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All Journal PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Desimal: Jurnal Matematika JTAM (Jurnal Teori dan Aplikasi Matematika) Mathvision : Jurnal Matematika GERVASI: Jurnal Pengabdian kepada Masyarakat Jurnal Tekno Kompak Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Jurnal Visi Pengabdian Kepada Masyarakat International Journal of Engagement and Empowerment (IJE2) FARABI: Jurnal Matematika dan Pendidikan Matematika Premium: Insurance Business Journal International Journal of Multidisciplinary Research and Literature (IJOMRAL) Journal of Computer Science and Informatics Engineering Jurnal Pengabdian Masyarakat Ilmu Komputer
Novika, Fanny
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Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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PELATIHAN PENCADANGAN DOKUMEN PENTING SECARA DIGITAL BAGI WARGA SUNGAI BAMBU BEKASI SEBAGAI ANTISIPASI BENCANA BANJIR Novika, Fanny; P, I Made Indra
GERVASI: Jurnal Pengabdian kepada Masyarakat Vol. 9 No. 1 (2025): GERVASI: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM IKIP PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/gervasi.v9i1.8604

Abstract

Desa Segara Makmur salah satu desa yang seringkali mengalami banjir saat curah hujan cukup tinggi terjadi di Jabodetabek. Salah satu upaya untuk meminimalkan dampak negatif banjir adalah dengan melakukan persiapan yang matang, termasuk mencadangkan dokumen penting. Kegiatan pengabdian masyarakat ini dilakukan dengan tujuan untuk meningkatkan kesiapsiagaan masyarakat dalam menghadapi bencana banjir dalam hal mengamankan dokumen penting. Pelaksanaan pengabdian kepada masyarakat ini adalah dengan metode Service Learning yang juga sebagai media pembelajaran kolaboratif bersama mahasiswa untuk belajar bersama masyarakat melalui pengalaman langsung. Hasil kegiatan menunjukkan peningkatan kesadaran warga akan pentingnya pencadangan dokumen dan kemampuan mereka dalam melakukan pencadangan dokumen secara digital. Secara keseluruhan sebanyak 65% peserta menjawab sangat puas terhadap pelatihan yang telah dilakukan dan 35% menjawab puas. Sementara itu, tidak ada peserta yang menjawab cukup puas, kurang puas dan tidak puas. Dapat disimpulkan, kegiatan ini menambah kesiapan warga untuk dapat menghadapi banjir melalui pencadangan dokumen secara digital.
Comparative Performance of IndoBERT and IndoLEM Baseline Models for Post-Disaster Health Information Extraction from Indonesian Online News Istiqomah, Nalar; Novika, Fanny
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1174

Abstract

Natural disasters often have significant impacts on public health, yet systematic monitoring of post-disaster diseases in Indonesia remains limited. This study compares the performance of two Named Entity Recognition (NER) models in extracting health impacts, affected locations, and disaster types from Indonesian-language online news articles. The first model is IndoBERT, fine-tuned using 1,137 manually validated disaster-related news articles. The second comprises baseline models from the IndoLEM benchmark, namely mBERT and XLM-RoBERTa, without domain-specific training. Evaluation results show that IndoBERT outperforms the baseline models, achieving 90.00% accuracy and an F1-score of 88.26%, compared to mBERT (72.93%) and XLM-R (76.44%). Further analysis of the extracted entities reveals spatial and temporal disease trends: floods in Java are consistently associated with diarrhea and skin diseases, while volcanic eruptions in eastern Indonesia are linked to respiratory infections and hypertension. These findings highlight the importance of selecting appropriate models to support data-driven public health monitoring systems in disaster-prone regions
The estimation of the hazard function of earthquakes in aceh province with likelihood approach Maulidi, Ikhsan; Novika, Fanny; Mahmudi, Mahmudi; Apriliani, Vina; Syazali, Muhamad
Desimal: Jurnal Matematika Vol. 7 No. 3 (2024): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v7i3.21489

Abstract

In this article, we propose a novel application of the single decrement method with a likelihood approach to estimate the hazard function of earthquake events in Aceh province. While this method has traditionally been used in actuarial sciences for mortality table estimation, its application in seismic hazard estimation represents a new perspective in the field of earthquake risk analysis. To enhance the accuracy of the model, we applied the Box-Cox transformation to normalize the data and used simple regression to formulate the hazard function. Our results demonstrate that a cubic equation provides a more accurate model compared to linear and quadratic equations, as evidenced by the lower Mean Square Error (MSE). This study offers a new approach to hazard rate estimation that surpasses conventional methods by providing more informative and interpretable results for earthquake risk assessment.
Sentiment Analysis Penyedia layanan Asuransi dari Media Sosial Twitter Istiqomah, Nalar; Novika, Fanny
Jurnal Tekno Kompak Vol 18, No 1 (2024): FEBRUARI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtk.v18i1.3465

Abstract

Abstrak− Tujuan dari penelitian ini adalah menerapkan analisis sentimen untuk mengevaluasi pandangan masyarakat terhadap penyedia layanan asuransi kesehatan, sehingga dapat memahami reputasi penyedia layanan asuransi. Penelitian ini menggunakan algoritme Naïve Bayes untuk mengidentifikasi sentimen pengguna Twitter terkait penyedia layanan asuransi kesehatan dan mengevaluasi akurasi hasilnya. Penelitian ini dilakukan untuk mendapatkan informasi sentimen masyarakat tentang perspektif penyedia layanan asuransi kesehatan melalui media sosial twitter. Pertumbuhan pengguna Twitter yang mencapai lebih dari 500 juta twit setiap hari memberikan potensi Big Data untuk mengevaluasi pandangan masyarakat terhadap asuransi kesehatan. Penelitian ini menggunakan metode penelitian deskriptif kualitatif dengan dukungan bahasa pemograman Python. Populasi penelitian ini mencakup semua twit yang diposting oleh pengguna di Indonesia. Kami menggunakan metode purposive sampling, yaitu pemilihan sampel berdasarkan kriteria tertentu yang sesuai dengan tujuan penelitian, seperti twit yang berhubungan dengan penyedia layanan asuransi kesehatan. Data yang digunakan adalah data primer, yaitu twit dari pengguna Twitter di Indonesia yang berkaitan dengan penyedia layanan asuransi kesehatan. Pengumpulan data dilakukan melalui web scraping dari aplikasi Tweet Harvest, dilanjutkan dengan proses labeling, dan kemudian data dipraproses melalui tahapan pembersihan, tokenisasi, penyaringan, dan stemming. Terakhir, algoritme Naïve Bayes digunakan untuk analisis sentimen. Dari proses pengambilan data, kami berhasil mengumpulkan 31.190 data, yang kemudian disaring menjadi 1.483 data yang hanya berupa hasil review. Pada tahap pelabelan, 889 twit mendapatkan label positif, sementara 594 twit mendapatkan label negatif. Didapatkan akurasi dari algoritme Naïve Bayes adalah 74.41%. Hasil ringkasan twit menggambarkan pandangan yang beragam terkait BPJS Kesehatan dan asuransi kesehatan swasta. Terdapat pandangan positif terhadap BPJS Kesehatan, termasuk premi yang terjangkau, cakupan penyakit kritis, dan pendaftaran tanpa medical check-up. Namun, ada kritik terhadap prosedur pengobatan yang dianggap rumit, kesulitan dalam menghentikan keanggotaan, dan perdebatan tentang prinsip gotong royong. Di sisi lain, asuransi kesehatan swasta mendapatkan pandangan positif karena prosedur yang lebih sederhana, antrian cepat, dan pilihan produk yang sesuai dengan penghasilan individu. Namun, terdapat juga pandangan negatif, termasuk gangguan telemarketing, kasus gagal bayar oleh penyedia asuransi, dan konsumen yang merasa tertipu ketika asuransi pendidikan beralih menjadi asuransi kesehatan tanpa persetujuan mereka.Kata Kunci: BPJS Kesehatan; Naïve Bayes; Penyedia layanan Asuransi; Sentiment Analysis; Twitter
Extracting Post‑Disaster Health Impact Information from News Reports Using Named Entity Recognition Istiqomah, Nalar; Novika, Fanny
Journal of INISTA Vol 7 No 2 (2025): May 2025
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v7i2.1814

Abstract

Natural disasters have a significant impact on public health, giving rise to various post-disaster illnesses. This study presents an automated information‑extraction framework based on Named Entity Recognition (NER), leveraging the IndoBERT model to identify disaster types, health impacts, and affected locations from online news reports. Data were gathered via web scraping from multiple reputable news portals and subsequently processed through tokenization, stop‑word removal, and lemmatization. Extracted entities were visualized via bar charts and word clouds to reveal disease patterns associated with each disaster type. Results indicate that floods have a significant public health impact, with skin diseases being the most prevalent, followed by diarrhea, fever, influenza, and Acute Respiratory Infections (ARIs). Volcanic eruptions are linked to health conditions such as ARI, hypertension, diarrhea, and influenza, whereas earthquakes show strong correlations with diarrhea, ARI, skin diseases, and fever. Droughts and landslides are closely associated with diarrheal outbreaks due to compromised sanitation resulting from limited access to clean water. Although less frequently reported, tsunamis also exhibit a notable association with cases of diarrhea. The proposed method achieves 90 % accuracy and an 88 % F1‑score. These findings confirm the effectiveness of our NER-based approach in detecting causal relationships between disasters and health outcomes, providing valuable insights for policymakers and healthcare professionals in designing targeted post-disaster mitigation and response strategies.
Comparasion Model Analysis Time of Earthquake Occurrence in Indonesia based on Hazard Rate with Single Decrement Method Novika, Fanny; Maulidi, Ikhsan; Marsanto, Budi; Amalina, Anvika Nur
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 1 (2022): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i1.5535

Abstract

The purpose of this studi is to find an expectations and variability as estimators of the risk of earthquakes occurring in each province in Indonesia. Indonesia is a country that prone to natural disasters, especially earthquakes and tsunamis. The earthquake disaster damage the buildings and casualties. The risk of loss from earthquakes can be transferred using insurance. Insurance companies certainly need an analysis to estimate the probability of an earthquake occurring at a certain location and time. Hazard rate has an important role in the prediction theory of the process of earthquakes. The hazard rate can be known by the single decrement method. After the hazard rate is known, the survival function and the distribution function of the cumulative distribution of earthquake data in Indonesia will be known to look for expectations and variability as estimators of the risk of earthquakes occurring in each province in Indonesia. The data used in this study is earthquake that happen in Indonesia categorized as destructive earthquake minimum 5 magnitude. We used the data to compare a hazard function using linear model, quadratic model, cubic model and exponential. First, we plot and then using each models find the standard error. The best model suggest for Indonesia prediction Time of Earthquake Occurrence using an exponential model.
Spatial Pattern Analysis and Spatial Regression of Geological Disaster Risk in Indonesia Novika, Fanny; Kusdani, Dedi
FARABI: Jurnal Matematika dan Pendidikan Matematika Vol 8 No 2 (2025): FARABI (In Press)
Publisher : Program Studi Pendidikan Matematika FKIP UNIVA Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47662/farabi.v8i2.1114

Abstract

Indonesia is a country with a high level of vulnerability to geological disasters such as earthquakes, landslides, and volcanic eruptions due to its position in the meeting zone of three active tectonic plates. This study aims to map the spatial pattern of geological disasters Local Indicators of Spatial Association (LISA) and analyze the effect of spatial variables on the number of victims using a spatial regression analysis approach. Data were obtained from BNPB and analyzed using the OLS method and three spatial regression models, namely the Spatial Autoregressive Model (SAR), Spatial Error Model (SEM), and General Spatial Model (GSM). The LISA results show that several provinces are included in the high-high and spatial outlier categories that are prone to disasters. Regression analysis shows that for earthquakes, the SEM model is the best model with a pseudo-R² of 0.888 and the lowest AIC. For landslides, the GSM model gives the best results (pseudo-R² = 0.7860 and AIC = 78.389), while for volcanic eruptions, the spatial model does not show significant spatial effects, so the OLS model is sufficient to represent the relationship between variables. The variable number of events proved to have the most significant influence on the number of victims across all types of disasters. This finding emphasizes the importance of a spatial approach in risk mapping and geological disaster mitigation planning in Indonesia.
Co-Authors Amalina, Anvika Nur Awaloeddin, Mulawarman Chalista, Bunga Fandayani, Enno Karina I Made Indra Irwandi, Muhammad Istiqomah, Nalar Japari Antony Karina, Enno Kusdani, Dedi Lie, Antonius Anton Mahmudi Mahmudi Marsanto, Budi Maulidi, Ikhsan Muhamad Syazali Nalar Istiqomah Namiera, Adinda Nike Septivani P, I Made Indra Rahmadhianty , Nadya Rosmayanti, Melinia Saptyarani, Amelia Suryamika, Putu Egawastu Vina Apriliani