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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Media Statistika Jurnal Studi Manajemen Organisasi Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Jiko (Jurnal Informatika dan komputer) JURNAL PENDIDIKAN TAMBUSAI Jurnal Pendidikan dan Konseling Jurnal Sistem informasi dan informatika (SIMIKA) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) International Journal of Advances in Data and Information Systems Al-Mutharahah: Jurnal Penelitian dan Kajian Sosial Keagamaan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) International Journal of Community Service International Journal of Data Science, Engineering, and Analytics (IJDASEA) Journal of Renewable Energy, Electrical, and Computer Engineering Jurnal Inkofar Kreatifitas: Jurnal Ilmiah Pendidikan Islam Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Eksponensial Baitul Hikmah: Jurnal Ilmiah Keislaman Kohesi: Jurnal Sains dan Teknologi ITIJ Seminar Nasional Teknologi dan Multidisiplin Ilmu Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal ilmiah teknologi informasi Asia
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Journal : Media Statistika

FORECASTING FARMER EXCHANGE RATE IN CENTRAL JAVA PROVINCE USING VECTOR INTEGRATED MOVING AVERAGE Trimono, Trimono; Sonhaji, Abdulah; Mukhaiyar, Utriweni
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.13.2.182-193

Abstract

Farmer Exchange Rate (FER) is an indicator that can be used to measure the level of farmers welfare. For every agriculture sector, FER is affected by the historical price of harvest from the corresponding sector and historical prices of other agriculture sectors. In Central Java Province, rice & palawija, horticulture, and fisheries are the largest agriculture sectors which is the main livelihood for most of the population. FER forecasting is a crucial thing to determine the level of farmers welfare in the future. One method that can be used to predict the value of a variable that is influenced by the historical value of several variables is Vector Time Series. An empirical study was conducted using FER data from the rice & palawija, horticulture and fisheries sectors for January 2011-June 2017 in Central Java Province. The results obtained show that by using the VIMA(2.1) model, the FER prediction was very accurate, with MAPE values were 1.91% (rice & palawija sector), 2.44% (horticulture sector), and 2.18% (fisheries sector).
RISK ASSESSMENT OF STOCKS PORTFOLIO THROUGH ENSEMBLE ARMA-GARCH AND VALUE AT RISK (CASE STUDY: INDF.JK AND ICBP.JK STOCK PRICE) Tarno, Tarno; Trimono, Trimono; Maruddani, Di Asih I; Wilandari, Yuciana; Utami, Rianti Siswi
MEDIA STATISTIKA Vol 14, No 2 (2021): 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.14.2.125-136

Abstract

Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stock portfolio, the Value at Risk (VaR) can be predicted through the portfolio return. If portfolio return variance is heteroskedastic risk prediction can be done by using VaR with ARIMA-GARCH or Ensemble ARIMA-GARCH model approach. Furthermore, the accuracy of VaR is tested through Backtesting test. In this study, the portfolio is formed from PT Indofood CBP Sukses Makmur (ICBP.JK) and PT Indofood Sukses Makmur Tbk (INDF.JK) stocks from 01/01/2018 to 07/30/2021. The results showed that the best model is  Ensemble ARMA-GARCH with MSE 1.3231×10-6. At confidence level of 95% and 1 day holding period, the VaR of the Ensemble ARMA-GARCH was -0.0213. Based on the Backtesting test, it is proven to be very accurate to predict the value of loss risk because the value of the Violation Ratio (VR) is equal to 0.
STOCK PRICE PREDICTION IN INDONESIA USING EXTREME GRADIENT BOOSTING OPTIMIZED BY ADAPTIVE PARTICLE SWARM OPTIMIZATION Safira, Alya Mirza; Trimono, Trimono; Hindrayani, Kartika Maulida
MEDIA STATISTIKA Vol 18, No 1 (2025): 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.18.1.105-115

Abstract

High volatility is a major problem in generating accurate predictions of stock prices. It also causes unstable predictions and increases the loss risk. Therefore, an adaptive prediction model that is able to adjust to dynamic data pattern changes is needed. This study aims to address these issues by developing an Extreme Gradient Boosting (XGBoost) model optimized using Adaptive Particle Swarm Optimization (APSO). XGBoost was chosen for its ability to handle nonlinear relationships and minimize overfitting, while APSO serves to adaptively adjust parameters to obtain the optimal combination of hyperparameters. The novelty of this research lies in the application of XGBoost-APSO integration in the context of stock price prediction in the Indonesian capital market, which is characterized by high volatility. The study was conducted using daily closing price data of PT Aneka Tambang Tbk (ANTM) shares from November 2020 to May 2025 to predict prices seven days ahead. The results show that the XGBoost-APSO model provides the best performance with a MAPE value of 0.2%, superior to XGBoost-PSO (2.58%) and standard XGBoost (2.91%). This approach effectively improves prediction accuracy and supports quick and accurate investment decision making, while contributing to the development of intelligent prediction systems in the Indonesian capital market.
Co-Authors Abda Abda Abdullah Abdullah Adam, Cindi Ade Irma Agustian Adiwidyatma, Afdhal Reshanda Aliya Dasa Pramesthi Amanillah, Rahmatul Ardiani, Ardia Eva Arif, Farah Yusnaida Arifta, Septia Dini Aurelia, Cenditya Ayu Aviolla Terza Damaliana Awang, Wan Suryani Wan Aziziyah, Luqna Azni Aisyah Azzahra, Adelia Ramadhina Bainar Bainar, Bainar Bey Lirna, Cagiva Chaedar Carissa, Savvy Prissy Amellia Damaliana, Aviolla Terza Dewi, Ni Luh Ayu Nariswari Di Asih I Maruddani Di Asih I Maruddani Diash, Hakam Dzakwan Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Fahrudin, Tresna Maulana Fairuz Luthfia Winoto Putri, Maretta Febri Giantara Febriyanti, Alvi Yuana Febyanti, Iin Fitriani, Aulia Nur Hadi, Surjo Hadiyan Pradipta, Alvino Hasan Herlina Herlina Hervrizal, Hervrizal Hindrayani, Kartika Maulida I Gede Susrama Mas Diyasa Icha Rohmatul Jannah idhom, Mohammad Ikaningtyas, Maharani Irawan, Tanaya Anindita Kartini Kartini Kassim, Anuar bin Mohamed Khairunisa, Adenda Khosyi, Hanun Aufa Nur Kusdani, Kusdani Kuswardana, Dendy Arizki Linggasari, Dienna Eries Lisanthoni, Angela Maruddani, Di Asih Mas Diyasa, I Gede Susrama Mas Diyasa, I Gede Susrama Susrama Maulana Pasha, Naufal Ricko Maulidiyyah, Nova Auliyatul Mohammad Idhom Muhaimin, Amri Nabila, Nasywa Azzah Nafiah, Fajria Ulumin Nariyana, Calvien Danny Nasution, Baktiar Nathania, Vannesa Ningrum, Imelda Widya Ningtiyas, Rona Wulan Novita Anggraini Nugraheni, Setiawati Oktaviani, Sheny Eka Panglima, Talitha Fujisai Prisma Hardi Aji Riyantoko Putra, Andrawana Putri Ariyani, Kinanthi Putri, Irma Amanda Putri, Nabila Rizky Amalia Rafiqah, Lailan Rafli Feandika Nugroho, Muhammad Ratna Yulistiani Renaldi, Sahat Rhomaningtias, Lina Riswanda, Mohammad Nizar Riyantoko, Prismahardi Aji Ryan Dana, Alvin Sabela, Sefilah Naurah Safira Devi, Arsita Safira, Alya Mirza Salma Namira, Alivia Saputra, Wahyu Syaifullah Jauharis Sihananto, Andreas Sonhaji, Abdulah Sugiarti, Nova Putri Dwi Suprapto, Rheinka Elyana Susrama Mas Diyasa , I Gede Syamsul Rizal Syukri Syukri Tarno Tarno Taufik, Ikbar Athallah Terza Damaliana, Aviolla Utami, Rianti Siswi Utriweni Mukhaiyar Valentina, Tiara Wardah Ariij Adibah Wardah, Salsabila Wibowo, Muhammad Bagas Satrio Widayawati, Eny Widison, Daffin Tanjiro Yuciana Wilandari yuliza, eva Zalfa Assyadida, Azizah