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All Journal Media Statistika Statistika Jurnal Gaussian MIX : Jurnal Ilmiah Manajemen Indonesian Journal of Applied Statistics (JRAMB) Jurnal Riset Akuntansi Mercu Buana
Di Asih I Maruddani
Department Of Statistics, Faculty Of Science And Mathematics, Diponegoro University
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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VALUE AT RISK PADA PORTOFOLIO SAHAM DENGAN COPULA ALI-MIKHAIL-HAQ Delsy Nurutsaniyah; Tatik Widiharih; Di Asih I Maruddani
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.45 KB) | DOI: 10.14710/j.gauss.v8i4.26754

Abstract

Investment is one alternative to increase assets in the future. Investors can invest in a portfolio to reduce the level of risk. Value at Risk (VaR) is a measuring tool that can calculate the worst loss over a given time period at a given confidence level. GARCH (Generalized Autoregressive Conditional Heteroskedasticity) is used to model data with high volatility. The teory of copula is a powerful tool for modeling joint distribution for any marginal distributions. Ali-Mikhail-Haq copula from Archimedean copula family can be applied to data with dependencies τ between -0.1817 to 0.3333. This research uses Ali-Mikhail-Haq copula with a Monte Carlo simulation to calculate a bivariate portfolio VaR from a combination stocks of PT Pembangunan Perumahan Tbk. (PTPP), PT Bank Tabungan Negara Tbk. (BBTN), and PT Jasa Marga Tbk. (JSMR) in the period of March 3, 2014 - March 1, 2019. The results of VaR calculation on bivariate portfolio for next 1 day period obtained the lowest VaR is owned by bivariate portfolio between PTPP and JSMR with a weight of 30% and 70% at confidence level of 99%, 95%, and 90% respectively are 4.014%, 2.545%, and 1.876%.Keywords: Value at Risk, GARCH, Ali-Mikhail-Haq Copula, Monte Carlo
PENGUKURAN VALUE AT-RISK PADA PORTOFOLIO OBLIGASI DENGAN METODE VARIAN-KOVARIAN Khoirul Anam; Di Asih I Maruddani; Puspita Kartikasari
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.v9i4.29012

Abstract

A bond is investment instrument that is basically a debt investment. The profit gained in investing will be comparable with the risk. An investor must pay attention to the size of the risk in choosing bonds. Value at-Risk (VaR) is a risk measurement instruments for measure the maximum loss of asset or portfolio over a spesicif time interval for a given confidence level under normal market conditions. The purpose of this paper is to explain VaR measurement on bond portfolio using variance-covariance method and prove that method is valid to estimate VaR’s model using likelihood ratio. Variance covariance method was chosen because giving lower estimate potential volatility of asset or portfolio than historical simulation and Monte-Carlo simulation. This article use goverment bonds with code FR0053, FR0061, FR0073, FR0074 and portfolio combination. Normality test of return asset and portfolio are required before calculating VaR values. The result of this paper for confidence level 95% showed that bond portfolio FR0053 with FR0061 have a smaller value with VaR values 2,28% of the total market value. It was concluded that VaR bond portfolio are smaller than VaR single asset. Verification test estimate that VaR values using variance-covariance is valid at confidence level 95%.
METODE BAYESIAN PADA SISTEM ANTREAN PELAYANAN MENGGUNAKAN GUI R (Studi Kasus: Antrean Pelayanan di Kantor Dinas Kependudukan dan Pencatatan Sipil Kota Semarang) Atikah Mufidah; Sugito Sugito; Di Asih I Maruddani
Jurnal Gaussian Vol 11, No 1 (2022): 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.v11i1.34002

Abstract

The increase population of Semarang City has given many kinds of problem from births, deaths, marriages and other important events. The change of population identity data causes the number of visitors to the Semarang City Dispendukcapil to increase so that the service system becomes busy. The study aims to determine whether the service system in the Dispendukcapil is good or not. This can be known by determining the distribution of arrival patterns and service patterns to obtain a queuing system model and system performance measures. In this study, the distribution of arrival patterns and service patterns is determined by finding the posterior distribution using the Bayesian method. The Bayesian method was chosen because it is able to combine the distribution of the sample in the current study with previous information for the same case. Posterior distribution can be obtained if it has elements, namely prior distribution and likelihood function. The distribution of arrival patterns and service patterns obtained from prior information, follows the Discrete Uniform and Log-Normal distribution. Based on the calculation and analysis of the posterior distribution, the service system model of the Dispendukcapil Semarang City is obtained, namely for the Customer Service counter, and  for the legalization counter and the population document service counter with a good service system.Keywords:Population, Dispendukcapil Semarang City, queue, Bayesian, prior distribution, posterior distribution, queuing system model, Beta, Gamma, Inverse Gamma.
PENENTUAN MODEL ANTREAN NON-POISSON DAN PENGUKURAN KINERJA PELAYANAN BUS RAPID TRANSIT TRANS SEMARANG (STUDI KASUS: SHELTER PEMBERANGKATAN BRT KORIDOR V) Purwati Ayuningtyas; Sugito Sugito; Di Asih I Maruddani
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.v10i1.30932

Abstract

One of the queue systems that is often found  in daily life is the transportation service system, for example a queue system at the shelters departure of corridor V Bus Rapid Transit (BRT) Trans Semarang. Corridor V has three departure shelters, they are Shelter Victoria Residence, Shelter Marina, and Shelter Bandara Ahmad Yani. Corridor V was choosen, because of its high load factor on January to June 2019. Based on the observation, the service time at the departure shelter is usually longer than the normal shelter. This causes the rise of queue at the departure shelters. The queue at the departure shelters can hamper the arrival of BRT at the other shelters, so the application of the queue theory is needed to find out the extent of operational effectiveness at the departure shelters. The resulting queue model is the Non-Poisson queue model, the queue model for Victoria Residence Shelter: (DAGUM/GEV/1):(GD/∞/∞), Marina Shelter: (DAGUM/G/1):(GD/∞/∞), and Bandara Ahmad Yani Shelter: (GEV/GEV/1):(GD/∞/∞). Based on the value from measurement of the queue system performance, it can be conclude that the three departure shelters of corridor V BRT Trans Semarang have some optimal condition. Keywords: Shelter Departure of Corridor V, Non-Poisson Queueing Model, Dagum, Generalized Extreme Value, System Perfomance Measure  
ANALISIS METODE BAYESIAN PADA KINERJA SISTEM ANTREAN INSTALASI RAWAT JALAN RSUP DR. KARIADI (Studi Kasus: Poliklinik Mata, Poliklinik THT, Laboratorium, dan Pendaftaran) Eny Sulistyowati; Sugito Sugito; Di Asih I Maruddani
Jurnal Gaussian Vol 10, No 3 (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.v10i3.32804

Abstract

Indonesian people’s awareness of the importance of health has increased significantly so that it has a positive impact on the development of the health sector in Indonesia. The largest service facility in Central Java Province is RSUP Dr. Kariadi. The number of patients who came for an examination at Dr. Kariadi’s arrival rate is unpredictable. This can cause the service system to be busy and result in queues. The purpose of this study was to find out how the service system in Dr. Kariadi especially eye polyclinic, ENT polyclinic, laboratory, and registration. Queue theory has random arrivals and services. Bayesian method is used to analyze the queue system, that has been running for a long time by combining the prior and likelihood distribution of samples. Prior distribution is obtained from previous research, namely the Poisson distribution. Meanwhile, the likelihood of the sample obtained from the current study is the Poisson distribution and the Negative Binomial distribution. The resulting queue models for the eye polyclinic are (GAMM/BETA/4):(GD/∞/∞), ENT polyclinic (GAMM/GAMM/2):(GD/∞/∞), laboratory (GAMM/GAMM/4):(GD/∞/∞), and registration (GAMM/GAMM/3):(GD/∞/∞). Based on the results of the study, it was found that the patient care system at the eye polyclinic, ENT polyclinic, laboratory, and registration met steady state condition, meaning that the service system was running well. The value of the unemployment rate at the eye polyclinic is 96,36%; ENT polyclinic 31,86%; laboratory 34,87% and registration 32.85%. Thus, at the eye polyclinic, the unemployment rate is greater than the busy level. Meanwhile, in ENT polyclinics, laboratories, and registration is the opposite occurs. 
PENGUKURAN KINERJA PORTOFOLIO OPTIMAL CAPITAL ASSET PRICING MODEL (CAPM) DAN ARBITRAGE PRICING THEORY (APT) (Studi Kasus : Saham-saham LQ45) Dedi Baleo Pasaribu; Di Asih I Maruddani; Sugito Sugito
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.v7i4.28870

Abstract

Investing is placing money or funds in the hope of obtaining additional or specific gains on the money or funds. The capital market is one place to invest in the financial field of interest to investor. This is because the capital market gives investor the freedom to choose securities traded in the capital market in accordance with the wishes of investor. Investor are included in risk averter, that means investor will always try to avoid risk. To avoid risk, investor try to diversify their investment. Diversification concept commonly used is portfolio. To maximize the return to be earned, the investor will invest his funds into several stocks in order to earn a greater profit. Capital Asset Pricing Model (CAPM) is a balance model that describes the relation of a risk with return more simply because it uses only one variable to describe the risk. Arbitrage Pricing Theory (APT) is a balance model that used many risk variables to see the relation of risk and return. With both models will be obtained a portfolio with each constituent stock is four stocks selected from 45 stocks in the LQ45 index. To find out which portfolio is the best performed a performance analysis using the Sharpe index. From the measurement result, it is found that the best portfolio is the CAPM portfolio with composite stock is PTBA with investment weight of 0.467%, BUMI with investment weight of 12.855%, ANTM with investment weight of 53.077% and PPRO with investment weight of 33.601%. Keywords: LQ45, portfolio, Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory                       (APT), Sharpe Index 
ANALISIS SENTIMEN GOJEK PADA MEDIA SOSIAL TWITTER DENGAN KLASIFIKASI SUPPORT VECTOR MACHINE (SVM) Nur Fitriyah; Budi Warsito; Di Asih I Maruddani
Jurnal Gaussian Vol 9, No 3 (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.v9i3.28932

Abstract

Appearance of PT Aplikasi Karya Anak Bangsa or as known as Gojek since 2015 give a convenience facility to people in Indonesia especially in daily activities. Sentiment analysis on Twitter social media can be the option to see how Gojek users respond to the services that have been provided. The response was classified into positive sentiment and negative sentiment using Support Vector Machine method with model evaluation 10-fold cross validation. The kernel used is the linear kernel and the RBF kernel. Data labeling can be done with manually and sentiment scoring. The test results showed that the RBF kernel gets overall accuracy and the highest kappa accuracy on manual data labeling and sentiment scoring. On manual data labeling, the overall accuracy is 79.19% and kappa accuracy is 16.52%. While the labeling of data with sentiment scoring obtained overall accuracy of 79.19% and kappa accuracy of 21%. The greater overall accuracy value and kappa accuracy obtained, the better performance of the classification model. Keywords: Gojek, Twitter, Support Vector Machine, overall accuracy, kappa accuracy
Valuasi Harga Saham PT Aneka Tambang Tbk sebagai Peraih IDX Best Blue 2016 Trimono Trimono; Di Asih I Maruddani
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 17, No 1 (2017)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v17i1.2579

Abstract

Menginvestasikan dan untuk membeli saham sebuah perusahaan merupakan salah satu bentuk investasi sektor finansial yang banyak diminati oleh para investor. Keuntungan investasi saham yang diperoleh, dapat dilihat dari nilai return saham. Harga saham adalah faktor utama yang berpengaruh terhadap nilai return saham. Namun, harga saham pada masa yang akan datang sering kali sulit untuk diprediksi. Geometric Brownian Motion (GBM) merupakan metode yang dapat digunakan untuk memprediksi harga saham jika diasumsikan return saham masa lalu berdistribusi normal. Jika dalam return saham masa lalu yang berdistribusi normal terdapat lompatan (jump), maka digunakan metode Jump Diffusion. Setelah diperoleh harga saham prediksi, dapat diukur nilai risiko investasinya. Hasil prediksi harga saham PT Aneka Tambang Tbk  periode 01/12/2016 sampai dengan 31/1/2017 dengan metode GBM, diperoleh nilai MAPE sebesar 11,01%. Berdasarkan nilai skewness dan kurtosis, dalam data return saham ANTM terdapat lompatan, sehingga harga saham ANTM lebih tepat dimodelkan dengan metode Jump Diffusion. Hasil prediksinya diperoleh nilai MAPE sebesar 1,95%. Metode Jump diffusion lebih tepat digunakan untuk prediksi, karena menghasilkan nilai MAPE yang lebih kecil. Untuk mengukur risiko investasi harga saham prediksi yang diperoleh dari model Jump Diffusion, digunakan metode VaR simulasi Monte Carlo dengan tingkat kepercayaan 95%. Dalam jangka waktu 1 hari setelah tanggal 25 Januari 2017 kerugian yang diterima tidak melebihi 5,617%. Berdasarkan uji backtesting, nilai VaR harga saham prediksi dengan metode Jump Diffusion pada taraf signifikansi 5% menghasilkan perhitungan yang akurat, karena tidak ditemukan adanya pelanggaran.Kata Kunci: Geometric Brownian Motion, Jump Diffusion Model, Value at Risk, Backtesting 
RISIKO DAN STRATEGI INVESTASI SAHAM SECOND LINER DENGAN GLOBAL MINIMUM VARIANCE PORTFOLIO Di Asih I Maruddani; Tutut Dewi Astuti
(JRAMB) Jurnal Riset Akuntansi Mercu Buana Vol 7, No 1: Mei 2021
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jramb.v7i1.1559

Abstract

Saham lapis kedua (second liner) menjadi perhatian investor karena mendorong kenaikan IHSG di masa resesi global akibat pandemi. Indeks Small Medium Cap (SMC) merupakan kumpulan saham kelompok emiten kecil dan menengah yang terdaftar di BEI dengan kinerja fundamental dan likuiditas yang baik. Penilaian saham, pemilihan kombinasi portofolio, dan ukuran risiko menjadi dasar strategi yang dilakukan investor. Komposisi saham pembentuk portofolio dilakukan dengan tujuan mendapatkan risiko minimal dengan return maksimal. Global Minimum Variance Portfolio mengoptimalkan tujuan ini dengan memanfaatkan fungsi Lagrange. Pada kondisi pandemi ini, 3 saham second liner yaitu TOWR, MIKA, dan PGAS menunjukkan outperform yang membantu menahan kejatuhan IHSG dan mendorong kenaikan IHSG secara signifikan. Proporsi saham yang terbentuk dengan komposisi 41,93% saham TOWR, 32,62% saham MIKA, dan 25,45% saham PGAS. Portofolio yang terbentuk berdasarkan proporsi ini menunjukkan sifat skewness dan kurtosis, sehingga pengukuran Value at Risk menggunakan Value at Risk dengan pengembangan Ekpansi Cornish-Fisher yang memperhatikan sifat skewness dan kurtosis dari data. Risiko investasi pada portfolio ini dengan tingkat keyakinan 95% untuk 1 periode ke depan cukup kecil, yaitu sebesar 3,60% dari investasi yang ditanamkan.
KLASTERISASI PERUSAHAAN SECOND LINER DI MASA RESESI GLOBAL DENGAN INDIKATOR RASIO KEUANGAN Tutut Dewi Astuti; Di Asih I Maruddani
(JRAMB) Jurnal Riset Akuntansi Mercu Buana Vol 7, No 2: November 2021
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jramb.v7i2.1989

Abstract

Masa pandemi Covid-19 yang menyebabkan kondisi resesi global dunia berimbas pada dunia investasi dan keuangan. IHSG sebagai indikator kinerja saham di Indonesia melemah. Saham-saham blue chip sebagai pendorong utama bursa mengalami penurunan kinerja. Akan tetapi saham lapis kedua (second liner) berhasil menahan turunnya IHSG sepanjang tahun 2020. Harga rendah dan potensi keuntungan yang tinggi menjadi pertimbangan yang menarik investor beralih pada saham-saham di kelompok tersebut. Saham-saham lapis menengah yang tergabung dalam Index PEFINDO25 cukup mampu mempertahankan kinerja keuangannya. Indikator yang diwakili dengan nilai-nilai rasio keuangan perusahaan cukup baik. Akan tetapi sebagai kelompok saham lapis kedua, investor harus tetap cermat dalam menganalisis kinerja perusahaan-perusahaan tersebut. Pengelompokan perusahaan berdasar karakteristik rasio keuangannya perlu dilakukan. Penelitian ini bertujuan membuat klaster perusahaan yang tergabung dalam Index PEFINDO25 menggunakan Hierarchical Clustering dengan Average Linkage. Jumlah klaster optimum yang diperoleh berdasarkan statistik Pseudo-F adalah 3 klaster. Indikator yang digunakan pada klasterisasi ini adalah rasio keuangan likuditas, solvabolitas, profitabilitas, dan aktivitas data laporan keuangan perusahaan periode tahun 2020 selama masa krisis global. Hasil menunjukkan bahwa KLBF merupakan perusahaan yang mempunyai karakteristik jauh berbeda dibandingkan perusahaan lainnya. Modal kerja yang tinggi disertai rasio keuangan yang baik membuat KLBF menjadi perusahaan terbaik di kelompok ini. BEST, DMAS, MIKA, dan TSPC merupakan kelompok dengan modal kerja sedang dan rasio keuangan baik. Sedangkan AKRA, BULL, ELSA, ERAA, ESSA, GJTL, HEAL, ITMG, LSIP, MDKA, MNCN, PWOR, PTBA, SCMA, SIDO, TBLA, TINS, UNVR, WOOD merupakan klaster perusahaan dengan kriteria modal kerja rendah dan rasio keuangan baik.
Co-Authors Abdul Hoyyi Abdurakhman Abdurakhman Agus Rusgiyono Ahmad Badruttamam Alifia Hana Linda Rachmawati Atikah Mufidah Budi Warsito Dede Andrianto Dedi Baleo Pasaribu Delsy Nurutsaniyah Desi Nur Rahma Diah Safitri Dina Rahma Prihatiningsih Dwi Harti Pujiana Dwi Ispriyanti Eka Anisha Eny Sulistyowati Fatiya Nur Umma Fredy Yoseph Marianto Hanik Malikhatin Hasbi Yasin Hasbi Yasin Henny Setyowati Juria Ayu Handini Khoirul Anam Lina Tanasya Maria Odelia Mas'ad Mas'ad Meiliawati Aniska Mia Anastasia Sinulingga Mustafid Mustafid Mutik Dian Prabaning Tyas Nidaul Khoir Nur Fitriyah Nur Khofifah Purwati Ayuningtyas Puspita Kartikasari Puspita Kartikasari Putri Devitasari Reno Penggalih Surya Wardhani Reyuli Andespa Ria Epelina Situmorang Rita Rahmawati Rukun Santoso Salsabila Syifa Binsanno Setiani Setiani Sudarno Sudarno Sugito Sugito Suparti Suparti Tarno Tarno Tatik Widiharih Trimono Trimono Trimono Trimono Tutut Dewi Astuti Tutut Dewi Astuti Yustian Dwi Saputra