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All Journal Jurnal Ilmiah Kursor Jurnal Sains Matematika dan Statistika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) JTIK (Jurnal Teknik Informatika Kaputama) JISA (Jurnal Informatika dan Sains) Abdimasku : Jurnal Pengabdian Masyarakat Madaniya Unnes Journal of Mathematics IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Jurnal Pengabdian Sosial Parameter: Jurnal Matematika, Statistika dan Terapannya IJCOSIN : Indonesian Journal of Community Service and Innovation
Aina Latifa Riyana Putri
Telkom University
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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EARLY DETECTION OF RAINFALL ANOMALIES USING LSTM AND ISOLATION FOREST Adhystira Raihannoeza Almadiva; Atika Ratna Dewi; Aina Latifa Riyana Putri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp3559-3574

Abstract

The uncertainty of daily rainfall patterns in Cilacap Regency with extreme variations makes it difficult to detect hydrological anomalies early using traditional methods. This study aims to obtain the most optimal LSTM parameters for rainfall prediction models, evaluate model performance using the Mean Squared Error (MSE) also Root Mean Squared Error (RMSE) metric, and predict rainfall anomalies for the next year using Isolation Forest. Daily BMKG data from January 2015 to December 2024 were processed through preprocessing stages, including missing data handling and time sequence creation. The Long Short Term Memory model was trained using regularization techniques to avoid overfitting, and the prediction results were analyzed using Isolation Forest to identify anomalies. The experiment showed that the best combination of hyperparameters was LSTM with 50 units and a tanh activation function, dropout 0.3, followed by a first dense layer of 50 units with ReLU activation and a single output layer. This configuration resulted in a validation MSE of 23.5247161 and RMSE 4.8502, this result identified five cases of anomalies that were validated for suitability based on rainfall data from BPBD. These results demonstrate the model's ability to reconstruct rainfall patterns and detect potential anomalies, so the system has potential to support early warning efforts for disaster mitigation and water resource management in Cilacap.
Optimalisasi AI secara Etis: Strategi Guru Meningkatkan Kualitas Karya Ilmiah untuk Menembus Jurnal Nasional Terakreditasi Sofia Debi Puspa; Joko Riyono; Christina Eni Pujiastuti; Dianing Novita Nurmala Putri; Aina Latifa Riyana Putri
Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Vol. 4, No. 2: October 2025
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.adipati.2025.v4i2.7910

Abstract

Penulisan karya ilmiah penting bagi guru untuk mendukung pengembangan ilmu dan peningkatan karir profesionalisme. Namun, guru sering mengalami kendala, seperti sulit menentukan topik, keterbatasan pemahaman struktur penulisan, serta keterbatasan penggunaan manajer referensi yang belum optimal. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk mengembangkan pengetahuan dan keterampilan guru dalam penulisan karya imiah serta meningkatkan literasi digital dalam pemanfaatan AI, seperti Elicit dan Research Rabbit, dengan tetap memperhatikan etika penulisan ilmiah. Pelatihan ini ditujukan bagi guru SMP di wilayah Tangerang dan Jakarta, dilaksanakan secara daring, dan diikuti oleh 82 peserta. Hasil evaluasi menunjukkan adanya peningkatan signifikan kemampuan peserta. Nilai rata-rata pre-test tercatat sebesar 46,48 dan meningkat menjadi 69,27 pada post-test. Uji t berpasangan menghasilkan p-value 0,000 kurang dari  0,05 yang menunjukkan adanya perbedaan signifikan antara kemampuan peserta sebelum dan sesudah mengikuti pelatihan. Secara kualitatif, 21,95% peserta menyatakan “sangat setuju” dan 68,29% “setuju” bahwa pelatihan ini bermanfaat dalam meningkatkan wawasan dan keterampilan menulis karya ilmiah.Kata kunci: artificial intelligence, etik, publikasi, teknologi
Co-Authors Adhystira Raihannoeza Almadiva Amalia, Raisha Atika Ratna Dewi Atika Ratnadewi Ayu, I Gusti De Bashiran, Himam Bayu Surarso Brian Nugraha Wiyono Christina Eni Pujiastuti Christina Eni Pujiastuti Christina Eni Pujiastuti Desty Mayang Pratiwi Dewanti, Anggun Dianing Novita Nurmala Putri Dody Prayitno Eni Pujiastuti, Christina Fayza Nayla Riyana Putri Gabriella F Pandiangan Gavrilla Claudia Harnoko, Sri Namira Putri Irwan Susanto Joko Riyono Joko Riyono Joko Riyono Kania, Putri Emas Kartika Dian Kurniasari Khoirun Niamah Khulika Malkan Mega Yuliani Ramme Mikhael Setia Budi Nurkaromah Dwidayati, Nurkaromah Prameswari, Mayesq Pujiastuti, Christina Eni Puspa, Sofia Debi Rizal Wahyu Pratama Setyaningsih, Destina Bekti Silaen, Ferdinan Siti Khomsah, Siti Sofia Debi Puspa Sofia Debi Puspa Supriyadi Supriyadi Supriyadi Supriyadi Supriyadi Supriyadi Supriyadi Syahid Nur Khomsyi Syahida, Shafa Tamara, Donna Nur Titi Udjiani SRRM Zahra, Indy Aurellia Az