Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

p-Index From 2021 - 2026

P-Index

This Author published in this journals

All Journal PROSIDING SEMINAR NASIONAL Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Moch. Abdul Mukid

Unknown Affiliation

Author-ID : 475550

Decision Sciences, Operations Research & Management Education Other

Published : 45 Documents Claim Missing Document

Claim Missing Document

Articles

Title

1 2 3 4 5

IDENTIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI TERJADINYA PREEKLAMPSIA DENGAN METODE CHAID (Studi Kasus pada Ibu Hamil Kategori Jampersal di RSUD Dr.Moewardi Surakarta) Restu Sri Rahayu; Moch. Abdul Mukid; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Pre-eclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy . This sickness is caused by many factors. To identify the factors, We lowercase a statistical analysis that can explain the characteristics of pregnant women who has pre-eclampsia. One analysis used for segmentation is CHAID (Chi-Squared Automatic Interaction Detection). This analysis classify and view the segmentation on nominal scale dependent variable (patient’s status). CHAID analysis result indicates that the history of hypertension is the most influential independent variable. The tree diagram shows that there are seven segments of pregnant women, this study reveals that, there are three segments that need to be concerned because these segments show a high number and high index value exceeds 100% of pregnant women with pre-eclampsia. These segments need an effort to support the reduction of MMR. The three segment are segment pregnant women who has the history of hypertension; segment pregnant women of primary school degree and who are jobless, overweight, with no history of hypertension; and segment pregnant women with elementary and junior high school degree, who has jobs, and no hypertension history. Accuration of the CHAID algorithm in classifying is 78,2%. Keywords: Pre-eclampsia, Classify, CHAID, Maternal Mortality Ratio, Accuration

ANALISIS KECENDERUNGAN INFORMASI DENGAN MENGGUNAKAN METODE TEXT MINING (Studi Kasus: Akun twitter @detikcom) Syaifudin Karyadi; Hasbi Yasin; Moch. Abdul Mukid
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The internet is an extraordinary phenomenon. Starting from a military experiment in the United States, the internet has evolved into a 'need' for more than tens of millions of people worldwide. The number of internet users is large and growing, has been creating internet culture. One of the fast growing social media twitter. Twitter is a microblogging service that stores text database called tweets. To make it easier to obtain information that is dominant discussed, then sought the topic of twitter tweet using clustering. In this research, grouping 500 tweets from twitter account @detikcom using k-means clustering. The results of this study indicate that the maximum index Dunn, the best grouping K-means clustering to obtain the dominant topic as many as three clusters, namely the government, Jakarta, and politics.Keywords: text mining, clustering,, k-means , dunn index, and twitter.

OPTIMALISASI PORTOFOLIO MENGGUNAKAN CAPITAL ASSET PRICING MODEL (CAPM) DAN MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP) (Studi Kasus: Saham-Saham LQ45) Mardison Purba; Sudarno Sudarno; Moch. Abdul Mukid
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investment is planting some funds to get profit. However, there is a positive relationship between risk and return that is High Risk High Return. So, the investor seeks to maximize expected return using portfolio optimization. The nature of the stock fluctuates over time, often times it poses a risk to lose money. In the science of finance, the fluctuations of stock returns is known as volatility. Then the stock volatility measurement uses Exponentially Weighted Moving Average (EWMA). Methods of Capital Assets Pricing Model (CAPM) is used for the selection of the best stocks of the nine sectors LQ45. Portfolios are formed of nine sectors were weighted using the Mean-Variance optimal Efficient Portfolio (MVEP). The weight placed on the largest fund shares at IMAS 25.12%, amounting to 19.53% BDMN, BWPT by 6.40%, 9.75% for INCO, SMCB by 7.72%, amounting to 9.37% INDF, BKSL for 2.27%, 16.87% and TLKM of MAPI by 2.98%. Based on analysis, volatility measurement of IMAS, TLKM and BDMN especially using EWMA. Risk measurement tool used for stock portfolio is Value at Risk (VaR) and Risk measurement tool used for stocks is Component Value at Risk (CVaR). With a confidence level of 95% and an investment of IDR 100.000.000 the loss investment using VaR for one day in the future is IDR 1.799.824. Meanwhile, if using CVaR then the maximum loss investment for the day ahead is IDR 1.523.000,73.

ANALISIS PREFERENSI KONSUMEN TERHADAP PRODUK SUSU BERBASIS ANALISIS CONJOINT MENGGUNAKAN METODE PRESENTASI PAIRWISE-COMPARISON (Studi kasus di Beberapa SMP di Kecamatan Banyumanik Kota Semarang) Trianita Resmawati; Moch. Abdul Mukid; Diah Safitri
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In this study aims to help producer or milk companies to know and understand consumer preferences for attributes combination of milk products specifically for adolescent. The method used in this study is the conjoint analysis using pairwise-comparison as a method of presentation. In this research, the attributes that used are the type of milk, flavor, packaging, and fat content. The result of this reserach shows that the packaging is the most important attribute between the other attributes with a relative importance value of 56.13%. The second most importance attribute is flavor of milk with a relative importance value of 38.55%. Fat content was ranked in the third place with a relative importance value of 4.28%, and the type of milk as the fourth attribute with a relative importance value of 1.05%. In addition, the stimuli is desired by consumers for milk products specifically for adolescent are condensed milk, chocolate, canned, and non fat.

PENGARUH MARKETING MIX TERHADAP KEPUASAN DAN LOYALITAS KONSUMEN MENGGUNAKAN METODE STRUCTURAL EQUATION MODELLING (SEM) Syarah Widyaningtyas; Triastuti Wuryandari; Moch. Abdul Mukid
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Marketing mix is a combination of variables that constitute the core of marketing system, consisting a set of variables that can be controlled and used by companies to influence consumer responses in target markets comprise. One that used in this study for analysis is Structural Equation Model (SEM). The study shows that satisfaction influenced by promotion, pricing, product and location of 38,9%, that loyalty is explained by satisfaction, promotion, pricing, product and location of 99,8%. In significant testing, it was found that pricing, product, location are significant to satisfaction. Satisfaction is significant to loyalty; while pricing, location, product are not significant to loyalty. Promotion is not significant to satisfaction and loyalty. Based on the results of data processing using software AMOS 22.0, the model SEM has been convenient and fit for use in research because the data has been proven to have normal distribution and have met the criteria for Goodness of Fit.Keywords: Marketing Mix, Consumer Satisfaction, Consumer Loyalty, Structural Equational Modelling.

RANCANGAN D-OPTIMAL UNTUK REGRESI POLINOMIAL DERAJAT 3 DENGAN HETEROSKEDASTISITAS Naomi Rahma Budhianti; Tatik Widiharih; Moch. Abdul Mukid
Jurnal Gaussian Vol 2, No 2 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Suatu model hubungan antara variabel prediktor X dan variabel respon Y, dalam hal ini adalah model regresi polinomial derajat 3 dengan heteroskedastisitas yang mempunyai fungsi bobot . Permasalahan yang muncul adalah bagaimana memilih titik-titik rancangan X yang akan dicobakan sehingga model menjadi signifikan. Rancangan D-Optimal adalah rancangan dengan kriteria keoptimalan meminimumkan variansi estimator parameter. Jika variansi estimator parameter minimum maka diharapkan parameter dalam model menjadi signifikan sehingga model juga signifikan. Kriteria rancangan D-Optimal didapatkan dengan memaksimumkan determinan matriks informasi atau meminimumkan determinan invers matriks informasi.

PEMODELAN DATA INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI PENALIZED SPLINE Novia Agustina; Suparti Suparti; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Indonesia Composite Index (IHSG) is an indicator of stock price changes in Indonesia Stock Exchange. IHSG is time series data that can be modeled with parametric models. But there are some assumptions for parametric model, while the fluctuated IHSG data usually doesn’t occupy these assumptions. Another alternative for this study is nonparametric regression. Penalized spline regression is one of nonparametric regression method that can be used. The optimal penalized spline models depends on the determination of the optimal smoothing parameter λ and the optimal number of knots, that has a minimum value of Generalized Cross Validation (GCV). The best model in this study is penalized spline degree 1 (linear) with 1 knot, that is 5120,625, smoothing parameter λ value is 41590, and GCV value is 1567,203. R2 value for in sample data is 83,2694% and R2 value for out sample data is 96,4976% show that the model have a very good performance. MAPE values for in sample data is 0,5983% and MAPE values for out sample data is 0,4974%. Because the value of MAPE in sample and out sample is less than 10%, it means that the performance of the model and forecasting are very accurate. Keywords: Indonesia Composite Index, Nonparametric Regression, Penalized Spline Regression, GCV, MAPE

PERBANDINGAN METODE K–MEANS DAN SELF ORGANIZING MAP (STUDI KASUS: PENGELOMPOKAN KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA 2015) Rachmah Dewi Kusumah; Budi Warsito; Moch. Abdul Mukid
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cluster analysis is a process of separating the objects into groups, so that the objects that belong to the same group are similar to each other and different from the other objects in another group. In this study used two method to classify data of district / city in Central Java based on indicators of Human Development Index (HDI) 2015 are K-Means and Self Organizing Map (SOM) with the number of groups as much as two to seven. Furthermore, the results of both methods were compared using the Davies-Bouldin Index (DBI) values to determine which method is better. Based on the research that has been conducted found that the K-Means (K=4) method works better than SOM (K=2) to classify district / city in Central Java based on indicators of Human Development Index (HDI) as evidenced by the value of the Davies-Bouldin Index (DBI) on K-Means (K=4) of 0.786 is smaller than the value at SOM (K=2) Davies-Bouldin Index (DBI) which is equal to 0.893. Keywords: clustering, HDI, K-Means, SOM, DBI

Pemodelan Regresi 2-Level Dengan Metode Iterative Generalized Least Square (IGLS) (Studi Kasus: Tingkat Pendidikan Anak di Kabupaten Semarang) Dyan Anggun Krismala; Dwi Ispriyanti; Moch. Abdul Mukid
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In a research, data was used often hierarchical structure. Hierarchical data is data obtained through multistage sampling from a population with independent variables can be defined within each level and dependent variable can be defined at the lowest level. One analysis that can be used for data with a hierarchical structure is a multilevel regression analysis. Multilevel regression analysis is the most simple regression analysis 2-levels. 2-level regression analysis will be used to construct a regression model the education level of children in Semarang where children (level-1) nested on the distrits (level-2) with the factors that influence. Estimation of parameter in 2-level regression model can use some methods, one of them is Iterative Generalized Least Square (IGLS). From the results of the discussion indicates that the factors which affect the level of education of children in Semarang is the mother’s education, father’ education, and percentage of farm families. The diversity level of the education of children in Semarang caused more variation among children than the variation between districts.

PEMODELAN INDEKS PEMBANGUNAN MANUSIA DI PROVINSI JAWA TENGAN TAHUN 2008-2013 DENGAN MENGGUNAKAN REGRESI DATA PANEL Muhammad Rizki; Agus Rusgiyono; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Human Development Index (HDI) is a way to measure the success of human development based on a number of basic components quality of life. HDI is formed by three basic variables namely health, education and decent living standards. This study aims to identify factors that influence the Human Development Index in Central Java Province and get a model Human Development Index in Central Java province in 2008-2013. The data used in this study is a combination of cross section data and time series data are commonly called panel data, then this HDI modeling using panel data regression. There are three estimation of panel data regression model namely Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). Estimation of panel data regression model used is the Fixed Effects Model (FEM). FEM estimation results show the number of health facilities, school participation rate and Labor Force Participation Rate significantly affect the HDI by generating for 93.58%.Keywords : Fixed Effect Model, panel data regression, HDI in Central Java Province

Co-Authors Abdul Hoyyi Agus Rusgiyono Alan Prahutama Alvita Rachma Devi Anifa Anifa Anissa Pangastuti Arief Rachman Hakim Bella Cynthia Devi Bramaditya Swarasmaradhana Budi Warsito Bunga Maharani Catra Aditya Wisnu Aji Chainur Arrasyid Hasibuan Cyntia Surya Utami Dedy Douglas Harianja Desy Trishardiyanti Adiningtyas Diah Safitri Dwi Ispriyanti Dyan Anggun Krismala Elyas Darmawan Endah Cahyaningrum Erna Fransisca Angela Sihotang Erna Puspitasari Etik Setyowati Fatma Septy Deviana Fitra Ramdhani Hasbi Yasin Herwindhito Dwi Putranto Iantazar Rezqitullah Maharsi Kiki Febri Azriati Laili Isna Nur Khiqmah Landong Panahatan Hutahaean Mardison Purba Marta Widyastuti Muhammad Rizki Naomi Rahma Budhianti Niken Anggraini Dewi Novia Agustina Nunung Hanurowati Nurhikmah Megawati Panji Wisnu Wirawan Rachmah Dewi Kusumah Restu Sri Rahayu Rita Rahmawati Riza Adi Priantoro Shaumal Luqman Solly Aryza Sudarno Sudarno Sugito Sugito Suparti Suparti Syaifudin Karyadi Syarah Widyaningtyas Tatik Widiharih Trianita Resmawati Triastuti Wuryandari Ungu Siwi Maharunti Yosi Dhyas Monica Yuciana Wilandari

Title Search

Found 41 Documents Search Journal : Jurnal Gaussian

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 41 Documents
Search
Journal : Jurnal Gaussian