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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Sains dan Teknologi Majalah Ilmiah METHODA
Adi, Suko Prayitno
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health

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Design of drought early warning system based on standardized precipitation index prediction using hybrid ARIMA-MLP in Banten province Soekirno, Santoso; Ananda, Naufal; Wicaksana, Haryas Subyantara; Yulizar, David; Prabowo, Muhammad Agung; Adi, Suko Prayitno; Santoso, Bayu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1878-1887

Abstract

Drought Early Warning System (DEWS) is an effort to disseminate early warning information based on climate and hydrology aspects. The DEWS design uses ARIMA, MLP, and hybrid ARIMA-MLP models to predict drought based on SPI for 1, 3, and 6 months. Predictions were made using ERA5 monthly rainfall data from 1981-2022 corrected based on observation data on 9 grids of observation rain gauges in Banten Province. The design of the ARIMA model is determined by selecting the combination of p and q parameters with the lowest AIC value, while the MLP architecture is determined by referring to the study literature and by trial and error testing. ARIMA models and hybrid models are not able to follow actual data fluctuations and have high error values in both SPI1, SPI3, and SPI6, so they are not recommended in this study. The MLP model has the best prediction ability, namely in SPI6 prediction with NSE value reaching >0.5 and RMSE value.
TRANSFORMASI PUBLIKASI STMKG DIGITAL: PENINGKATKAN SUMBER DAYA MANUSIA UNGGUL DAN PERCEPATAN AKREDITASI INSTITUSI Sinambela, Marzuki; Hidayat, Nur; Adi, Suko Prayitno; Sulistya, Widada; Sudarisman, Maman; Riama, Nelly Florida
Majalah Ilmiah METHODA Vol. 13 No. 2 (2023): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Improving excellent human resources is an initiative that aims to develop and strengthen individual and collective potential within the BMKG (Meteorology, Climatology and Geophysics Agency) organization to make it a leading global player in the fields of meteorology, climatology, geophysics and instrumentation. Excellent human resources in higher education institutions have the potential to conduct quality research and produce quality scientific publications. In this action of change, the integration of the STMKG Digital publication service program, both updating the E-Journal and building the STMKG PRESS publishing media as a single digital-based and indexed account, has been successfully carried out and is the key to the realization of a comprehensive publication information system. The integration of publication services is aimed at improving efficiency and effectiveness in both indexing and digital documents. This transformation will encourage teams involved in this change action plan to collaborate more, effective communication, and writing literacy. The results of this change action are expected to be useful for STMKG's internal interests, namely to facilitate the accreditation preparation process, academic data collection, and the accreditation assessment simulation process. The benefits for BMKG are the implementation of the BMKG 2022-2024 strategic plan and the improvement of superior human resources towards 500 Doctorates and BMKG Global Player.
TRANSFORMASI PUBLIKASI STMKG DIGITAL: PENINGKATKAN SUMBER DAYA MANUSIA UNGGUL DAN PERCEPATAN AKREDITASI INSTITUSI Sinambela, Marzuki; Hidayat, Nur; Adi, Suko Prayitno; Sulistya, Widada; Sudarisman, Maman; Riama, Nelly Florida
Majalah Ilmiah METHODA Vol. 13 No. 2 (2023): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol13No2.pp207-216

Abstract

Improving excellent human resources is an initiative that aims to develop and strengthen individual and collective potential within the BMKG (Meteorology, Climatology and Geophysics Agency) organization to make it a leading global player in the fields of meteorology, climatology, geophysics and instrumentation. Excellent human resources in higher education institutions have the potential to conduct quality research and produce quality scientific publications. In this action of change, the integration of the STMKG Digital publication service program, both updating the E-Journal and building the STMKG PRESS publishing media as a single digital-based and indexed account, has been successfully carried out and is the key to the realization of a comprehensive publication information system. The integration of publication services is aimed at improving efficiency and effectiveness in both indexing and digital documents. This transformation will encourage teams involved in this change action plan to collaborate more, effective communication, and writing literacy. The results of this change action are expected to be useful for STMKG's internal interests, namely to facilitate the accreditation preparation process, academic data collection, and the accreditation assessment simulation process. The benefits for BMKG are the implementation of the BMKG 2022-2024 strategic plan and the improvement of superior human resources towards 500 Doctorates and BMKG Global Player.
IDENTIFIKASI RANGKAIAN GEMPA BUMI PENDAHULUAN (FORESHOCKS) DENGAN PENDEKATAN KORELASI SILANG SINYAL SEISMIK TEMPLATE (STUDI KASUS RANGKAIAN GEMPA BUMI KARO 2017) Akbar, Dzikrullah; Sianipar, Dimas Salomo Januarianto; Sipayung, Renhard; Adi, Suko Prayitno
JST (Jurnal Sains dan Teknologi) Vol. 6 No. 2 (2017)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (875.576 KB) | DOI: 10.23887/jstundiksha.v6i2.11800

Abstract

Penelitian ini berhasil membuktikan bahwa pendekatan korelasi silang sinyal seismik dapat digunakan untuk mendeteksi kejadian seismik menggunakan waveform dari jaringan BMKG (Badan Meteorologi Klimatologi dan Geofisika). Pendeteksian ini dilakukan untuk melengkapi kejadian gempa bumi yang belum tercatat pada katalog reguler BMKG karena berbagai keterbatasan. Adanya rangkaian kejadian gempa pendahuluan (foreshock sequence) sebelum kejadian gempa Karo M 5,6 tanggal 16 Januari 2017 berhasil teridentifikasi. Tujuan dari penelitian ini adalah melakukan identifikasi kejadian gempa bumi pendahuluan (foreshocks) dengan memanfaatkan data sinyal template gempa bumi M 3,9 yang sebelumnya dianggap sebagai satu-satunya foreshock dalam rangkaian kejadian ini. Penelitian ini berhasil mendeteksi 12 kejadian gempa pendahuluan (foreshocks) setelah diterapkan metode deteksi berbasis korelasi silang. Foreshock mulai terdeteksi pada tanggal 14 Januari 2017 atau dua hari sebelum gempa utama. Magnitudo gempa pendahuluan semakin meningkat secara sistematis sampai kejadian gempa pendahuluan terbesar. Penelitian ini berimplikasi pada manfaat penerapan metode deteksi berbasis waveform untuk mendukung pemahaman fisis sumber gempa dan prediksi gempa bumi di Indonesia.
Co-Authors Akbar, Dzikrullah Ananda, Naufal Marzuki, Sinambela Muhammad Agung Prabowo, Muhammad Agung Nur Hidayat Riama, Nelly Florida Santoso, Bayu Sianipar, Dimas Salomo Januarianto Sipayung, Renhard Soekirno, Santoso Sudarisman, Maman Wicaksana, Haryas Subyantara Widada Sulistya Yulizar, David