Nama Lengkap : Prof. Dr. Budi Nurani Ruchjana, MS.
E-mail: [email protected]
Bidang Keahlian : Matematika
Scopus Author ID : 25229331100
Prodi S2 Calon Mahasiswa: S2 Matematika FMIPA
Prodi S3 Calon Mahasiswa: S3 Matematika FMIPA
Judul Penelitian yang Ditawarkan:
MODEL SPATIO TEMPORAL DENGAN PENDEKATAN DATA MINING UNTUK KAJIAN FENOMENA IKLIM DI INDONESIA
Spatio Temporal Model with a Data Mining Approach for the Study of Climate Phenomena in Indonesia.
Abstrak:
Proposal Program Magister Doktor Sarjana Unggulan (PMDSU) 2021 ini diusulkan untuk menaungi aktivitas akademik yang dapat diikuti oleh calon mahasiswa program Fast-Track Magister Doktor Bidang matematika pada Fakultas Matematika dan Ilmu pengetahuan Alam Universitas Padjadjaran. Topik yang dipilih adalah Model Spatio Temporal dengan Pendekatan Data Mining untuk Kajian Fenomena Iklim di Indonesia. Topik ini merupakan materi untuk kajian disertasi yang akan diselesaikan dalam waktu 4 (empat) tahun, 2021-2024. Topik proposal difokuskan pada pengembangan model Spatio Temporal berbasis model time series Box-Jenkins (1976) yang dikembangkan menjadi model Generalized Space TIme Autoregressive (GSTAR) oleh Ruchjana (2002). Kajian model Spatio temoral secara teoretis maupun aplikasinya didukung dengan Pola Ilmiah Pokok (PIP), SDGs dan pilar riset Universitas Padjadjaran khususnya untuk kajian lingkungan berdasarkan fenomena iklim yang terjadi di Indonesia.
Pengembangan model Spatio Temporal untuk kajian fenomena iklim di Indonesia merupakan integrasi analisis data time series, analisis data spasial dan kombinasi keduanya berupa analisis spatio temporal berbasis big data atau data science. Pengembangan model juga disesuaikan dengan fenomena big data atau data science berupa data mining dalam pengamatan real time melalui pendekatan tiga tahap preprocessing-data mining-postprocessing, sehingga melibatkan Tim promotor dalam bidang Matematika-Statistika, dan Ilmu Komputer. Tim promotor juga merupakan kolaborasi antara para peneliti dari Departemen Matematika dan Departemen Ilmu Komputer FMIPA Unpad dengan Peneliti bidang Ilmu Komputer dari Albaha University, Saudi Arabia. Oleh karena itu, dalam penelitian ini akan dilakukan kajian teoretis dan aplikasi didukung dengan komputasi menggunakan perangkat lunak open source R atau Phyton, sehingga dapat diperoleh suatu model Spatio Temporal untuk peramalan atau forcasting fenomena iklim di Indonesia. Hasil yang diperoleh diharapkan dapat memberikan kontribusi bagi pengembangan ilmu berbasis analisis time series, analisis spasial dan analisis spatio temporal, serta secara aplikasi diperoleh suatu program berupa script terintegrasi dalam peramalan fenomena iklim dengan berbagai variabel seperti curah hujan, sea surface temperature, kelembaban, dan lain-lain untuk digunakan sebagai early warning bagi pengambil kebijakan. Hasil akhir dari penelitian ini berupa penelitian disertasi dan diharapkan dapat menghasilkan publikasi karya ilmiah mahasiswa program Doktor Matematika FMIPA Unpad pada jurnal internasional bereputasi terindeks Scopus atau Web of Science, sehingga dapat meningkatkan kualitas akademik mahasiswa dan lulusan Doktor Matematika maupun institusi di tingkat nasional maupun internasional, serta peningkatan kualitas kerja sama berupa joint supervision, joint publication dan joint conference.
Abstract:
The Proposal for the 2021 Excellence Undergraduate Doctoral Masters Program (PMDSU) is proposed to oversee academic activities that can be participated by prospective students of the Fast-Track Masters Doctoral Program in mathematics at the Faculty of Mathematics and Natural Sciences, Padjadjaran University. The topic chosen was the Spatio Temporal Model with a Data Mining Approach for the Study of Climate Phenomena in Indonesia.
This topic is material for a dissertation study which will be completed within 4 (four) years, 2021-2024. The topic of the proposal focused on the development of the Spatio Temporal model based on the Box-Jenkins time series model (1976) which was developed into a Generalized Space Time Autoregressive (GSTAR) model by Ruchjana (2002). The theoretical study of the Spatio-temporal model and its application is supported by the Principal Scientific Pattern (PIP), SDGs and the research pillars of Padjadjaran University, especially for environmental studies based on climate phenomena that occur in Indonesia.
The development of the Spatio Temporal model for the study of climate phenomena in Indonesia is an integration of time series data analysis, spatial data analysis and a combination of both in the form of big data or data science-based spatio-temporal analysis. Model development is also adapted to the big data or data science phenomenon in the form of data mining in real time observation through a three-stages preprocessing-data mining-post-processing approach, so that it involves the promoter team in the fields of Mathematics, Statistics and Computer Science.
The promotor team is also a collaboration between researchers from the Department of Mathematics and the Department of Computer Science, Faculty of Mathematics and Natural Sciences Unpad and Researchers in the field of Computer Science from Albaha University, Saudi Arabia. Therefore, in this research, theoretical studies and applications will be carried out supported by computation using open source R or Python software, so that a Spatio Temporal model can be obtained for forecasting or forcasting climate phenomena in Indonesia. The results obtained are expected to contribute to the development of science based on time series analysis, spatial analysis and spation temporal analysis, and by application, a program is obtained in the form of an integrated script in forecasting climate phenomena with various variables such as rainfall, sea surface temperature, humidity, and so on. Furthermore, the result can be used as an early warning for policy makers.
The final result of this research is a dissertation research and is expected to produce the publication of scientific papers of doctoral students of the Mathematics at Faculty of Mathematics and Natural Sciences Unpad in a reputable international journals indexed by Scopus or Web of Science, so that it can improve the academic quality of students and Mathematics Doctoral program, and institutions at national and international levels. as well as improving the quality of cooperation in the form of joint supervision, joint publication and joint conference.