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Analisis Klaster dalam Pembentukan Portofolio Robust Mean-Variance Epha Diana Supandi; Yogi Anggara
Jurnal Sains Matematika dan Statistika Vol 9, No 1 (2023): JSMS Januari 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v9i1.19003

Pembentukan portofolio adalah proses menggabungkan beberapa aset dengan tujuan menghasilkan return tertinggi pada tingkat risiko terendah. Portofolio optimal model Mean-Variance (MV) sangat sensitif terhadap keberadaan outlier. Salah satu cara untuk mengatasi kelemahan portofolio MV adalah dengan menggunakan estimasi robust. Data penelitian menggunakan saham-saham yang terdaftar di Jakarta Islamic Index (JII) dimana pada tahap awal digunakan teknik clustering dengan metode K-Means. Hasil analisis kelompok terbentuk dua klaster, dimana klaster pertama terdiri dari saham ITMG, ADRO, PTBA, dan MDKA sedangkan klaster kedua terdiri dari saham INDF, TLKM, KLBF, dan UNTR. Hasil analisis kinerja saham menunjukkan bahwa klaster pertama model portofolio klasik Obj-10 paling baik karena memiliki sharpe ratio tertinggi. Sedangkan pada klaster kedua portofolio robust model Obj-100 paling baik

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

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

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

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.

Analisis Diskriminan Pada Survei Kepuasan Masyarakat Terhadap Pelayanan BPJS Kesehatan Menggunakan Software R PRAMONO, YUDA EKA; Setyaningsih, Ira; Diana Supandi, Epha
Jurnal Teknik Industri Vol 3, No 2 (2024)
Publisher : Fakultas Teknologi Industri, UNISSULA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jurti.3.2.106-112

Penelitian ini bertujuan untuk menganalisa terkait kepuasan masyarakat terhadap pelayanan BPJS Kesehatan di Kabupaten Pemalang. Penelitian dilakukan dengan menyebarkan kuesioner kepada pengguna BPJS Kesehatan dengan menggunakan jumlah sampel yang diambil sebanyak 50 responden. Penelitian ini dilakukan dengan tujuan untuk mengetahui perbedaan yang signifikan kepuasan masyarakat pengguna BPJS Kesehatan Kabupaten Pemalang dengan membentuk model diskriminan. Metode penelitian yang digunakan adalah metode survey dengan pengumpulan data primer menggunakan angket melalui pengambilan sampel proporsional. Kepuasan pelanggan dibedakan menjadi dua kategori yaitu sangat memuaskan, dan kurang memuaskan. Sedangkan variabel yang diduga mempengaruhi tingkat kepuasan pelanggan adalah Pelayanan Administrasi, Keahlian dan Keterampilan Petugas Pelayanan, Teknologi Pelayanan Medis dan Sikap Petugas Pelayanan Terhadap Hubungan Antar Manusia. Setelah ditemukan hasil survei kepuasan masyarakat kemudian dilakukan proses tahap selanjutnya yaitu analisis diskrimian menggunakan Software R untuk membuat model diskriminan linear. Hasil yang diperoleh bahwa model diskriminan linier berhasil dibentuk dengan koefisiensi varibel X1, X2, X3, dan, X4 dengan hasil yang positif. Prediksi klasifikasi menunjukan sebanyak 45 pengamatan tepat dan sebanyak 5 pengamatan salah, dengan ketepatan klasifikasi 90%. Pada uji signifikansi terkait uji wilks menunjukan p-value sebesar 3.208 x 10-7 sehingga H0 ditolak, dimana menunjukan perbedaan signifikansi antar kelompok. Kemudian terkait keberhasilan data dapat dijelaskan bahwa data tidak berdistribusi normal multivariat karena p-value lebih kecil dari α (0,001052623 < 0.05), dan tidak terdapat adanya multikolinieritas antar variabel bebas karena VIV < 0,05. Didapatkan sebuah rekomendasi yaitu pada persamaan diskriminan linier berperan efektif dalam membedakan kelompok-kelompok berdasarkan variabel bebas, dan kemudian perlu adanya perbaikan pelayanan pada administrasi dan teknologi pelayanan medis untuk meningkatkan kepuasan masyarakat.Kata kunci: Analisis Diskriminan, Kepuasan Masyarakat, Software R

COMPARISON OF ROBUST ESTIMATION ON MULTIPLE REGRESSION MODEL Jana, Padrul; Rosadi, Dedi; Supandi, Epha Diana
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0979-0988

This study aimed to compare the robustness of the OLS method with a robust regression model on data that had outliers. The methods used on the robust regression model were M-estimation, MM-estimation, and S-estimation. The step taken was to check the characteristics of the data against outliers. Furthermore, the data were modeled with and without outliers using the OLS method and the M-, MM-, and S-estimations. The results were very different between the data with and without the outlier models in the OLS method. It was reflected in the intercept and standard error variables generated from the models. Meanwhile, the regression model with the M-, MM-, and S-estimations was quite stable and able to withstand the presence of outliers. Based on the three estimations that were robust against the outliers, the MM-estimation was the best candidate because, in addition to having a stable intercept parameter estimation, it also had the smallest standard error, which was 61.9 in the resulting model.

CLUSTER ANALYSIS OF K-MEANS AND WARD METHOD IN FORMING A ROBUST PORTFOLIO: AN EMPIRICAL STUDY OF JAKARTA ISLAMIC INDEX Zain, Zuva Amalina; Mussafi, Noor Saif Muhammad; Supandi, Epha Diana
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp537-546

Building a portfolio is one method of reducing investment risk. Cluster analysis can shorten the time required to choose companies for a portfolio because it makes it easy to put firms in the same category together. To maintain the best state of the portfolio cluster analysis in the case of data containing outliers, K-means, and ward cluster analysis are employed in conjunction with a robust portfolio strategy. K-means clustering is a popular method for grouping data by assigning observations to clusters based on proximity to the cluster’s center meanwhile the Ward method is based on the size of the distance between clusters by minimizing the number of squares. This study seeks to determine the robust portfolio performance comparison outcomes produced by K-Means and Ward clustering utilizing the Sharpe ratio criterion. The Sharpe ratio is one of the most widely used methods to evaluate a portfolio’s risk-adjusted performance. The greater a portfolio's Sharpe ratio, the better its risk-adjusted performance. Stocks included in the Jakarta Islamic Index 70 (JII70) are used in this research. The results of the formation of a robust portfolio on K-Means clustering produce a return rate of 0.01038627 and risk of 0.1066364, while in the Ward cluster, the portfolio profit rate is obtained at 0.01632749 and the risk is 0.1340073. Based on the Sharpe ratio criteria, in this case, the robust portfolio with the Ward cluster is superior to the K-Means cluster because it produces a higher Sharpe value.

A Full-Profile Conjoint Analysis to Identify University Students’ Preferences Toward Food Delivery Services: A Case Study of the Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta Supandi, Epha Diana; Rochmiyani, Fitri
Journal of Industrial Engineering and Halal Industries Vol. 6 No. 2 (2025): Journal of Industrial Engineering and Halal Industries (JIEHIS)
Publisher : Industrial Engineering Department, Faculty of Science and Engineering, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiehis.5592

The rapid development of digital technology has transformed consumer behavior, particularly in fulfilling food needs through online food delivery services. University students represent one of the most active user groups due to their high mobility and preference for practical lifestyles. This study aims to analyze students’ preferences toward food delivery service attributes and to identify the most influential factors in determining their choices. The research involved 100 respondents from the Faculty of Science and Technology, Universitas Islam Negeri Sunan Kalijaga Yogyakarta, using the traditional conjoint analysis method with a full-profile design approach. Six attributes were examined: type of service, price, payment method, courier service, food quality, and service quality. The results indicate that price has the highest level of importance (25.401%), followed by type of service (22.230%), service quality (16.231%), courier service (15.926%), payment method (10.960%), and food quality (9.252%). The most preferred combination of attributes includes GrabFood or GoFood services with promotional prices, uniformed couriers, diverse food options, and fast delivery. These findings suggest that promotional pricing strategies and service quality improvements are key factors for online food delivery providers to enhance customer satisfaction and attract student users.

Portfolio Risk Assessment Using VaR and CVaR: A Comparative Study of Variance–Covariance Method and Monte Carlo Simulation Epha Diana Supandi; Atika Oktavia
Telematika Vol 19, No 1: February (2026)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v19i1.3120

This study examines portfolio risk in Indonesia’s energy sector by applying Value at Risk (VaR) and Conditional Value at Risk (CVaR) under the Variance–Covariance and Monte Carlo Simulation approaches. The analysis focuses on ten stocks from the oil and gas as well as coal subsectors listed on the Indonesia Stock Exchange (IDX), using monthly closing price data from January 2020 to December 2024. A Weighted Scoring Method (WSM) is first employed to select stocks with superior fundamentals and liquidity, based on market capitalization, return on equity, debt-to-equity ratio, net profit margin, trading volume, and dividend yield. An optimal portfolio is then constructed using the Maximum Sharpe Ratio (MSR) framework, resulting in a portfolio dominated by PTBA, MEDC, and MBAP. Portfolio risk is subsequently estimated using VaR and CVaR at the 95% and 99% confidence levels under both the Variance–Covariance and Monte Carlo approaches. The empirical results indicate that CVaR consistently produces higher risk estimates than VaR, highlighting its superior ability to capture tail risk. Furthermore, the Variance–Covariance method yields slightly more conservative CVaR estimates compared to Monte Carlo Simulation, which is attributed to the near-normal distribution of portfolio returns during the observation period. Model validity is confirmed through backtesting using the Kupiec test, which shows that the VaR estimates satisfy statistical adequacy criteria. Overall, the findings suggest that while the Variance–Covariance approach remains effective under normality assumptions, Monte Carlo Simulation offers greater flexibility in modeling extreme market conditions. This study contributes to the literature by providing empirical evidence on comparative risk estimation methods in Indonesia’s highly volatile energy sector.

Fourier Series Nonparametric Regression Modeling in the Case of Rainfall in West Java Province Anatansyah Ayomi Anandari; Epha Diana Supandi; Muhammad Wakhid Musthofa
IJID (International Journal on Informatics for Development) Vol. 11 No. 1 (2022): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

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

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.

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