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Cahyadi, Tedy Agung
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Analisis Ambang Batas Curah Hujan Dengan Pendekatan Statistik Median di Daerah Rawan Longsor Samigaluh, Kulon Progo Marganiswati, Yudha Tintana; Maharani, Yohana Noradika; Cahyadi, Tedy Agung; Prasetya, Johan Danu; Prastistho, Widyawanto
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.v13i3.34962

Abstract

Landslides in tropical regions are often triggered by intense rainfall, causing significant impacts. This study assesses the feasibility of rainfall thresholds for landslide early warning in Kapanewon Samigaluh, Kulon Progo. The objectives include characterizing the rainfall regime, testing the relationship between rainfall and landslide events, evaluating spatial consistency with the landslide hazard map, and establishing and verifying operational thresholds. Landslide data from the BPBD and daily rainfall data from BMKG were processed by aligning the dates and performing quality checks, followed by quantitative analysis. The number of landslide events analysed was 197, with rainfall data collected from a single measurement station. Thresholds were set using the median approach for daily rainfall (CH0) and three-day accumulation (CH−2) from the 2014–2023 series. Verification was conducted on 213 days of the 2024 rainy season using Proportion Correct. Characterization shows a consistent monsoonal pattern with notable interannual variability. A positive tendency is observed between annual rainfall accumulation and landslide frequency. Spatially, around 93% of events occur in high-hazard zones. The median-based thresholds obtained are 31 mm for CH0 and 81 mm for CH−2. Operational verification results in PC values of 84.0% for CH0 and 83.6% for CH−2, indicating acceptable performance. Physically, the intensity of rainfall on event days effectively distinguishes landslide from nonlandslide days, while three-day rainfall accumulation increases risk through soil saturation. These findings support the implementation of locally calibrated thresholds for strengthening early warning, with a focus on monitoring during the rainy season. However, the potential for false alarms related to geological conditions and land-use variability may affect model accuracy. Furthermore, periodic recalibration of thresholds is necessary to address uncertainties resulting from changing hydrometeorological conditions and land-use dynamics.
Peramalan Harga Nikel Berbasis Machine Learning menggunakan Algoritma Gated Recurrent Unit (GRU) Erlangga, Robby; Ardian, Aldin; Suharyadi, Heru; Kodong, Frans Richard; Cahyadi, Tedy Agung
Jurnal Teknologi Pertambangan Vol. 11 No. 2 (2026): Januari 2026
Publisher : Universitas Pembangunan Nasional Veteran Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/jtp.v11i2.16120

Abstract

Nikel merupakan komoditas tambang yang penting dalam pembuatan baterai kendaraan listrik (electric Vehicle (EV)). Meningkatnya produksi EV dalam upaya mengurangi emisi karbon menyebabkan tingginya kebutuhan Nikel sebagai bahan baku baterai kendaraan listrik diprediksi akan meningkat. Seiring meningkatnya produksi EV untuk menekan emisi karbon, kebutuhan nikel sebagai bahan baku baterai diproyeksikan terus naik. Kenaikan ini secara teori mendorong tekanan naik pada harga, terutama ketika pertumbuhan permintaan lebih cepat daripada kemampuan pasokan untuk bertambah dalam jangka pendek. Karena itu, tren permintaan yang meningkat menjadi salah satu faktor utama yang membentuk tren harga nikel ke depan. Selanjutnya, harga Nikel memiliki dampak signifikan terhadap keputusan investasi tambang, perkembangan ekonomi perusahaan Nikel, serta negara yang bergantung pada sumber daya Nikel. Namun, terdapat ketidakpastian mengenai tren harga Nikel di masa depan, sehingga solusi untuk permasalahan ini menarik untuk dikaji lebih dalam. Penelitian ini bertujuan untuk mengetahui hasil peramalan harga nikel jangka pendek dengan menerapkan algoritma Gated Recurren Unit (GRU) yang merupakan bagian dari kecerdasan buatan (Artificial Intelligent, mengetahui akurasi peramalan harga nikel menggunakan algoritma GRU, serta menyajikan data peramalan harga informatif kepada pengguna (user). Hasil penelitian menunjukkan GRU sangat efektif dalam melakukan peramalan harga Nikel berdasarkan evaluasi kerja model menggunakan Mean Absolute Percentage Error (MAPE) sebesar 1,21%. 
PERBANDINGAN HASIL ANALISIS POLA ALIRAN DENGAN PERSAMAAN RANS DAN LES DALAM COMPUTATIONAL FLUID DYNAMICS (CFD): LITERATURE RIVIEW Thiansy, Elsy; Cahyadi, Tedy Agung; Haq, Shofa Rijalul
Indonesian Mining Journal Vol 28 No 2 (2025): Indonesian Mining Journal, October 2025
Publisher : Balai Besar Pengujian Mineral dan Batubara tekMIRA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30556/imj.Vol28.No2.2025.1664

Abstract

The settling pond functions to hold and settle suspended particles, especially Total Suspended Solid (TSS) in order to reduce the pollutant load. However, the effectiveness of settling ponds is greatly influenced by the flow characteristics and the concentration of tss carried. This research compares two numerical approaches in Computational Fluid Dynamics (CFD), namely Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES). Both of these methods are widely used in turbulent flow simulations, but have different approaches and levels of accuracy in representing turbulence structures. This study reviews various recent scientific publications that apply the rans and les equations in internal and external flow cases, including settling pond applications. The review results show that the RANS equation is suitable for large-scale engineering simulations with low computational requirements but is less accurate in capturing turbulence details. The les equation provides more accurate results in capturing turbulent flow patterns than the RANS model. However, tutoring models require greater computational resources, so they need to be considered for more complex applications. From this comparison it can be concluded that the selection of equations in a CFD is very dependent on the analysis objectives, limited computing resources, and the level of data detail required.
PERBANDINGAN HASIL ANALISIS POLA ALIRAN DENGAN PERSAMAAN RANS DAN LES DALAM COMPUTATIONAL FLUID DYNAMICS (CFD): LITERATURE RIVIEW Thiansy, Elsy; Cahyadi, Tedy Agung; Haq, Shofa Rijalul
Indonesian Mining Journal Vol 28 No 2 (2025): Indonesian Mining Journal, October 2025
Publisher : Balai Besar Pengujian Mineral dan Batubara tekMIRA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30556/imj.Vol28.No2.2025.1664

Abstract

The settling pond functions to hold and settle suspended particles, especially Total Suspended Solid (TSS) in order to reduce the pollutant load. However, the effectiveness of settling ponds is greatly influenced by the flow characteristics and the concentration of tss carried. This research compares two numerical approaches in Computational Fluid Dynamics (CFD), namely Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES). Both of these methods are widely used in turbulent flow simulations, but have different approaches and levels of accuracy in representing turbulence structures. This study reviews various recent scientific publications that apply the rans and les equations in internal and external flow cases, including settling pond applications. The review results show that the RANS equation is suitable for large-scale engineering simulations with low computational requirements but is less accurate in capturing turbulence details. The les equation provides more accurate results in capturing turbulent flow patterns than the RANS model. However, tutoring models require greater computational resources, so they need to be considered for more complex applications. From this comparison it can be concluded that the selection of equations in a CFD is very dependent on the analysis objectives, limited computing resources, and the level of data detail required.
Co-Authors A. Belo, Delia Ximenes Abdul Halim Pelu Achmad Sadikin Agung Yulianto Nugroho Agustian, Yusrian Aisyah Salma Aji Lambang Hidayah aldin ardian, aldin Alfianto, Danny Algifari, Arif Aminuyati Amrin, Dedy Andrawina Wina Angggian R., Shahensah Anand Anggoro, Hengky Ansori, Muhammad Iqbal Anton Sudiyanto Anton Sudiyanto Ardinanta, Desta Nugraha Arif Munandar Arrina Khanifa Astika Putri Roshinta Bagus Wiyono Bagus Wiyono Bambang Dwijo Pranowo Barlian Dwinagara Bimantoro, Adyaksa Bagas Butungan, Jeragustivia Dahono Haryanto Dedy Amrin Deka Citra Dinata Delia Ximenes A. Belo Divina Maria Marques Doni Firdaus Fadlil Dwi Januar Ariyanto Dwi Mayanti Mega Lesmana Dwi Poetranto Waloeyo Adji Dwi Yolanda Sumbung Dyah Nunki Yalesrie Eddy Winarno Eddy Winarno Eddy Winarno, Eddy Edy Nursanto Edy Nursanto Edy Nursanto Edy Nursanto Edy Nursanto Eman Widijanto Erlangga, Robby Erwedi Erwedi Erwedi, Erwedi Fadlil, Doni Firdaus Faizal Agung Riyadi Ficky Adi Kurniawan Firmansyah, Ilham Fitri Nauli Fitriani Fitriani Frans Richard Kodong Gabriel Ranteallo Gandar Mahojwala Genadi Toar Nainggolan Gunawan Nusanto Gunawan Nusanto, Gunawan Gunawan, Risal Habibah, Annisa Ummu Hadi Purwanto Halimah Tusak Diah Hana Trijayanti Haq, Shofa Rijalul Hartono Hartono Hartono Hartono Hartono Hartono Hartono Sihir Hasywir Thaib Siri Hasywir Thaib Siri Hasywir Thaib Siri hasywir thaib siri, hasywir thaib Hendriono Hengky Anggoro Herlina Jayadianti Herniti, Dwi Heru Suharyadi Ifa Aulia Chusna Ilham Firmansyah Imawati, Rika Indah Setyowati Indah Setyowati Indun Titisariwati Indun Titisariwati Indun Titisariwati Indun Titisariwati, Indun Inmarlinianto Inmarlinianto, Inmarlinianto Jeragustivia Butungan Jeremia Christopher Herbert Siregar kadek nando setiawan nando Karel Lutan Warda Ketut Gunawan Ketut Gunawan Khanifa, Arrina Kresno Kresno Kresno Kresno Kurniawan, Fitra Kusumayudha, Sari Bahagiarti Leka, Emil Salim Kahmi Lesmana, Dwi Mayanti Mega Lilik Eko Widodo Linggasari, Shenny M. Rahman Yulianto Marganiswati, Yudha Tintana Mariatul Kiptiah Marques, Divina Maria Masjon Parhusip Mendrofa, Yudha Chrisman Moh Ardiansyah Monica Warih Widi Krisanti Muhammad Arifin Nur Muhammad Fathurrahman Pitayandanu Muhammad Iqbal Ansori Muhammad Tri Aditya Muhammad Wildan Ilyasa Nainggolan, Genadi Toar Notosiswoyo, Sudarto Nugroho, Arif Rianto Budi Nur Ali Amri Nur Ali Amri Nur Ali Amri Nur Ali Amri, Nur Ali Nurkhamim Nurkhamim Nurkhamim Nurkhamim, Nurkhamim Pambayu, Aldio Kresna Pasa, Titis Ilham Permadi, Fajar Peter Eka Rosadi Peter Eka Rosadi, Peter Eka Prasetya, Johan Danu Prastistho, Widyawanto Prawira, Hadi Putranto, Fery Izzan R.Horman, Juanita Rahmat Aditya Ramadhana Adi Rusyada Rendy Fahlevi Resa Risal Pradita Reza Adhi Fajar Rika Ampuh Hadiguna Rika Ernawati Rika Ernawati Rika Ernawati Rika Ernawati Rika Ernawati Rika Ernawati Rika Imawati Risaldi Hidayat Riyadi, Achmad Riyadi, Faizal Agung Rusdi Darmawan S. Koesnaryo Sabrina Umi Khabibah Sari Bahagiarti Kusumayudha Sari Bahagiarti Kusumayudha satria fitrio SB, Waterman Septianto, Erwin Setiyawa, Meindra Shahensah Anand Angggian R. Shofa Rijalul Haq Sigit Bagus Prabowo Singgih Saptono, Singgih Siregar, Imerilda Parlina Siswahyudianto Soekamto, Untung Stephanus Maria Eduat Sudarto Notosiswoyo Sudaryanto Suharsono Suharsono Suyono Suyono Suyono Suyono Suyono Syafrianto, Syafrianto Syamsul Arifin Syari Rahma Yanti Syihab, Zuher Tasidjawa, Gabriela Elisabeth Thiansy, Elsy Totok Sulistyo Tri Aditya, Muhammad Ulfa Nindya Kesuma Warsito utami, Hasrin citra Vega Vergiagara Vinansius Jimmy Jati Waterman SB Waterman SB Waterman SB Waterman SB Waterman Sulistyana Bargawa Waterman Sulistyana Bargawa Waterman Sulistyana Bargawa Waterman Sulistyana Bargawa Waterman Sulistyana Bargawa, Waterman Sulistyana Wawong Dwi Ratminah Wawong Dwi Ratminah, Wawong Dwi Wenny Kartika Widijanto, Eman Widodo, Lilik Eko Widyawanto Prastistho Winda Winda Yohana Nodarika Maharani Yohana Noradika Maharani Yohanes Ary Prayoga Yulantoro, Marchell Yulfanzah Zuher Syihab