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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 Al Hurriyah : Jurnal Hukum Islam 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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MODEL HUBUNGAN VOLUME LALULINTAS HARIAN DENGAN KECELAKAAN LALULINTAS DI JALAN TOL ANTAR-KOTA Bambang Haryadi; Bambang Riyanto; Mustafid Mustafid; Agung Budiwirawan
Jurnal Transportasi Vol. 10 No. 3 (2010)
Publisher : Forum Studi Transportasi antar Perguruan Tinggi (FSTPT)

Safety is one of the minimum criteria that should be met on the toll road operation. Ideally, the level of safety of highway sections can be predicted even if the highway is still on the design stage. This paper aims to develop mathematical models that could be used to predict the number of accidents, by its level of severity, on inter urban toll road sections based on its average daily traffic per lane and section length. Two yearperiod of traffic and accident data were obtained from Jagorawi, Jakarta-Cikampek, Padaleunyi, and Palikanci toll road operators. Models were developed using the negative binomial regression method. The reluts show that the negative binomial regression gives desirable properties in describing the relationshipbetween the accident frequency and the average daily traffic per lane on each toll road section observed.Keywords: toll road safety, accident model, negative binomial regression.

ANALISIS SIX SIGMA DENGAN DECISION ON BELIEF CHART PADA PRODUK HOT STRIP MILL Alifia Hanifah Mumtaz; Mustafid Mustafid; Sudarno Sudarno
Jurnal Gaussian Vol 10, No 1 (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.v10i1.29951

The Decision On Belief (DOB) control chart is a univariate control chart that was initially introduced as a solution to the problem of less than optimal control limits from the shewhart attribute diagram, especially the control chart C. The new scheme based on the DOB control chart is that the calculation step , can change the data which initially is not normally distributed into a normal distribution, then can diagnose quality control process errors. . defines belief or an assumption in the new observation vector and . The aim of this research is to apply the DOB control chart to data that is not normally distributed, so that it becomes a normal distribution. The result of the DOB control chart shows that the value of . is between the BKA and BKB values, which indicates a statistically controlled process. In this study, using one specification limit, namely the upper specification limit (USL) given by the company, which is 15 percent of the average production. The capability index used is for 3 sigma using the transformation result . Based on the sample data, the result shows that the value is 0.40633 and the sigma level is 2.719, so it can be concluded that the Hot Strip Mill production process is still not capable and has not reached the level of three sigma.Keywords: Six Sigma, Decision On Belief, capability index, , DPMO, level sigma.

IMPLEMENTASI METODE SIX SIGMA MENGGUNAKAN GRAFIK PENGENDALI EWMA SEBAGAI UPAYA MEMINIMALISASI CACAT PRODUK KAIN GREI Ayudya Tri Wahyuningtyas; Mustafid Mustafid; Alan Prahutama
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The quality being a very important aspect for consumer to choose products beside price that competes. In production process grey fabric there are several kinds of defects, the defects can cause to decrease of grade fabric produced. Six sigma method is a method that can be used to analyze defect rate to approach zero defect products. A procedure used for quality improvement toward the target that the concept of six sigma DMAIC. This study aims to implement six sigma method and EWMA control chart in quality control of product quality cloth of grey. The results obtained in this study is one the whole production process produces DPMO value of 24790.97 with sigma quality level of 3.464 means that the product of one million cloth of grey there are 24790.97 meters of product that does not fit in production. In the calculation process capability, process capability ratio value obtained more than 1 means that the process is going well and meets the specifications that have been established, but it is still possible to be improved so that the products resulting better. Keywords: Quality, Quality Control, Six Sigma, EWMA

PENERAPAN GRAFIK KENDALI JUMLAH KUMULATIF UNTUK MENDETEKSI PERGERAKAN KURS MATA UANG (Studi Kasus: Kurs Jual dan Kurs Beli Dollar Amerika) Silvia Julietty Sinaga; Mustafid Mustafid; Sugito Sugito
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30382

The Average Control Chart ( can be used to see if there has been an average change in a process. But this graph has a weakness that is not sensitive to small average shifts. The Cumulative Sum Control Chart (CUSUM) is considered to be more effective in detecting small average process shifts, because it combines information taken from multiple samples by describing the cumulative number of sample deviations from the target value. Both of these graphs are used to detect currency exchange rate shifts with the conclusion that the exchange rate of US Dollar (USD) to Rupiah (IDR) are out of control. The Average Run Length (ARL) value of the CUSUM Chart tends to be smaller than ARL of the chart. The ARL of CUSUM Control Chart for the selling rate and buying rate is 14,4269 and 19,3798. The ARL of chart with the 3 sigma limit is 370,37. CUSUM control chart also gives the result that the average of selling rate has increased from 13,022 to 13,200 and the average of buying rate has decreased from 13,022 to 12,6027. This means that the Dollar selling price in the bank will increase/expensive while the Dollar purchase price will decrease/cheaper. Keywords: Exchange Rate, Average Control Chart, Cumulative Sum Control Chart (CUSUM), Average Run Length (ARL), US Dollar (USD), Rupiah (IDR)

PENERAPAN IMPROVED GENERALIZED VARIANCE PADA PENGENDALIAN KUALITAS PAVING BLOCK SEGIENAM Nathasa Erdya Kristy; Mustafid Mustafid; Sudarno Sudarno
Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In quality assurance of hexagonal paving block products, quality control is needed so the products that produced are in accordance with the specified standards. Quality control carried out involves two interconnected quality characteristics, that is thickness and weight of hexagonal paving blocks, so multivariate control chart is used. Improved Generalized Variance control chart is a tool used to control process variability in multivariate manner. Variability needs to be controlled because of in a production process, sometimes there are variabilities that caused by engine problems, operator errors, and deffect in raw materials that affect the process. The purpose of this study is to apply Improved Generalized Variance control chart in controlling the quality of hexagonal paving block products and calculating the capability of production process to meet the standards. Based on the assumption of multivariate normal distribution test, it can be seen that the data of quality characteristics of hexagonal paving blocks have multivariate distribution. While based on the correlation test between variables it can be concluded that the characteristics of the quality of thickness and weight correlate with each other. The result of the control using these control chart shows that the process is statistically in control. The results of process capability analysis show that the production process has been running according to the standard because the process capability index value is generated using a weighting of 0.5 for each quality characteristic that is 1.01517. Keywords: Paving Block, Quality Control, Variability, Improved Generalized Variance, Process Capability Analysis

GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION UNTUK MENANGANI OVERDISPERSI PADA JUMLAH PENDUDUK MISKIN Nova Delvia; Mustafid Mustafid; Hasbi Yasin
Jurnal Gaussian Vol 10, No 4 (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.v10i4.33106

Poverty is a condition that is often associated with needs, difficulties an deficiencies in various life circumstances. The number of poor people in Indonesia increase in 2020. This research focus on modelling the number of poor people in Indonesia using Geographically Weighted Negative Binomial Regression (GWNBR) method. The number of poor people is count data, so analysis used to model the count data is poisson regression. If there is overdispersion, it can be overcome using negative binomial regression. Meanwhile to see the spatial effect, we can use the Geographically Weighted Negative Binomial Regression method. GWNBR uses a adaptive bisquare kernel for weighting function. GWNBR is better at modelling the number of poor people because it has the smallest AIC value than poisson regression and negative binomial regression. While the GWNBR method obtained 13 groups of province based on significant variables.

PENERAPAN DIAGRAM KONTROL MEWMA DAN MEWMV PADA PENGENDALIAN KARAKTERISTIK KUALITAS AIR (Studi Kasus: Kualitas Pengolahan Air II PDAM Tirta Moedal Kota Semarang) Adestya Ayu Maharani; Mustafid Mustafid; Sudarno Sudarno
Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Water is one of the most important elements for human life, water treatment is done for human consumption and must fulfill the health requirements with the levels of certain parameters. Quality of Water Treatment II is the second water purification installation owned by PDAM Tirta Moedal Semarang City with production capacity of 60 l/s. Variables used in the water treatment process are correlated with each other, so used multivariate control chart. The Multivariate Exponentially Weighted Moving Average control chart is used for monitoring process mean, and the Multivariate Exponentially Weighted Moving Variance control chart is used for monitoring process variability. The variables used are colour, turbidity, organic substance, manganese and the total dissolved solid. MEWMA control chart with λ = 0.5, showed that the process mean is controlled statistically. MEWMV control chart showed that variability is controlled statistically in λ = 0.4, ω = 0.2 and L = 3.3213. MEWMA and MEWMV control chart showed that the process is not capable because it obtained the value of process capability index less than 1. Keywords: Water, Multivariate Exponentially Weighted Moving Average, Multivariate Exponentially Weighted Moving Variance, process capability.

PENGENDAIAN MULTIVARIATE DENGAN DIGRAM KONTROL MEWMA ENGGUNAKAN METODE SIX SIGMA (STUDI KASUS PT FUMIRA SEMARANG TAHUN 2019) Puspita Ayu Utami; Mustafid Mustafid; Tatik Widiharih
Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

As one of the biggest corrugation producing industries, PT Fumira Semarang is always required to fulfill customer needs by continuously improving their quality. Galvanized Steel is the raw material for the production of corrugation at PT Fumira Semarang. There are three important quality characteristics to be controlled in order that the results of galvanized steel production fit the standards to be manufactured as corrugation are waves, rust, and scratches. Six Sigma is a method for controlling quality. Six Sigma has focus on reducing defects, by standard 3,4 defects per one million opportunties. This research aims to identify the galvanized steel production process using Six Sigma method with MEWMA control chart and the capability of the process to fit the standards. Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is a tool used to control multivariate process averages. The result of this research are MEWMA control chart with lambda 0.7 shows that the process is controlled statistically and The Sigma value for waves is 2,33, for rust 2,05, and for scratches 2,64. And the research reveals the galvanized steel production process has not fit to the standard because the process capabilty index is 0,2805. Keywords: Galvanized Steel, Quality Control, Six Sigma, Multivariate Exponentially Weighted Moving Average, Process Capability Analysis

DIAGRAM KONTROL MULTIVARIAT np DAN DIAGRAM KONTROL JARAK CHI-SQUARE DALAM PENGENDALIAN KUALITAS PRODUK KAIN DENIM (Studi Kasus di PT Apac Inti Corpora) Dwi Harti Pujiana; Mustafid Mustafid; Di Asih I Maruddani
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.v7i4.28866

Denim fabric sort number 78032 is one type of fabric in the last 4 years almost every month produced by PT Apac Inti Corpora. In the continuity of denim fabric production process, there are data defects (non-conformity) that causes the quality of denim fabric decreases. To maintain the consistency of the quality of products produced in accordance with the specified specifications, it is necessary to control the quality of the production process that has been running for this. Multivariate control charts attributes used are multivariate control charts np using the number of samples and the proportion of disability data with correlation between variables while the chi-square distance control charts use squared distances with uncorrelated data between variables. The results showed that in the multivariate control chart np there were 2 out-of-control observations in the phase II data using control limits from phase I data already controlled by the value of BKA of 636321.4. While in the chi-square distance control chart showed all observations are in in-control condition with BKA value of 0.06536. Controlled production process obtained multivariate process capability value for multivariate control np diagram of 0.625142 <1 which means the process is not capable, while the value of process capability in the chi-square distance control chart is 1.1329> 1 which means the process is capable. Keywords: denim fabric, multivariate np control chart, chi-square distance control chart, multivariate process capability

PENERAPAN FUZZY C-MEANS KLUSTER UNTUK SEGMENTASI PELANGGAN E-COMMERCE DENGAN METODE RECENCY FREQUENCY MONETARY (RFM) Stevanus Sandy Prasetyo; Mustafid Mustafid; Arief Rachman Hakim
Jurnal Gaussian Vol 9, No 4 (2020): 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.v9i4.29445

E-commerce has become a medium for online shopping which is growing and popular among the public. Due to the ease of access for all internet users and the completeness of the products offered, e-commerce has become a new alternative in meeting people's needs. Currently, the competition in the business world is very fierce, any e-commerce company needs to be able to carry out the right marketing strategy to compete in acquiring, retaining, and partnering with customers. In this research, the segmentation of e-commerce customers was carried out using the Fuzzy C-Means cluster and the RFM method. The clustering process is carried out six times with the number of clusters starts from two to seven clusters. The results showed that the optimum number of clusters formed according to the Xie-Beni validity index was four clusters. The cluster becomes customer segments that have the characteristics of each customer based on their recency, frequency, and monetary value. The best segment is segment 4 which has very loyal customers in shopping on tumbas.in e-commerce. From the segments that have been formed, they can be used as a consideration in implementing the right marketing strategy for each customer. Keywords : E-commerce, customer segmentation, Fuzzy C-Means Cluster, RFM, Xie-Beni Index

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 Algifari, Muhammad Faiz 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 Arisman Arisman 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 Khairunnas Rajab 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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