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All Journal Communications in Science and Technology Jurnal Informatika Universitas Pamulang INTECOMS: Journal of Information Technology and Computer Science JSiI (Jurnal Sistem Informasi) Indonesian Physical Review Building of Informatics, Technology and Science Infotekmesin Piston: Journal of Technical Engineering Journal of Innovation and Future Technology (IFTECH) Jurnal Sistem Komputer & Kecerdasan Buatan Buletin LOUPE (Laporan Umum Penelitian) Journal of Applied Sciences and Advanced Technology Jurnal Pengendalian Pencemaran Lingkungan (JPPL) Jurnal Teknologi Informatika dan Komputer Akrab Juara : Jurnal Ilmu-ilmu Sosial Jurnal Mesin Nusantara Jurnal Pengabdian kepada Masyarakat Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia International Journal of Engagement and Empowerment (IJE2) JURNAL ILMIAH GLOBAL EDUCATION Journal Of Sustainable Research In Management Of Agroindustry (SURIMI) ACROPORA: Jurnal Ilmu Kelautan dan Perikanan Papua JAMAIKA: Jurnal Abdi Masyarakat JURNAL AGROINDUSTRI HALAL Abdi Jurnal Publikasi Jurnal Teknologi Pangan dan Industri Perkebunan OKTAL : Jurnal Ilmu Komputer dan Sains Jurnal Ilmiah Multidisiplin Indonesia MULTIPLE: Journal of Global and Multidisciplinary Acta Solum Food and Agro-industry (FAGI) Journal Jurnal Ilmu Komputer
Murni Handayani
Universitas Pamulang, Banten, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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ANALISIS SISTEM DETEKSI DINI FRAUD PADA TRANSAKSI PERBANKAN MENGGUNAKAN LONG SHORT-TERM MEMORY (LSTM) DAN TRANSFORMER Abdullah, Arken; Waskita, Arya Adhyaksa; Handayani, Murni
INTECOMS: Journal of Information Technology and Computer Science Vol. 9 No. 1 (2026): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/83yrz474

Abstract

The development of digital banking services in electronic payment channels has led to a significant increase in transaction volumes, accompanied by higher fraud risk. Fraud patterns are dynamic and temporal, making detection based solely on individual transactions ineffective. This study aims to develop an early fraud detection system using a cluster-aware sequential deep learning approach. Transaction data are processed through data cleansing, behavioral feature extraction, and customer clustering based on transaction characteristics. Long Short-Term Memory (LSTM) is employed to learn temporal transaction patterns, while Transformer is used to capture global context and nominal transaction deviations. Both models are integrated through a dynamic ensemble approach with adaptive thresholds for each cluster. Model evaluation is conducted in a supervised manner using PR-AUC as the primary metric, supported by ROC-AUC, Precision, Recall, and F1-Score. The results demonstrate that the cluster-based ensemble approach improves detection stability, reduces false positives, and adapts effectively to differences in customer behavior. Experimental results show that models trained without oversampling provide more stable precision–recall performance on datasets where fraud manifests as extreme behavioral outliers, while SMOTE is used as a comparative scenario.  Keywords: Fraud Detection, Deep Learning, LSTM, Transformer, Bank
ANALISIS PREDIKTIF UNTUK MENINGKATKAN RETENSI MAHASISWA MENGGUNAKAN METODE RECURRENT NEURAL NETWORK DAN SUPPORT VECTOR MACHINE Siti Cici Carliah; Tukiyat Tukiyat; Murni Handayani
Journal of Innovation And Future Technology Vol. 8 No. 1 (2026): Vol 8 No 1 (Februari 2026): Journal of Innovation and Future Technology (IFTECH
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v8i1.4382

Abstract

Student retention is a critical indicator in evaluating the quality of higher education institutions. High dropout rates pose significant challenges, including at Al-Khairiyah University in Cilegon, Banten. This study develops a predictive model for student retention using two machine learning approaches: Recurrent Neural Network (RNN) and Support Vector Machine (SVM), while identifying the most influential factors. The dataset comprises 3371 records from 2021-2024, including academic variables (GPA, semester grades 1-8, attendance) and non-academic variables (organizational activity, competition achievements, parental income, admission pathway, and study system). Data was split into 80% training and 20% testing sets. Results show that the RNN model demonstrates superior performance with 93.5% accuracy, 99.7% precision, 89.3% recall, 94.2% F1-score, and 0.967 AUC, while SVM achieved 85.5% accuracy, 89.8% precision, 85.3% recall, 87.5% F1-score, and 0.912 AUC. Feature importance analysis reveals that Total GPA and first-semester grades (IPS.1) are the dominant factors influencing student retention, while non-academic factors have relatively small contributions. This research provides practical contributions through an Early Warning System framework that can be implemented by universities to detect at-risk students early, enabling proactive academic interventions.
Chatbot dengan RAG untuk Sistem FAQ Pondok Pesantren menggunakan Model Retriever dan Generator: Chatbot dengan RAG untuk Sistem FAQ Pondok Pesantren menggunakan Model Retriever dan Generator Surya, Surya Ariwibowo; Heryandi Suradiradja, Kahfi; Handayani, Murni
Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) Vol. 9 No. 2 (2026): Volume IX - Nomor 2 - Februari 2026
Publisher : Teknik Informatika, Sistem Informasi dan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/siskom-kb.v9i2.890

Abstract

Pesatnya perkembangan teknologi informasi mendorong lembaga pendidikan, termasuk pondok pesantren, untuk menyediakan akses informasi yang lebih efisien. Saat ini, penyampaian informasi di pondok pesantren masih dilakukan secara manual, sehingga memakan waktu dan tenaga karena harus menjawab pertanyaan yang berulang dari wali santri. Penelitian ini mengembangkan chatbot FAQ berbahasa Indonesia menggunakan pendekatan Retrieval-Augmented Generation (RAG) yang menggabungkan model retriever dan generator untuk menghasilkan jawaban yang relevan dan alami. Model retriever yang digunakan meliputi SBERT, DPR, dan E5, sedangkan model generator terdiri dari IndoBART, IDT5, dan IndoGPT. Data dikumpulkan melalui observasi, wawancara, dan studi literatur. Sistem dirancang menggunakan pencocokan semantik berbasis vektor dan decoding autoregresif untuk menghasilkan jawaban. Evaluasi performa dilakukan dengan metrik Hit@1, BLEU, dan BERTScore. Berdasarkan Hasil penelitian menunjukkan bahwa kombinasi SBERT + IndoBART mencapai akurasi tertinggi sebesar 96%, diikuti SBERT + IdT5 sebesar 95%. Model E5 mencatat skor CSAT tertinggi sebesar 70% dan respon tercepat 0.066 detik, sementara RoBERTa memperoleh skor CSAT terendah 39%, sehingga kombinasi SBERT + IndoBART cocok diterapkan dalam chatbot FAQ PPS. Imam Syafi’i.
SOSIALISASI TEKNOLOGI MODIFIKASI CUACA UNTUK PENINGKATAN LITERASI SAINS ATMOSFER BAGI SISWA SMA IT BAITUL ILMI BEKASI Tukiyat; Murni Handayani; Uliyatunisa
JAMAIKA: JURNAL ABDI MASYARAKAT Vol 6 No 3 (2025): OKTOBER
Publisher : Universitas Pamulang

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

Abstract

Kegiatan Pengabdian kepada Masyarakat (PKM) Universitas Pamulang dilaksanakan di SMA IT Baitul Ilmi Bekasi dengan tujuan meningkatkan literasi sains atmosfer melalui sosialisasi teknologi modifikasi cuaca (TMC). Literasi sains atmosfer di kalangan pelajar masih tergolong rendah, padahal pemahaman terhadap dinamika atmosfer penting dalam menghadapi perubahan iklim dan bencana hidrometeorologi. Kegiatan dilaksanakan dalam tiga sesi, yaitu pengenalan konsep atmosfer, pemutaran video edukatif dan diskusi kelompok, serta evaluasi melalui pre-test dan post-test. Hasil kegiatan menunjukkan peningkatan signifikan pada pemahaman siswa, dengan tingkat kepuasan rata-rata mencapai 83,7% dan 98% peserta menyatakan kegiatan bermanfaat. Penilaian kualitas materi, metode, dan penyampaian narasumber berada pada kategori sangat baik, meskipun aspek interaktivitas dan antusiasme masih perlu ditingkatkan. Secara umum, kegiatan ini efektif, edukatif, dan kontekstual, serta berhasil meningkatkan motivasi dan kesadaran lingkungan siswa. Kegiatan ini berkontribusi terhadap pelaksanaan Tridharma Perguruan Tinggi melalui luaran berupa laporan PKM dan publikasi artikel ilmiah. Kata kunci: literasi sains atmosfer; sosialisasi; modifikasi cuaca; pengabdian masyarakat; siswa SMA
Perbandingan Proses Mineralisasi Karbon dan Nitrogen serta Humifikasi Pada Sistem Pertanian yang Berbeda di Tanah Andisol: Comparison of Carbon and Nitrogen Mineralization Processes and Humification in Different Agricultural Systems in Andisol Soil Hidayanto, Fajar; Purnamasari, Retno Tri; Utami, Sari Widya; Handayani, Murni
Acta Solum Vol. 3 No. 3 (2025): Juli 2025
Publisher : Department of Soil, Faculty of Agriculture, Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/actasolum.v3i3.3128

Abstract

The organic farming system has become the choice of most farmers in Indonesia because it has a major impact on agricultural quality and soil fertility. Vegetable farming in Magelang and Semarang Regencies is cultivated on andisol soil which has a relatively high soil fertility level, but farmers still use organic fertilizers to increase the organic matter content of the soil. The organic farming system applies 10 tons ha-1 of cow manure, 20 liters ha-1 of liquid fertilizer, and the return of plant residues at each planting season. The conventional farming system with high organic matter applies 7 tons ha-1 of cow manure, 50 kg ha-1 of urea, 50 kg ha-1 of NPK fertilizer, 15 liters ha-1 of liquid fertilizer, while the conventional farming system with low organic matter applies 3 tons ha-1 of chicken manure, 50 kg ha-1 of ZA fertilizer, 50 kg ha-1 of KCl fertilizer, and 50 kg ha-1 of NPK fertilizer. Observation variables include pH NaF, C-organic, N-total, C/N ratio, humic acid, fulvic acid and humification rate. Data were analyzed for variety and if different, the method of the smallest significant difference test was continued. The results of the study showed that the organic farming system was more effective in increasing carbon and nitrogen in the soil and accelerating humification, so that nutrients were available more quickly. However, the deeper the soil layer, the mineralization and humification processes will decrease because they are greatly influenced by the availability of organic matter.
Co-Authors Abdullah, Arken Abu Khalid Rivai Agus Santoso Ahmad Gunawan Wibisono Al Habib, Irsyad Allam Ramzy Allam Ramzy Anggai, Sajarwo Any Kurniawati, Any Ari Kristiningsih Arrozi , Ubed Sonai Fahruddin Arsita Nur Rizkia Putri Astuti, Wijayanti Dwi Aza Fauziana, Noer Choirunnisa Firdaus Ivana Da, Oh Wen Darmawan, Rizki Ahmad Dawam Agung Pribadi Destiny, Keysi Devain Dewanto, Hizkia Alpha Dwi, Sadina Sahitya Dwityaningsih, Rosita Evila Purwanti Sri Rahayu, Theresia Fadillah Fajar Hidayanto, Fajar Feni Aryanti Fernandez, Nikolas Krisma Hadi Fitri Khoerunnisa Giyanto Gunawarman Hartanto Heryandi Suradiradja, Kahfi Hesti Rahayuningsih Hidayat, Dahlan Hizam, Fadli Iasya, Yurin Karunia Apsha Albaina Ipung Saputra Irnanda, Istifhamy Iwan Setiawan Jatmoko Awali Joko Setia Pribadi Jon Affi, Jon Kanim Kristiningsih, Ari Kurnia, Akhmad Rinaldy Kushendarsyah Saptaji Latifatul Khusna Lutfi Syafirullah Mahendra, Brillian Ardy Makhsun Makhsun Makhsun Mardiyana Mardiyana Mardiyana Mardiyana Maulana, Romdon Mila Prametha, Novika Moh. Triyana Abbas Mohammad Nurhilal Mohammad Rayhan Afdillah Muhamad Sibli Muji Mulyani Mustofa, Rizki musyafa, ahmad Nabila, Najwa Natasya Arifah Natasya Arifah Nur Rohmat Nuraini Sitepu Nuraini Sitepu Nurhayati, Mita Nurlinda Ayu Triwuri Oto Prasadi putri, raekhanrahmah Putri, Restiani Alia Raekhan Rahmah Putri Rafli Rafli Rafli Rafli Ragaventrand, Ramses Maur Reno Saeprani Retno Tri Purnamasari, Retno Tri Rifqi Fakhri Yogi Syafruddin Rizki Agustian Rosita Dwityaningsih Rosita, Rosita Dwityaningsih Saefuloh, Iman Salma Maulikhatun Zulfa Santika, Ariel Sari Widya Utami Sari Widya Utami Satrio Herbirowo, Satrio Siti Cici Carliah Siti Khoirunnisa Slamet Raharjo Slamet Raharjo Sudarno Sudarno Sumardiono, Arif Surya, Surya Ariwibowo Syadilla Ega Maharani Taswanda Taryo Taswanda Taryo Tukiyat Tukiyat Tukiyat Tukiyat Tukiyat, Tukiyat Ulikaryani Uliyatunisa Uliyatunisa, Uliyatunisa Waskita, Arya Adhyaksa Widuri Indana Saleha Widuri Indana Saleha Witriansyah, Khoeruddin Wittriansyah, Khoeruddin Yessi Permana Yuli Yetri Yunita Triana, Yunita Yunus Yunus Zain, Rafi Mahmud Zeni Ulma