorial experimental design can be used for determining the optimal machine setting. This research, which is conducted in PT Sekar Sari, found the most optimal combination of pressure and temperature setting of the machine, so that the defects generated are decreasing after optimal condition treatment. Sigma level increased by 0.89 sigma, from 2,47 sigma to 3,36 sigma and COPQ (cost of poor quality) percentage decreased by 3.64%.Keywords: Six Sigma, DMAIC, Factorial Design of Experiment, COPQ.

PENERAPAN METODEEXPECTED SHORTFALLPADA PENGUKURAN RISIKO INVESTASI SAHAM DENGAN VOLATILITAS MODEL GARCH Nurul Fitria Fitria Rizani; Mustafid Mustafid; Suparti Suparti
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of the methods that can be used to measure stock investment risk is Expected Shortfall (ES). ES is an expectation of risk size which value is greater than Value at Risk (VaR), ES has characteristics of sub-additive and convex. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to model stock data that has high volatility. Calculating ES is done with data that shows deviations from normality using Cornish-Fisher's expansion. This researchapplies the ES at the closing stock price of PT Astra International Tbk. (ASII), PT Bank Negara Indonesia (Persero) Tbk. (BBNI), and PT Indocement Tunggal Prakarsa Tbk. (INTP) for the period of 11 February 2013 - 31 March 2019. Based on the volatility of GARCH (1,1) analysis, we find ES calculation for each stock by 95% level confidence. The ES for ASII shares is 4.1%, greater than the VaR value which isonly 2.64%.The ES for BBNI shares is 4.38%, greater than it’s VaR value which is only 2,86%. The ES for INTP shares is 6.22%, which is also greater than it’s VaR value which is only3,99%. The greather of VaR then Thegreather of ES obtained.Keywords: Expected Shortfall, Value at Risk, GARCH

PENGUKURAN PROBABILITAS KEBANGKRUTAN OBLIGASI KORPORASI DENGAN SUKU BUNGA COX INGERSOLL ROSS MODEL MERTON (Studi Kasus Obligasi PT Indosat, Tbk) Muhammad Akhir Siregar; Mustafid Mustafid; Rukun Santoso
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Nowadays bonds become one of the many securities products that are being prefered by investors. Observing the level of the company's rating which good enough or in the criteria of investment grade can’t be a handle of investors. Investing in long-term period investors should understand the risks to be faced, one of investment credit risk on bonds is default risk, this risk is related to the possibility that the issuer fails to fulfill its obligations to the investor in due date. The measurement of the probability of default failure by the structural method approach introduced first by Black-Scholes (1973) than developed by Merton (1974). In Bankruptcy model, merton’s model assumed the company get default (bankrupt) when the company can’t pay the coupon or face value in the due date. Interest rates on the Merton model assumed to be constant values replaced by Cox Ingersoll Ross (CIR) rates. The CIR rate is the fluctuating interest rate in each period and the change is a stochastic process. The empirical study was conducted on PT Indosat, Tbk's bonds issued in 2017 with a face value of 511 Billion in payment of obligations by the issuer for 10 years. Based on simulation results done with R software obtained probability of default value equal to 7,416132E-215 Indicates that PT Indosat Tbk is deemed to be able to fulfill its obligation payment at the end of the bond maturity in 2027. Keywords: Bond, CIR Rate, Merton Model, Ekuity, Probability of default

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

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

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

PEMODELAN AUTOREGRESSIVE FRACTIONALLY INTEGRATED MOVING AVERAGE DENGAN EFEK EXPONENTIAL GARCH (ARFIMA-EGARCH) UNTUK PREDIKSI HARGA BERAS DI KOTA SEMARANG Rezky Dwi Hanifa; Mustafid Mustafid; Arief Rachman Hakim
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.v10i2.29933

Time series data is a type of data that is often used to estimate future values. Long memory phenomenon often occurs in time series data. Long memory is a condition that shows a strong correlation between observations even though they are quite far away. This phenomenon can be overcome by modeling time series data using the Autoregressive Fractional Integrated Moving Average (ARFIMA) model. This model is characterized by a fractional difference value. ARFIMA (Autoregressive Fractional Integrated Moving Average) model assumes that the residuals are normally distributed, mutually independent, and homogeneous. However, usually in financial data, the residual variants are not constant. This can be overcome by modeling variants. Standard equipment that can be used to model variants is the ARCH / GARCH (Auto Regressive Conditional Heteroscedasticity / Generalized Auto Regressive Conditional Heteroscedasticity) model. Another phenomenon that often occurs in GARCH models is the leverage effect on the residuals of the model. EGARCH (Exponential General Auto Regessive Conditional Heteroscedasticity) is a development of the GARCH model that is appropriate for data that has an leverage effect. The implementation of this model is by modeling financial data, so this study takes 136 monthly data on rice prices in Semarang City from January 2009 to April 2020. The purpose of this study is to create a long memory data forecasting model using the Exponential method. Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). The best model obtained is ARFIMA (1, d, 1) EGARCH (1,1) which is capable of forecasting with a MAPE value of 3.37%.Keyword : Rice price, forecasting , long memory, leverage effect, GARCH, EGARCH

Sistem Manajemen Potensi Anak Sejak Dini (SIMPONI) Berdasarkan Teori Kecerdasan Majemuk Menggunakan Metode Simple Additive Weighting (SAW) Mustafa Mustafa; Mustafid Mustafid; R Rizal Isnanto
Infotek: Jurnal Informatika dan Teknologi Vol 3, No 2 (2020): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Program pembelajaran untuk anak usia Sekolah Dasar (SD) akan lebih mudah disampaikan apabila menggunakan strategi pembelajaran yang sesuai dengan gaya belajar atau profil kecerdasan majemuk anak. Identifikasi profil kecerdasan majemuk anak dapat dilakukan melalui proses observasi orang tua dan guru sekolah terhadap kegiatan sehari-hari anak. Profil kecerdasan majemuk anak bersifat dinamis sehingga perlu dilakukan identifikasi profil kecerdasan majemuk secara berkala minimal satu tahun sekali. Penelitian ini bertujuan untuk mengimplementasikan metode Simple Additive Weight (SAW) pada Sistem Manajemen Potensi Anak Sejak Dini (SIMPONI) berdasarkan Teori Kecerdasan Majemuk. Metode Simple Additive Weighting (SAW) digunakan untuk perhitungan penentuan rangking profil Kecerdasan Majemuk anak. Hasil penelitian ini adalah sistem informasi manajemen identifikasi Profil Kecerdasan Majemuk dengan pengolahan data menggunakan metode Simple Additive Weighting (SAW). Keunggulan produk yang dihasilkan penelitian ini adalah orang tua dapat melakukan identifikasi profil kecerdasan majemuk anak secara lebih mudah dibandingkan model sebelumnya yang menggunakan metode wawancara yang mengharuskan tatap muka.DOI : 10.29408/jit.v3i2.2250

Co-Authors Abdul Hoyyi Abdul Munir, Akmal Adestya Ayu Maharani Adi Wahyu Romariardi Adian Fatchur Rochim Agatha, Insani Tiara Agil Setyo Anggoro Agung Budiwirawan Agung Budiwirawan Agus Rusgiyono Agus Setyawan Agus Subagio Ahmad Lubis Ghozali Akbarizan Akbarizan Al Bajuri, Azzuhri Alan Prahutama Alfahari Anggoro, Alfahari Alfrianus Papuas Alifia Hana Linda Rachmawati Alifia Hanifah Mumtaz Amrina Rosyada Anak Agung Gede Sugianthara Anastasia Arinda Andi Gunawan Anisa, Darania Anwar, Alfiansyah Arief Rachman Hakim Aris Sugiharto Aulia Desy Deria Ayudya Tri Wahyuningtyas Bambang Haryadi Bambang Riyanto Bambang Riyanto Basuki Rahmat Masdi Siduppa Bayu Surarso Beta Noranita Budi Warsito Catur Edi Widodo Cynthia Damayanti Daniel Alfa Puryono Di Asih I Maruddani Diah Safitri Diandra Zakeshia Tiara Kannitha Djalal Er Riyanto Dwi Harti Pujiana Dwi Ispriyanti Dwi Putri Handayani Dwinta Rahmallah Pulukadang, Dwinta Rahmallah Dyna Marisa Khairina Edi Widodo, Edi Eko Adi Sarwoko Faiz Algifari, Muhammad Ferry Jie, Ferry Hasbi Yasin Hosen, Hosen Hsb, Putra Halomoan I Gusti Ngurah Antaryama Ibnu Widiyanto Ibrahim, Muhammad Rivani Imam Nur Sholihin Irfan Ismail Sungkar ISNUGROHO, AWING Jatmiko Endro Suseno Jayawarsa, A.A. Ketut Juwanda, Farikhin Kemas Muhammad Gemilang Kholidah Kholidah, Kholidah Leni Pamularsih Lulus Darwati, Lulus Mardona Siregar Meilia Kusumawardani, Meilia Moch. Abdul Mukid Muhammad Akhir Siregar Muhammad Nugroho Karim Amrulllah Muhammad Nur Mustafa, Mustafa Nathasa Erdya Kristy Nesari Nesari Nida Adelia Nova Delvia Nurul Fitria Fitria Rizani Oky Dwi Nurhayati Pipin Widyaningsih Prihati Prihati Puananndini, Dewi Asri Puspita Ayu Utami Puspita Kartikasari Putra, Firman Surya Putranto, Aldi Satya Qurtubi, Achmad Napis R Rizal Isnanto Radian Lukman Rangkuti, Nuraini Ratna Kencana Putri Redemtus Heru Tjahjana Rezky Dwi Hanifa Ririn Sulpiani Rita Rahmawati Rita Rahmawati Rizaldy Khair Rizky Parlika, Rizky Rosmiati Rosmiati Rukun Santoso Satriyo Adhy Silvia Julietty Sinaga Sinta Tridian Galih Siregar, Mardona Sobhan, Sobhan Sri Mulyani Stevanus Sandy Prasetyo Sudarno Sudarno Sudarno Sudarno Sugito Sugito Sulastri Sulastri Sumper Mulia Harahap, Sumper Mulia Suparti Suparti Supriyono Supriyono Suryono Suryono Syamsul Arifin Tarno Tarno Tatik Widiharih Thalita, Indah Tri Ernayanti Triastuti Wuryandari U.S, Supardi Udi Harmoko Windy Rohalidyawati Wulandari, Heni Dwi Yennylawati, Eng Yudie Irawan Yundari, Yundari Zega, Nesty Novita Sari

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