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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) EKSAKTA: Journal of Sciences and Data Analysis Jurnal Ilmu Komputer dan Informasi MATEMATIKA Jurnal Sains dan Seni ITS IPTEK Journal of Science IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Natural A Seminar Nasional Informatika (SEMNASIF) Science and Technology Indonesia NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Matematika: MANTIK Syntax Literate: Jurnal Ilmiah Indonesia Business and Finance Journal Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Indonesian Journal of Electrical Engineering and Computer Science Inferensi Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Proceeding ISETH (International Summit on Science, Technology, and Humanity) Sewagati PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Nur Iriawan
Departemen Statistika Institut Teknologi Sepuluh Nopember
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Analisis Pola Persebaran Pelanggan Telat Bayar Listrik Menggunakan Spatial Poisson Point Process Wijaya, Elizabeth Meiliana; Iriawan, Nur
Jurnal Sains dan Seni ITS Vol 14, No 1 (2025)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23373520.v14i1.155296

Abstract

Saat ini, permintaan energi listrik semakin meningkat dari hari ke hari, sementara sumber daya yang dibutuhkan untuk menghasilkan energi ini semakin sedikit. Oleh karena itu, penggunaan listrik harus diperhatikan dengan seksama. PT. Pe-rusahaan Listrik Negara (PLN) (Persero) merupakan perusa-haan penyedia jasa kelistrikan terbesar di Indonesia yang men-yediakan dua jenis layanan listrik, yaitu listrik prabayar dan pasca bayar. Pelanggan listrik pasca bayar perlu membayar tagihan listrik sesuai pemakaiannya di setiap akhir bulan kare-na pelanggan PLN telah diberikan hak untuk menggunakan aliran listrik di tempat tinggal mereka. Namun, masih banyak pelanggan PLN yang mengabaikan proses pembayaran tarif listrik tersebut. Salah satu metode yang cocok untuk melihat karakteristik pelanggan telat bayar listrik adalah dengan Spatial Poisson Process. Metode tersebut digunakan karena data lokasi pelanggan merupakan jenis data spatial point pattern, di mana jenis data tersebut dapat dianalisis dengan pendekatan Point Process. Model terbaik didapatkan dari model masing-masing kecamatan dengan AIC terendah, yaitu -299.012,122 dan jumlah pelanggan telat bayar listrik pada sebagian besar kecamatan secara signifikan dipengaruhi karakteristik daerah yang berbeda-beda, seperti jumlah keluarga pengguna listrik, jumlah koperasi aktif, dan proporsi pelanggan sukses bayar di bulan ke-6.
Bayesian Survival Mixture Model on Years of Schooling in West Papua Province Nitivijaya, Maulidiah; Iriawan, Nur; Kuswanto, Heri
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2015: Proceeding ISETH (International Conference on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.2375

Abstract

Education could be considered as one of the basic pillars to determine the performance indicator of a respective region. Year of schooling is one of the education indexes,which becomes the government's target in the 9-year compulsory education program. This index illustrates the importance of knowledge and higher-level skills. Meanwhile, West Papua Province as one of the youngest provinces in Indonesia is challenged to improve the quality of human resources, particularly in the underdeveloped regions. Therefore, it is important to identify the variables which influence the years of schooling in the West Papua province. Statistically, the type of data such as length of time is frequently used to be the survival analysis. Nevertheless, the distribution patternof the response variables is difficult to be analyzed. For that reason, this study applied mixture model on years of schooling. Mixture model estimation leads to the complex statistical problems with a number of parameters. Bayesian methods accomplish the estimation through the simulation process of Markov Chain Monte Carlo (MCMC). The survival mixture model was formed based on the status of county. Rural areas were evidenced to give the contribution of years of schooling distribution more than urban area up to 59.87 percent. The opportunity to obtain formal education at least to junior high school in urban areas was greater than rural area had, yet it went down faster in year 12-th or in senior high school level. In general, the factors which influenced the years of schooling in urban and rural areas turned out to be different.
Hybrid Geometric Brownian Motion-Markov Switching untuk Peramalan Harga Saham Indonesia Hamdani, Aldan Maulana; Iriawan, Nur; Irhamah, Irhamah
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.35300

Abstract

This study aims to analyse the performance of a stock price forecasting model based on Geometric Brownian Motion (GBM) modified with a Markov Switching (MS) approach. The research gap addressed is the limitation of the classical GBM model, which assumes constant volatility and is therefore unable to capture sudden changes in market regimes. To address these limitations, this study proposes a hybrid GBM-MS model as its main scientific contribution, in whichthe drift and volatility parameters are dynamically estimated following changes in market conditions through a switching mechanism between regimes. Parameter estimation is performed using the Hidden Markov Model. The model's performance is compared with the classical GBM as a benchmark. The research uses daily closing price data of PT Bank Central Asia Tbk. (BBCA) shares for the period 1 July – 30 December 2024. The results show that the hybrid GBM-MS model provides better forcasting accuracy with a MAPE value of 2.25% on training data and 1.38% on testing data, lower than the classical GBM model. These findings confirm that the integration of Markov Switching enhances the model's adaptability in capturing structural changes and market volatility. Practically, the hybrid GBM-MS model can be used as a more reliable forecasting and risk management tool to support investment decision-making, especially in dynamic and unstable market environments.
Pemodelan Saham Sektor Energi Menggunakan Non-Homogeneous Markov Switching Autoregressive (NHMS-AR) dengan Probabilitas Transisi Non-Homogeneous Adam Fahmi Fandisyah; Nur Iriawan; Kartika Fithriasari
Numerical: Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 2 (2025)
Publisher : Universitas Ma'arif Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/numerical.v9i2.7159

Abstract

The movement of energy sector stock returns is dynamic and influenced by external factors that cause changes in market conditions over time. These characteristics indicate the existence of regime shifts that cannot be optimally modeled using conventional linear time series. Therefore, this study aims to model energy sector stock returns in Indonesia using the Non-Homogeneous Markov Switching Autoregressive (NHMS-AR) approach with a focus on the transition probability between regimes influenced by exogenous variables. The data used are monthly logarithmic returns of PT Perusahaan Gas Negara Tbk (PGAS), PT Adaro Energy Indonesia Tbk (ADRO), and PT Medco Energi Internasional Tbk (MEDC) for the period September 2008 to December 2024. The exogenous variables used include the Climate Risk Index, Geopolitical Risk (GPR), and Global Economic Policy Uncertainty (GEPU). The NHMS-AR model is implemented with the assumption that exogenous variables influence the probability of regime shifts, while the autoregressive structure in each regime is homogeneous. The results show that the dynamics of energy sector stock returns can be represented by two hidden regimes: a stable regime and a volatile regime. Transition probability estimates indicate that CRI and GEPU increase the probability of switching between regimes, whereas GPR exhibits an asymmetric effect, depending on the direction of the transition. Furthermore, the volatile regime has a higher degree of persistence than the stable regime. The main contribution of this study lies in the application of NHMS-AR with non-homogeneous transition probabilities to Indonesian energy sector stocks, as well as in presenting empirical evidence on the role of external factors in shaping regime switching dynamics in emerging markets.
Co-Authors Achmad Nuruddin Syaifulloh Adam Fahmi Fandisyah Adam Fahmi Fandisyah Adatul Mukarromah Agus Suharsono Ahyudanari, Ervina Akhmad Ridho Ashariansyah Almuhayar, Mawanda Ani Budi Astuti Ani Budi Astuti Anindya Apriliyanti Pravitasari Ari Purwanto Sarwo Prasojo Bani Unggul, Didik Brodjol Sutija Suprih Ulama Dwi Atmono AW Edijatno Edijatno Eko Fajariyanto Entin Hidayah Ferriastuti, Widiana Fithriasari, Kartika Hady Suryono Hamdani, Aldan Maulana Heri Kuswanto I Nyoman Latra Indira Swa Buana Irhamah Irhamah - Irwan Susanto Jupita Sari Ika Hanugraheni Mahendrawathi Mahendrawathi Mohammad Naufal Abdullah Muhammad Fajar Nadjadji Anwar Ni Luh Putu Ika Candrawengi Nitivijaya, Maulidiah Oktaviana, Pratnya Paramitha Pratnya Paramitha O Pratnya Paramitha Oktaviana Probo Prasetya, Andyk Purhadi Purhadi Rina Wahyuningsih, Rina Rinda Nariswari Santi Wulan Purnami Setiawan Sinta Septi Pangastuti Soehardjoepri Soehardjoepri Suci Astutik Suhartono Suhartono Sulhan Sulhan Susi Tri Wahyuni Taufik Azmi Tiza Ayu Virania Ulfa Siti Nuraini Viera Wardhani Wahyuni Suryaningtyas, Wahyuni Wijaya, Elizabeth Meiliana Wirajaya Kusuma Wiwiek Setya Winahju Wiyli Yustanti Zainiyah Hilda Paramita