Article Per Year (5 Year)
p-Index From 2021 - 2026
4.134
P-Index
This Author published in this journals
All Journal Indonesian Journal of Geography Jurnal Mahasiswa Jurusan Teknik Pengairan Jurnal Teknik Pengairan: Journal of Water Resources Engineering Rekayasa Sipil Jurnal Teknik Sipil U Karst Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Irigasi Civil and Environmental Science Journal (CIVENSE) Jurnal DISPROTEK International Journal Of Science, Technology & Management (IJSTM) International Journal of Engineering, Science and Information Technology Jurnal Teknologi dan Rekayasa Sumber Daya Air
Lily Montarcih Limantara
Civil Engineering Department, Faculty Of Engineering, Brawijaya University, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 78 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 78 Documents
Search

 4   5   6   7   8 
Estimasi Tinggi Curah Hujan dari Data Klimatologi Menggunakan Model Artificial Neural Network (ANN) di Jakarta Pusat, Provinsi DKI Jakarta Diando, Azamulail; Limantara, Lily Montarcih; Wahyuni, Sri
Jurnal Teknologi dan Rekayasa Sumber Daya Air Vol. 4 No. 1 (2024): Jurnal Teknologi dan Rekayasa Sumber Daya Air (JTRESDA)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtresda.2024.004.01.002

Abstract

Banyaknya data yang hilang maupun kurang akibat kerusakan alat pencatat, proses perbaikan, maupun kesalahan manusia, berpengaruh besar terhadap proses Analisa sumber daya air. Kebutuhan akan data curah hujan yang lengkap dan akurat, pada proses perencanaan suatu wilayah sangatlah penting. Studi ini diharapkan dapat mengatasi kemungkinan adanya kekurangan informasi mengenai data yang dibutuhkan dalam sebuah analisis sumber daya air. Dengan menggunakan data curah hujan dan klimatologi berupa suhu udara, kelembapan, lama penyinaran matahari, dan kecepatan angin, dapat diperkirakan estimasi tinggi curah hujan yang turun di daerah dalam kurun waktu tertentu dengan menggunakan metode permodelan jaringan syaraf tiruan. Pada studi ini ditemukan nilai validasi terbaik pada proses kalibrasi dengan rentang 29 tahun, dengan epoch 1500, didapatkan nilai Nash-Sutcliffe Efficiency (NSE) = 0,81, Root Mean Square Error (RMSE) = 66,12, dan Koefisien Korelasi (R) = 0,9, sedangkan nilai validasi terbaik pada proses verifikasi dengan rentang 1 tahun, epoch 1000, didapatkan nilai Nash-Sutcliffe Efficiency (NSE) = 0,83, Root Mean Square Error (RMSE) = 57,81, dan Koefisien Korelasi (R) = 0.98.
Performance Evaluation of Machine Learning and Deep Learning for Rainfall Forecasting Soebroto, Arief Andy; Limantara, Lily Montarcih; Mahmudy, Wayan Firdaus; Sholichin, Moh.; Hidayat, Nurul; Kharisma, Agi Putra
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1179

Abstract

Climate change is a significant challenge for both humans and the environment, with its impacts increasingly felt across various regions of the world. The most evident consequence is the alteration of extreme weather patterns, which often lead to destructive and life-threatening natural disasters. Among these, extreme rainfall was the most damaging factor, frequently triggering floods. However, the increasing occurrence of related events outlined the urgent need for developing more accurate rainfall forecasting systems as a strategic measure for disaster risk reduction. This research adopted daily rainfall data from Samarinda City, collected between 2004 and 2012, to conduct prediction using both machine and deep learning methods. The implementation of machine learning methods, such as Support Vector Regression (SVR), enabled the model to learn from historical data and uncover complex patterns, resulting in accurate forecasts and improved adaptability to climate variability. Meanwhile, deep learning models, including Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM), enhanced prediction performance by capturing more intricate and abstract data relationships. Performance evaluations conducted using Mean Absolute Error (MAE) and Mean Squared Error (MSE) showed that deep learning outperformed machine learning in accuracy. The LSTM model achieved the best performance, with loss values of 0.0482 and 0.0527 for MSE and MAE, respectively. The advantage of deep learning lies in its ability to build more complex models for handling non-linear problems and to learn data representations at various levels of abstraction, which has led to more accurate results. Furthermore, LSTM surpassed RNN by effectively overcoming the vanishing gradient issue, allowing for more stable and efficient training that led to superior predictive performance.
Economic Feasibility Study Of The HIPAM Clean Water Network System, Genting Village, Merjosari Village, Lowokwaru District, Malang City Fandianto, Erno; Montarcih, Lily; Yuliani, Emma
International Journal of Science, Technology & Management Vol. 4 No. 1 (2023): January 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i1.740

Abstract

The need for clean water for the community is urgently needed, therefore the HIPPAM (Drinking Water Users Association) was formed which is a legal forum according to government regulations and regulations to manage the supply of clean water to the community. There were many obstacles that occurred during operation, one of which was the regional regulation of East Java Province which required HIPPAM to pay groundwater withdrawal tax which ultimately affected the increase in the price of clean water. One area that was realized from the existence of this regulation was Genting Village, Merjosari Subdistrict, Lowokwaru District, Malang City. Given these problems, the purpose of this study is to analyze the economic feasibility of determining the price of clean water in the area. The results of this study show economic feasibility based on bank interest of 9%, Benefit Cost Ratio = 2.44, Net Present Value = Rp. 16,069,451,606, Internal Rate of Return = 13.99%, payback period = 13 years, and sensitivity analysis with IDR prices. 1,000/m3 and a 25% increase every 4 years following inflation.
From Water Allocation to Food Security: Irrigation System Optimization through Deterministic Dynamic Programming in the Gembolo Irrigation Area Mokhamad Rusdha Maulana; Lily Montarcih Limantara; itojo Tri Juwono
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.12630

Abstract

Inefficient irrigation water distribution remains a critical barrier to achieving optimal crop productivity and ensuring food security in rural Indonesia. This study focuses on the Gembolo Irrigation Area, Mojokerto Regency, by applying Deterministic Dynamic Programming (DDP) to optimize water allocation under a Rice–Rice–Secondary Crop (RTTG) rotation. The comprehensive integration of hydrological, climatological, and cropping data was employed to construct a DDP model that synchronizes irrigation supply with crop water demand across nine irrigation structures (G1–G9). The optimization results reveal significant improvements: irrigated area expanded by 254 ha, cropping intensity increased from 277 to 300%, and farmers’ net income rose by IDR 5.3 billion compared to the existing allocation scheme. These findings demonstrate the capacity of DDP to enhance water-use efficiency while strengthening the resilience and sustainability of rural agricultural systems. The study highlights the importance of data-driven optimization as a decision-support framework for advancing integrated irrigation management and rural development.
Estimasi Tinggi Curah Hujan dari Data Klimatologi Menggunakan Model Artificial Neural Network (ANN) di Kabupaten Badung Bali Selatan Juma'a, Muhammad Walidi; Limantara, Lily Montarcih; Wahyuni, Sri
Jurnal Teknologi dan Rekayasa Sumber Daya Air Vol. 1 No. 1 (2021): Jurnal Teknologi dan Rekayasa Sumber Daya Air (JTRESDA)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtresda.2021.001.01.11

Abstract

Abstract: The objective of this research was to establish the results of calibration relationship between rainfall and climatology, mathematical equations and the results of the validation Artificial Neural Network (ANN) method from 30 years of climatological data and historical rainfall. The population was taken from the Meteorology, Climatology and Geophysics Agency at Ngurah Rai Station, Badung Regency, Bali. Climatic data and rainfall data were analyzed the quality of the data, namely the consistency test, stationary test, trend absence test and persistence test. The output of the analysis calculation of rainfall using the (ANN) method of observational data based on the calibration found that in the distribution of data for 25 years epoch 2000 with an indicator value of NSE = 0.83 (Good) and R = 0.91 (Very strong) showed the best results, while for verification on 1 year epoch 2000 data with an indicator value of  NSE = 0.48 (fulfilled) and R = 0.90 (very strong). The comparison of rainfall data with observational data is almost close if the Nash-Sutchliffe Efficiency (NSE) and Correlation Coefficient (R) values meet the existing categories. Abstrak : Tujuan penelitian ini untuk mengetahui hasil kalibrasi hubungan curah hujan dengan klimatologi, persamaan matematis dan hasil validasi metode Artificial Neural Network (ANN) dari 30 tahun data klimatologi dan curah hujan historis. Populasi diambil dari Badan Meteorologi Klimatologi dan Geofisika di Stasiun Ngurah Rai, Kabupaten Badung, Bali. Data iklim dan data curah hujan dilakukan analisis kualitas data, yaitu dengan Uji Konsistensi, Uji Stasioner, Uji Ketidakadaan trend dan Uji Persistensi. Hasil analisis perhitungan curah hujan dengan metode (ANN) terhadap data pengamatan berdasarkan kalibrasi didapatkan bahwa di pembagian data 25 tahun epoch 2000 dengan nilai indikator NSE = 0,83 (Baik) dan R = 0,91 (Sangat kuat) menunjukan hasil terbaik, sedangkan untuk verifikasi pada data 1 tahun epoch 2000 dengan nilai indikator NSE = 0,48 (Memenuhi) dan R = 0,90 (Sangat kuat). Perbandingan data curah hujan dengan data pengamatan hampir mendekati jika nilai Efisiensi Nash-Sutchliffe (ENS) dan Koefisien Korelasi (R) memenuhi kategori yang ada.
Evaluasi Rasionalisasi Pos Hujan dengan Metode Stepwise dan Standar WMO pada DAS Telomoyo Kabupaten Kebumen Nugrahanto, Bagus Aji; Limantara, Lily Montarcih; Wahyuni, Sri
Jurnal Teknologi dan Rekayasa Sumber Daya Air Vol. 2 No. 2 (2022): Jurnal Teknologi dan Rekayasa Sumber Daya Air (JTRESDA)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtresda.2022.002.02.16

Abstract

The Telomoyo watershed is included in the category of mountainous areas and tropical plains. In term of fulfilling the need for adequate water infrastructure, good quality rain data is needed. The methods that can be used are stepwise rationalization and evaluation based on WMO guidance. The stepwise method is chosen in order to check the correlation between the rainfall data and debit data based on multi-correlated statistics and the WMO guidance are used to complete the minimum requirement of the number of rainfall stations in a watershed according to geographical aspects. It was found that the Telomoyo watershed has met the minimum WMO standards, namely with 9 rainfall stations, but it is still considered irrational due to the uneven distribution of rainfall station as seen from the range of influence in each rainfall station. Meanwhile, from the stepwise analysis, it is found that the combination of 4 rainfall stations is considered rational and meets WMO standards. However, this study only provides recommendations for the most statistically rational rainfall station combinations. It is also permissible to move or choose another rainfall station that has more strategic locations so that the influence area of the rainfall stations is more evenly distributed. DAS Telomoyo memiliki luas sebesar 553,22 km2 dan termasuk dalam kategori daerah pegunungan serta dataran tropis. Dalam pemenuhan akan kebutuhan infrastruktur bangunan air yang memadai, diperlukan data hujan dengan kualitas baik yang salah satu caranya yaitu melihat keterkaitan data hujan yang ada dengan data debit yang didapatkan di lapangan. Metode yang dapat digunakan adalah rasionalisasi metode stepwise dan evaluasi berdasarkan standar WMO. Metode stepwise dipilih untuk mengecek korelasi data hujan dengan data debit berdasarkan statistika multi korelasi dan standar WMO digunakan untuk melengkapi ketentuan minimum dari jumlah pos hujan suatu DAS menurut aspek geografi. Didapatkan bahwa DAS Telomoyo sudah memenuhi standar minimum WMO yaitu dengan 9 stasiun curah hujan serta 2 AWLR, namun hal ini masih dirasa belum rasional karena persebaran pos hujan yang kurang merata yang menurut luas pengaruh area setiap stasiun curah huan. Sedangkan dari analisis stepwise diperoleh bahwa gabungan 4 pos hujan sudah rasional serta memenuhi standar WMO. Namun studi ini hanya memberikan rekomendasi kombinasi pos hujan yang paling rasional secara statistik. Diperbolehkan juga melakukan pemindahan atau pemilihan pos lain yang memiliki lokasi lebih strategis sehingga luas pengaruh pos hujan lebih merata lagi.
Rationalization Study of Rainfall Network Density Using The Kagan-Rodda Method in Sub Watershed of Bango Azhari, Zeinnia Alya; Limantara, Lily Montarcih; Fidari, Jadfan Sidqi
Jurnal Teknologi dan Rekayasa Sumber Daya Air Vol. 2 No. 2 (2022): Jurnal Teknologi dan Rekayasa Sumber Daya Air (JTRESDA)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtresda.2022.002.02.20

Abstract

Management of water resources in watershed determined by avaibility of accurate rainfall data. The study of rationalization rainfall recorded density result the suggestion of amount and placement of rainfall recorded in watershed. The study was manage in Watershed of Bango with total area 246,4 km2 using Kagan-Rodda method and WMO Standard. The analysis of rainfall recorded using WMO Standard, 100-250 km2/rainfall recorded shown that none of the existing rainfall recorded in Bango Sub-Watershed are qualified. The result of Kagan-Rodda analysis giving recommendation the precise amount of rainfall recorded in Bango Sub-Watershed is Blimbing as point of reference station and form another rainfall recorded, C station. The coverage area of Blimbing is 133,74  km2 and C Station is 112,61 km2.
Analisis Debit Banjir Rancangan dengan Metode HSS Nakayasu, HSS ITB-1, dan HSS Limantara pada DAS Manikin di Kabupaten Kupang Damayanti, Alvine Cinta; Limantara, Lily Montarcih; Haribowo, Riyanto
Jurnal Teknologi dan Rekayasa Sumber Daya Air Vol. 2 No. 2 (2022): Jurnal Teknologi dan Rekayasa Sumber Daya Air (JTRESDA)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtresda.2022.002.02.25

Abstract

East Nusa Tenggara Province is a dry area where the rain season is relatively short and the rainfall intensity is low. This causes the production of food crops can not be maximized, even crop failure. The limited water resources in East Nusa Tenggara Province can be optimized by doing construction the Manikin Dam. In water resources planning, realistic flood discharge is needed by using the Synthetic Unit Hidrograph Method. The purpose of this research is to analyze the design flood discharge using the Methods of Synthetic Unit Hidrograph Nakayasu, ITB-1, and Limantara in Manikin Watershed of Kupang Regency. The calculation of the design flood discharge is carried out after obtaining the design rainfall value by using Normal, Log Normal, Gumbel, and Log Pearson Type III distribution methods. The results obtained are tested for suitability and the design rainfall value that passed can be use in the calculation of the design flood discharge. The results showed that the design flood discharge from the calculation of Nakayasu SUH method is 1597,16 m3/sec, that the design flood discharge from the calculation of ITB-1 SUH method is 965,64 m3/sec, and that the design flood discharge from the calculation of Limantara SUH method is 401,32 m3/sec. Based on the results, the value of the calculation of Nakayasu SUH method is the most suitable method and the closest to the conditions in the Manikin watershed.Provinsi Nusa Tenggara Timur merupakan daerah kering dimana musim basah (hujan) relatif pendek dan intensitas curah hujan yang kecil. Hal ini menyebabkan terjadinya produksi tanaman pangan tidak dapat maksimal, bahkan gagal panen. Terbatasnya sumber daya air di Propinsi Nusa Tenggara Timur dapat dioptimalkan dengan melakukan pembangunan Bendungan Manikin. Pada perencanaan bidang sumber daya air, dibutuhkan data debit banjir yang realistis dengan menggunakan Metode Hidrograf Satuan Sintetis. Penelitian bertujuan untuk menganalisis debit banjir rancangan dengan menggunakan ketiga metode Hidrograf Satuan Sintetis yaitu HSS Nakayasu, ITB-1, dan Limantara pada DAS Manikin di Kabupaten Kupang. Perhitungan debit banjir rancangan dilakukan setelah mendapat nilai hujan rancangan dengan menggunakan metode distribusi Normal, Log Normal, Gumbel, dan Log Pearson Type III. Hasil yang diperoleh diuji kembali kesesuaiannya dan nilai hujan rancangan yang lolos digunakan dalam perhitungan debit banjir Damayanti, A. C. et al., Jurnal Teknologi dan Rekayasa Sumber Daya Air Vol. 0 No. 0 (2021) p. 0-0 2 rancangan. Hasil penelitian menunjukkan bahwa nilai debit banjir rancangan perhitungan metode HSS Nakayasu sebesar 1597,16 m3 /det, debit banjir rancangan perhitungan metode HSS ITB-1 sebesar 965,64 m3 /det, dan debit banjir rancangan perhitungan metode HSS Limantara sebesar 401,32 m3 /det. Berdasarkan hasil analisis, nilai dari perhitungan metode HSS Nakayasu merupakan metode yang sesuai dan paling mendekati dengan kondisi di DAS Manikin.
Co-Authors A.A. Ketut Agung Cahyawan W Achmad Hariyadi Adiputra, Dhimas Satibi Agi Putra Kharisma, Agi Putra Agung Rahmadi Agus Priombodo Agustina Pagatiku Alamsyah, Muhammad Bayu Ambarwati, Arum Nurwidya Aniek Masrevaniah Arfiyanti, Anandini Fatma Arief Andy Soebroto Arif Rahmad Darmawan Ariston Samosir Azhari, Zeinnia Alya Azwar Annas Kunaifi Chandrasasi, Dian Damayanti, Alvine Cinta Dian Chandrasasi Dian Sisinggih Diando, Azamulail Djunaedi Djunaedi Donny Harisuseno Dwi Priyantoro Edison Hukom Eka Agus Subiyantoro Emma Yuliani Endang Purwati RN Ery Suhartanto Ery Suhartanto Ery Suhartanto Fandianto, Erno Fathia, Ayasha Fauziyah, Fauziyah Februanto, Aaron Jeremy Ferina, Marisa Ayu Hana Arum Rossy Tamaya Haris Djafar, Haris Harisuseno, Donny Harri Pranowo Ikrar Hanggara, Ikrar Ilham, Rendy Khoirul Indra Kusuma Sari Islamiyanto, Yudho Putra itojo Tri Juwono Iwan Nursyriwan Jadfan Sidqi Fidari Jamhari Jamhari Juma'a, Muhammad Walidi Juni, Riska Wulan Kharistanto, Robertus Tegar Kurnia Lalu Sigar Canggih Ranesa, Lalu Sigar Canggih Lenny Febriana Ideawati, Lenny Febriana Linda Prasetyorini Lucky Dyah Ekorini M. Bisri Mahendra, Hardiman Maulida Hayati Megantara, Anggit Gilang Mochammad Ibrahim Moh. Sholichin Moh. Sholichin Mohammad Bisri Mokhamad Rusdha Maulana Muhamad Rodhita Muhammad Bisri Muhammad Ilham nalurita, sari Nuf'a, Hilma Nugrahanto, Bagus Aji Nurdiyanto Nurdiyanto, Nurdiyanto nurfitriani, Alvina nurfitriani, Alvina Nurul Hidayat Pitojo Tri Juwono Pramasela, Pramasela Putra, Whima Regianto Qomarul Huda, Qomarul Rachma, Siti Talitha Rahmah Dara Lufira Ramadian, Bagas ramdhani, fitroh Respatiningrum, Amalia Wara Rini Wahyu Sayekti Rini, Firda Agustiya Rispiningtati Rispiningtati Riwin Andono Riyanto Haribowo Rony Rudson Rossy Tamaya, Hana Arum Runi Asmaranto Safira Anisah Haromain Safira Anisah Haromain Salimah, Ghaida Nurul Salsabila, Nadia Semuel J. Ch. Ahab, Semuel J. Ch. Shihab, Muhammad Qurais Sri Wahyuni Sri Wahyuni Sri Wahyuni Suhardjono Suhardjono Sulianto Sulianto Suwanto Marsudi Tae Lake, Geovani Valerian Maria Tri Budi Prayogo Tri Budi Prayogo, Tri Budi Triwidianto, Heru Tyas Daru, Tyas Ussy Andawayanti Very Dermawan Wahyuni, Sri Wahyuni, Sri Wayan Firdaus Mahmudy Whima Regianto Putra Widandi Soetopo Yanuar Wicaksono, R. Fajar Yudha Mediawan Yumna Atika