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Peningkatan Kemampuan Manajemen Dalam Pengelolaan Elektronik Komplain Layanan Laboratorium Universitas Nurul Jadid Rahman, M. Fadhilur; Syafiih, M; Maulana Rahman, Zidan Abdallah; Mawardi, Imam; Romadhani, Ahmad; Rahman, Taufiqur
GLOBAL ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2021): Mei 2021, GLOBAL ABDIMAS
Publisher : Unit Publikasi Ilmiah Perkumpulan Intelektual Madani Indonesia

Laboratorium Komputer Universitas Nurul Jadidi menjadi tanggung jawab penuh Fakultas Teknik, pemanfaatan layanan laboratorium bagi mahasiswa teknik dan diluar Fakultas Teknik yang membutuhkan praktikum komputer. Penggunaan laboratorium diatur sesuai jadwal roster kuliah yang telah ditetapkan diawal perkuliahan pada setiap semesternya, sedangkan penggunaan ekstra akan disesuaikan diluar jadwal kuliah. Permasalahan yang terjadi adalah manajemen akan sulit menentukan jadwal tepat pagi pengguna laboratorium. Solusinya perlu adanya aplikasi yang mengatur penggunaaan serta kuluhan dari mahasiswa dan dosen, aplikasi tersebut akan mengakomodir semua kebutuhan dan keluhan yang ada di laboratorium komputer Fakultas Teknik. Agar manajemen paham menggunakan aplikasi perlu adanya pelatihan tujuannya agar mudah memahami penggunaan aplikasi e-komplain. Metode yang digunakan adalah Longitudinal Method merupakan metode untuk menentukan dan mengukur data secara berulang untuk satu atau beberapa variable. Hasilnya adalah aplikasi e-komplain yang sudah siap digunakan oleh Fakultas Teknik Universitas Nurul Jadid.

Rainfall Prediction Using Attention-Based LSTM Architecture Romadhani, Ahmad; Santoso, Irwan Budi; Crysdian, Cahyo
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8727

This study addresses the challenge of accurately predicting rainfall in regions with complex climate dynamics, such as Malang Regency, East Java. It evaluates the performance of a Long Short-Term Memory (LSTM) model enhanced with the Bahdanau Attention Mechanism, comparing it with a Standard LSTM model in forecasting daily rainfall based on historical weather parameters including average temperature, relative humidity, sunshine duration, and wind speed. Using daily data from BMKG covering 2000 to 2023, both models underwent a structured machine learning process including data preprocessing, feature selection, model training, and evaluation. The Attention-Based LSTM consistently outperformed the Standard LSTM, particularly in handling rainfall anomalies, achieving an MSE of 0.00800 and RMSE of 0.08948, compared to 0.00817 and 0.09039 respectively for the Standard LSTM. These results demonstrate that integrating Bahdanau Attention improves the model’s focus on relevant temporal features, enhancing prediction accuracy and robustness. The architecture consisting of two LSTM cells combined with the attention mechanism effectively captures complex sequential patterns that the standard model tends to overlook. This research highlights the potential of attention mechanisms in time series weather prediction, contributing to more reliable early warning systems, adaptive agricultural strategies, and disaster risk reduction frameworks. Future work could explore hybrid models or incorporate additional weather features to further improve performance and generalization.

RAMADAN: Rancang Bangun Sistem Pengelolaan Berbasis Android Wisma Dosen di Universitas Nurul Jadid Sya'roni, Wahab; Romadhani, Ahmad; Purwanto, Edi; Rusdianto, Moh.
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 2, No 3 (2021): Pengembangan Teknologi dan Kesehatan di Lembaga Keagamaan
Publisher : Universitas Nurul Jadid

Fungsi utama wisma dosen Universitas Nurul Jadid yaitu sebagai tempat menginap dosen yang dari luar kota yang sedang melakukan aktifitas mengajar. Disamping itu wisma dosen Universitas Nurul Jadid juga digunakan sebagai ruang menginap tamu yang berkepentingan dengan Universitas seperti seminar dan tamu penting lainya. Keterbatasan ruangan pada wisma dosen mengakibatkan sering terjadi benturan jadwal menginap antara dosen fakultas satu dengan fakultas lainya. Hal tersebut diperparah dengan belum adanya pembukuan yang bagus dari pihak pengelola wisma dosen Universitas, sehingga pengelola wisma dosen kesulitan dalam melaporkan pemakaian wisma dosen Universitas Nurul Jadid. Melihat dari persoalan tersebut peneliti membuat Aplikasi Pengelolaan Peminjaman Ruang Berbasis Android, dengan adanya aplikasi dosen dapat melihat dan memesan ruang dosen tanpa harus dating langsung ke wisma, disi lain pihak pengelola dapat dengan mudah melaporkan pemakaian ruang wisma dosen dengan mudah dan cepat. Berdasarkan hasil uji dengan menggunakan metode black box aplikasi pengelolaan ruang wisma dosen berbasis android ini layak digunakan dengan tingkat kecocokan pengguna sebesar 88%.

PENGARUH PROFITABILITAS, UKURAN PERUSAHAAN DAN KEBIJAKAN DIVIDEN TERHADAP NILAI PERUSAHAAN Romadhani, Ahmad; Saifi, Muhammad; Nuzula, Nila Firdausi
Profit: Jurnal Adminsitrasi Bisnis Vol. 14 No. 2 (2020): Profit : Jurnal Administrasi Bisnis
Publisher : FIA UB

The purpose of this review is to find out the amounts of profit, company size, and dividend policy which can influence the companyâ€™s value. LQ45 which is listed in Indonesian Stock Exchange is in the year of 2015 â€“ 2018. This research is using Explanatory Research with quantitative approach. The sampling technique is using purposive sampling. Profitability is a financial method used to gauge companyâ€™s profit.Â Companyâ€™s profit that comes from sales and investment return, can influence the companyâ€™s size. The companyâ€™s scale is an important information, used by investor who wants to invest their wealth to the company. The magnitude of company can influence dividend return. Companyâ€™s profit can affect the size of company and dividend return. It can be reflected in the increasing of companyâ€™ value. The performance of company can be a parameter used by investor to do an investment or funding to the company.

PENGARUH COMPETITIVE ADVANTAGE, PROFITABILITAS DAN KEBIJAKAN DIVIDEN TERHADAP NILAI PERUSAHAAN (Studi pada perusahaan IDX LQ45 yang terdaftar di Bursa Efek Indonesia Tahun 2015-2020) Romadhani, Ahmad; Saifi, Muhammad; Nuzula, Nila Firdausi
Profit: Jurnal Adminsitrasi Bisnis Vol. 16 No. 2 (2022): Profit : Jurnal Administrasi Bisnis
Publisher : FIA UB

This study aims to analyze and explain the effect of competitive advantage (cost of capital, capital intensity, advertising expenses), profitability (ROA, ROE, NPM), dividend policy (DPR, DPS, Yield) on firm value (MBR, MBA, Tobin’s Q). The researcher uses explanatory research with a quantitative approach and the object of the research uses the company IDX LQ45 which is listed on the Indonesia Stock Exchange in 2015-2020. The total sample in this study was 4 companies from a population of 45 companies that met the sampling criteria and this study uses Partial Least Squares (PLS) as research data management. The results show that the effect of competitive advantage has a significant effect on profitability, profitability has no significant effect on firm value, competitive advantage has a significant effect on dividend policy, dividend policy has no significant effect on firm value and competitive advantage has a significant effect on firm value

Rainfall Prediction Using Attention-Based LSTM Architecture Romadhani, Ahmad; Santoso, Irwan Budi; Crysdian, Cahyo
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8727

This study addresses the challenge of accurately predicting rainfall in regions with complex climate dynamics, such as Malang Regency, East Java. It evaluates the performance of a Long Short-Term Memory (LSTM) model enhanced with the Bahdanau Attention Mechanism, comparing it with a Standard LSTM model in forecasting daily rainfall based on historical weather parameters including average temperature, relative humidity, sunshine duration, and wind speed. Using daily data from BMKG covering 2000 to 2023, both models underwent a structured machine learning process including data preprocessing, feature selection, model training, and evaluation. The Attention-Based LSTM consistently outperformed the Standard LSTM, particularly in handling rainfall anomalies, achieving an MSE of 0.00800 and RMSE of 0.08948, compared to 0.00817 and 0.09039 respectively for the Standard LSTM. These results demonstrate that integrating Bahdanau Attention improves the model’s focus on relevant temporal features, enhancing prediction accuracy and robustness. The architecture consisting of two LSTM cells combined with the attention mechanism effectively captures complex sequential patterns that the standard model tends to overlook. This research highlights the potential of attention mechanisms in time series weather prediction, contributing to more reliable early warning systems, adaptive agricultural strategies, and disaster risk reduction frameworks. Future work could explore hybrid models or incorporate additional weather features to further improve performance and generalization.

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