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All Journal Media Statistika Jurnal Ilmu Dasar Statistika Jurnal Matematika & Sains Jurnal Fourier BAREKENG: Jurnal Ilmu Matematika dan Terapan IJID (International Journal on Informatics for Development) STATISTIKA
Epha Diana Supandi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Transportation

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Pendekatan Conjoint Analysis untuk Mengukur Tingkat Preferensi Mahasiswa terhadap Layanan Sistem Informasi Akademik di UIN Yogyakarta Supandi, Epha Diana
Jurnal Fourier Vol 1, No 1 (2012)
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (338.25 KB)

Abstract

Information Technology (IT) represent one of main indicator to support the academic atmosphere at the university. Therefore UIN Sunan Kalijaga (Suka) Yogyakarta has owned sistem information technology and it is called Academic Information System (SIA). UIN Suka shall has knowledge preference and perception of consumer to the service, which is like what required by consumer. By using Conjoint Analysis method would have been obtained combination from level-level factor (stimuly) took a fancy by consumer according to value of highest utility from every level factor.  The objective of this research is to measure preference level of consumers (students) to the SIA services in UIN Suka used Conjoint Analysis method. The result shows that the most important factor in using SIA service is the benefit (importance value is 66,623%, the second important factor is accesibility of SIA ( importance value is 19,227%) and the last important is ability of staff  (importance value is 14,15%). According to value of utility estimate, it shows that consumers like to use SIA for key in courses (utility estimate is 2,104), online service (utility estimate is 0,577) and SIA staff who are very friendly when they were servicing the students (utility estimate is 0,210).
Optimisasi Robust Melalui Second Order Cone Programming dengan Aplikasi pada Penentuan Portofolio Optimal Supandi, Epha Diana; Rosadi, Dedi; Abdurakhman, Abdurakhman
Jurnal Matematika dan Sains Vol 19 No 3 (2014)
Publisher : Institut Teknologi Bandung

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Abstract

Pada makalah ini, kami meneliti mengenai optimisasi robust (robust optimization), metode ini berguna untuk menangani  masalah optimisasi dimana data permasalahan tidak diketahui dengan pasti tetapi diasumsikan berada dalam suatu himpunan ketidakpastian (uncertainty set). Selanjutnya Second Order Cone Programming (SOCP) digunakan untuk menyelesaikan masalah  optimisasi robust.  SOCP adalah masalah pemrograman konveks dimana fungsi tujuannya berbentuk linear dengan kendala second order cone. Penerapan SOCP pada pembentukan masalah portofolio mean variance berhasil dilakukan. Berdasarkan studi kasus, portofolio robust melalui SOCP lebih unggul dibandingkan portofolio klasik ditinjau dari capital gain. Kata Kunci : Optimisasi robust, Second order cone programming, Portofolio mean-variance.   Robust Optimization Through Second Order Cone Programming with Applications on the Establishment of Optimal Portfolio   Abstract In this paper, we studied about robust optimization, this method is useful for dealing with optimization problems where data are not known certainly but assumed belong to uncertainty set. Furthermore, Second Order Cone Programming (SOCP) is used to solve the robust optimization problems.  SOCP is a convex programming problem where the objective function in the form of linear with constraints in the form of second order cone. Application of SOCP in the formation of mean variance portfolio problem successfully conducted. Based on case studies,  robust portfolios through SOCP are superior compared to classical portfolios in terms of capital gain. Keywords: Robust optimization, Second order cone programming, Mean variance portfolio.
Pembentukan Portofolio Optimal dengan Menggunakan Mean Absolute Deviation dan Conditional Mean Variance Vanti, Eka Nur; Supandi, Epha Diana
Jurnal Fourier Vol 9 No 1 (2020)
Publisher : Program Studi Matematika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/fourier.2020.91.25-34

Abstract

Penelitian ini membahas tentang pembentukan portofolio optimal menggunakan model Mean Absolute Deviation (MAD) dan model Conditional Mean Variance (CMV). Pada model MAD risiko portofolio diukur menggunakan rata–rata deviasi standar sehingga portofolio optimal dapat diperoleh dengan menggunakan pemrograman linear. Sedangkan portofolio model CMV, rata–rata return diestimasi menggunakan model Autoregressive (AR) dan risiko (variansi) diestimasi menggunakan model GARCH. Selanjutnya kedua model portofolio diterapkan dalam membentuk portofolio optimal pada saham–saham yang terdaftar dalam Indeks Saham Syariah Indonesia (ISSI) periode 4 Juli 2016 sampai 4 Juli 2018. Kinerja kedua portofolio dianalisis menggunakan indeks Sortino. Hasilnya menunjukan bahwa kinerja portofolio model CMV lebih baik dibandingkan model portofolio MAD. [This study discusses the formation of optimal portfolios using the Mean Absolute Deviation (MAD) model and the Conditional Mean Variance (CMV) model. The MAD portfolio model measures portfolio risk by using average standard deviations so that optimal portfolios solved by using linear programming. Meanwhile the CMV portfolio model, the average return estimated by using the Autoregressive (AR) model and the risk (variance) estimated by using the GARCH model. Furthermore, both portfolio models applied in forming optimal portfolios for stocks listed in the Indonesian Syariah Stock Index (ISSI) for the period 4 July 2016 to 4 July 2018. The performance of both portfolios analyzed by using the Sortino index. The results show that the portfolio performance of the CMV model is better than MAD portfolio model.]
STRUCTURAL EQUATION MODELING WITH GENERALIZED STRUCTURED COMPONENT ANALYSIS ON THE RELATIONSHIP BETWEEN RENUMERATION AND MOTIVATION ON EMPLOYEE PERFORMANCE AT UIN SUNAN KALIJAGA YOGYAKARTA Supandi, Epha Diana
MEDIA STATISTIKA Vol 13, No 2 (2020): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.13.2.136-148

Abstract

Structural equation modeling (SEM) is a multivariate statistical analysis technique that is used to analyze the structural relationships between observed variables and latent constructs. SEM has several methods one of which is Generalized Structured Component Analysis (GSCA). An empirical application concerning the relationship between renumeration and work motivation on employee performance is presented to illustrate the usefulness of the GSCA method. Data were collected by a questionnaire distributed to lecturers and staffs at UIN Sunan Kalijaga Yogyakarta. The result showed that the remuneration variable had a significant and positive impact on work motivation. Also, the work motivation variable had a significant and positive effect on employee performance.
Predicting Interval of Product Reliability With Bootsrap Percentile Method Akhmad Fauzy; Epha Diana Supandi
Jurnal ILMU DASAR Vol 11 No 2 (2010)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

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Abstract

In this article, two methods are proposed to give the interval estimation for reliability function from a product. Reliability function is a probability of an individual (product) surviving till time t. Some resecearchers usually use traditional method to construct interval estimation. This interval needs an assumption that sample is exponentially distributed. This research applied another method, namely Bootstrap percentile. Bootstrap method is more potential in constructing interval estimation for reliability function from a product.
Penerapan Estimasi Fast-MCD dan SOCP dalam Pembentukkan Portofolio Robust Mean Variance Epha Diana Supandi; Dedi Rosadi; Abdurakhman Abdurakhman
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 14, No 1 (2014)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v14i1.1086

Abstract

Portofolio model Mean Variance (MV) menitikberatkan pada penggunaan vektor rata-rata danmatriks kovarian dalam pembentukkan portofolio optimal. pembentukkan portofolio menggunakanmodel MV menjadi optimal, karena Σ????dan ????̂ adalah Maximum Likelihood Estimator bagi Σ dan μ. Padakenyataanya data keuangan sering menyimpang dari kenormalan, sehingga pembentukkan portofoliorobust menjadi sangat penting. Pada penelitian ini akan membandingkan portofolio mean variancemelalui pendekatan Fast-MCD dan SOCP (second order cone programming). Hasil studi kasus padasaham yang terdaftar di Jakarta Islamics Index menunjukkan portofolio dengan pendekatanoptimisasi robust (SOCP) lebih unggul dibandingkan portofolio model MV maupun Fast MCD.
PENDUGAAN SELANG TAHAN HIDUP DARI DATA UJI HIDUP BERDISTRIBUSI PARETO DI BAWAH SENSOR TIPE II DENGAN METODE BAYESIAN (STUDI KASUS PARAMETER SKALA DIKETAHUI) Mohd. Rizam Abu Bakar; Epha Diana Supandi
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 3, No 1 (2003)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v3i1.550

Abstract

Bayesian adalah suatu metode untuk menduga parameter. Metode ini dapat diterapkan pada analisis uji hidup. Dalamtulisan ini diuraikan tentang pendugaan selang tahan hidup dari data uji hidup berdistribusi Pareto dibawah sensor tipe II denganmetode Bayesian, khususnya pada kasus parameter skala diketahui. Arnold dan Press (1989) telah melakukan pendugaan danperkiraan dengan metode bayesian pada data Pareto. Geisser (1985) telah menduga selang pada observasi eksponensial danPareto. Sementara Arnold dan Press (1983) telah membuat inferensi Bayesian pada populasi pareto
Regresi Data Panel untuk Mengetahui Faktor-Faktor yang Mempengaruhi IPM di Kabupaten/Kota Provinsi DIY Epha Diana Supandi; Riska Yulianti; Akhmad Fauzy
Statistika Vol. 22 No. 2 (2022): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v22i2.1122

Abstract

The Human Development Index (HDI) is a regional or national welfare index based on three aspects, namely a long and healthy life, knowledge, and a decent standard of living. This study aims to determine the factors that affect the HDI of Regency/City in the Province of the Special Region of Yogyakarta (DIY) in 2016-2021. These factors include poverty rates, average length of schooling, gross regional domestic product, and health complaints. The analysis used is panel data regression. The influencing factors are the variable of poverty level, average length of schooling and gross regional domestic product.
Pembentukan Portofolio Robust Mean-Variance Saham Syariah Jakarta Islamic Index (JII) Melalui Pendekatan Analisis Klaster K-Medoids Widiawati, Alfina Viona Isabela; Epha Diana Supandi
Statistika Vol. 24 No. 2 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i2.3994

Abstract

ABSTRAK Portofolio adalah kumpulan dari beberapa aset. Tujuan pembentukan portofolio yaitu untuk menghasilkan return yang paling tinggi sambil mengurangi risiko. Untuk menghindari outlier yang sering terjadi dalam portofolio model Mean-Variance (MV), perlu menggunakan estimasi robust. Data penelitian menggunakan closing price bulanan dari saham-saham yang konsisten selalu masuk ke dalam kelompok Jakarta Islamic Index (JII) periode Januari 2019 – Juni 2023. Tahap awal analisis menggunakan teknik klastering metode K-Medoids berdasarkan pada nilai expected return dan risiko. Klasterisasi dilakukan untuk menghemat waktu dan menekan biaya manajemen portofolio. Hasil analisis klaster menciptakan dua klaster. Saham INCO dan ADRO mewakili klaster pertama, dan saham KLBF dan AKRA mewakili klaster kedua. Keempat saham representasi tersebut dibentuk portofolio MV robust S dan portofolio MV robust Constrained-M (CM). Kinerja portofolio diukur menggunakan sharpe ratio. Hasil analisis menunjukkan bahwa kinerja model portofolio robust MV estimasi Constrained-M (CM) mengungguli kinerja model portofolio robust MV estimasi S. ABSTRACT A portfolio is an assortment of several items. The goal of portfolio construction is to get the maximum return at the least amount of risk. Robust estimate is a means to mitigate the sensitivity of the Mean-Variance (MV) model portfolio to outliers. The research data uses monthly closing prices of stocks that are consistently included in the Jakarta Islamic Index (JII) group for the period January 2019 - June 2023. The initial stage of analysis uses the K-Medoids method clustering technique based on the expected return and risk values. The purpose of the clustering is for time efficiency and to reduce the amount of costs in managing the portfolio. The results of the cluster analysis formed two clusters, where the first cluster is represented by INCO and ADRO stocks. While the second cluster is represented by KLBF dan AKRA stocks. The four representative stocks are formed MV robust S portfolio and MV robust Constrained-M (CM) portfolio. Portfolio performance is measured using the sharpe ratio. According to the analysis's findings, the Constrained-M (CM) estimation MV robust portfolio model performs better than the S estimation MV robust portfolio model.
Fourier Series Nonparametric Regression Modeling in the Case of Rainfall in West Java Province Anatansyah Ayomi Anandari; Supandi, Epha Diana; Musthofa, Muhammad Wakhid
IJID (International Journal on Informatics for Development) Vol. 11 No. 1 (2022): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3300

Abstract

The Fourier series is a trigonometric polynomial that has flexibility, so it adapts effectively to the local nature of the data. This Fourier series estimator is generally used when the data used is investigated for unknown patterns and there is a tendency for seasonal patterns. This study aims to determine the results of the best Fourier series nonparametric regression model and the level of accuracy of the Fourier series nonparametric regression model on rainfall data by month in West Java Province in 2015-2019. This research is about a nonparametric regression model of Fourier series which is estimated using Ordinary Least Square method. Nonparametric regression using the Fourier series approach was applied to Rainfall data in West Java Province in 2015-2019. The independent variables used were the average air humidity, air pressure, wind speed, and air temperature. The model used to model the amount of rainfall in West Java Province is a nonparametric Fourier series. The nonparametric regression model is the best Fourier series with K =13 values obtained Generalized Cross Validation, Mean Square Error, and R2 respectively at 549.92; 462.09; and 97.30%. The results showed that the variables of air humidity and air pressure had a significant effect on rainfall.
Co-Authors Abdurakhman Abdurakhman Akhmad Fauzy Anatansyah Ayomi Anandari Dedi Rosadi Jana, Padrul Luh Putu Ratna Sundari Mohd. Rizam Abu Bakar Muhammad Wakhid Musthofa Noor Saif Muhammad Mussafi Riska Yulianti Vanti, Eka Nur Widiawati, Alfina Viona Isabela Zain, Zuva Amalina