Article Per Year (5 Year)
p-Index From 2021 - 2026
4.71
P-Index
This Author published in this journals
All Journal E-Jurnal Matematika KONSELI: Jurnal Bimbingan dan Konseling (E-Journal) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sains Matematika dan Statistika MUST: Journal of Mathematics Education, Science and Technology Unisda Journal of Mathematics and Computer Science (UJMC) Jurnal Abadimas Adi Buana J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Wahana : Tridarma Perguruan Tinggi JAST : Jurnal Aplikasi Sains dan Teknologi KOMPUTIKA - Jurnal Sistem Komputer Mathvision : Jurnal Matematika EIGEN MATHEMATICS JOURNAL Jurnal Matematika UNAND Inferensi Variansi : Journal of Statistics and Its Application on Teaching and Research Jurnal Statistika dan Aplikasinya Jurnal Pengabdian kepada Masyarakat Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) MANGGALI Kanigara
Fitriani, Fenny
Universitas PGRI Adi Buana Surabaya
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology 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 Mathematics Nursing Physics Public Health Social Sciences Other

Published : 38 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 38 Documents
Search

 1   2   3   4 
PEMODELAN KASUS PREVALENSI BALITA STUNTING TAHUN 2021 DI PROVINSI NUSA TENGGARA TIMUR DENGAN GEOGRAPHICALLY WEIGHTED REGRESSION Ina, Sesilia; Pramesti, Wara; Fenny Fitriani
MathVisioN Vol 7 No 1 (2025): Maret 2025
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55719/mv.v7i1.1449

Abstract

disebabkan penyakit infeksi berulang dan kondisi malnutrisi kronis selama masa kanak-kanak. Dampak utama akibat stunting adalah adanya potensi memperlambat perkembangan otak pada anak dan dalam jangka panjang dapat muncul resiko penyakit kronis. Keadaan ini tentu diduga ada beberapa atau banyak faktor yang berpengaruh, diantaranya persentase balita pernah mendapat imunusasi dasar lengkap, persentase perempuan yang melahirkan dengan berat badan anak kurang dari 2500 gram, persentasi perempuan NTT yang pernah kawin di bawah usia 17 tahun, persentase bayi usia 0 – 23 bulan dengan pemberian ASI ekslusif, jumlah tenaga medis, persentase penduduk miskin dan rata-rata konsumsi protein. Prevalensi stunting pada setiap daerah di kabupaten/kota Provinsi Nusa Tenggara Timur (NTT) tentunya berbeda, maka untuk mengetahui faktor-faktor yang berpengaruh signifikan terhadap prevalensi stunting di setiap kabupaten/kota ini adalah dapat digunakan metode Geographically Weighted Regression (GWR). Hasil penelitian menunjukan bahwa faktor persentase penduduk miskin berpengaruh signifikan terhadap prevalensi stunting ditemukan di 14 kabupaten/kota yang ada di Provinsi NTT. Sehingga faktor kemiskinan ini merupakan faktor yang paling banyak mempengaruhi kejadian stunting pada kabupaten/kota di Provinsi NTT. Sedangkan untuk faktor rata-rata konsumsi protein merupakan faktor yang paling sedikit mempengaruhi prevalensi stunting, yaitu hanya berpengaruh signifikan pada dua kabupaten/kota saja.
Integrative Bioinformatics and Statistical Approaches for Identifying Prognostic Biomarkers and Therapeutic Targets in Breast Cancer Zulhan Widya Baskara; Anuraga, Gangga; Anurogo, Dito; Fitriani, Fenny; Rochmanto, Hani Brilianti; Baskara, Zulhan Widya
Eigen Mathematics Journal Vol 8 No 1 (2025): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i1.277

Abstract

Breast cancer is a leading cause of cancer-related mortality worldwide, necessitating the identification of reliable biomarkers for prognosis and targeted therapy. This study employed an integrative bioinformatics and statistical approach to analyze differentially expressed genes (DEGs) in breast cancer using datasets GSE70947 and GSE22820 from the gene expression omnibus (GEO). A protein-protein interaction (PPI) network was constructed to identify hub genes, followed by functional enrichment analysis to determine their biological significance. Survival analysis using the KMplot database revealed that CDC45, KIF2C, CCNB1, KIF4A, CENPE, CHEK1, KIF15, AURKB, NCAPG, and HJURP were significantly associated with poor prognosis. These genes were primarily enriched in cell cycle regulation, mitotic spindle organization, and DNA damage response, highlighting their role in tumor progression. Among them, CCNB1, CHEK1, and AURKB were strongly linked to cell cycle progression and checkpoint regulation, while KIF2C and CENPE played essential roles in mitotic division. High expression levels of these genes correlated with reduced overall survival, suggesting their potential as prognostic biomarkers and therapeutic targets in breast cancer.These discoveries help us better understand how breast cancer develops and point to potential targets for tailored treatments.
Peningkatan Literasi Bioinformatika bagi Siswa Sekolah Menengah melalui Pelatihan Implementasi Sains Data Anuraga, Gangga; Fitriani, Fenny; Adawiyah, Rabiatul; Utami, Diva Aprilia Trisha; Faramaysty, Laura Sekar
JAST : Jurnal Aplikasi Sains dan Teknologi Vol 9, No 1 (2025): EDISI JUNI 2025
Publisher : Universitas Tribhuwana Tunggadewi Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/jast.v9i1.7081

Abstract

Bioinformatics is an interdisciplinary field that integrates biology, statistics, and computer science to analyze large-scale biological data. In the context of secondary education, students' understanding of this concept is still minimal. This study aims to evaluate the effectiveness of a training on the Implementation of Data Science in Bioinformatics, organized by the Statistics Study Program at Universitas PGRI Adi Buana Surabaya as part of a community service activity. The training methodology used a hybrid approach combining offline and online sessions. Twelfth-grade science students from five partner high schools participated. The training materials covered the basics of statistics, an introduction to bioinformatics, and biological data analysis case studies. The training showed increased participants' conceptual understanding and interest in data science. Furthermore, active interaction between students and speakers demonstrated the success of the participatory approach in learning activities. This activity also created collaborative relationships between partner universities and schools, extending the educational impact to secondary education environments. This training demonstrates the importance of integrating bioinformatics in secondary education to prepare young people to face the challenges of data-driven science.ABSTRAK Bioinformatika merupakan bidang interdisipliner yang mengintegrasikan biologi, statistika, dan ilmu komputer untuk menganalisis data biologis dalam skala besar. Dalam konteks pendidikan menengah, pemahaman siswa terhadap konsep ini masih sangat terbatas. Penelitian ini bertujuan untuk mengevaluasi efektivitas pelatihan bertema Implementasi Sains Data pada Bidang Bioinformatika yang diselenggarakan oleh Program Studi Statistika Universitas PGRI Adi Buana Surabaya sebagai bagian dari kegiatan pengabdian kepada masyarakat. Metodologi pelatihan menggunakan pendekatan hybrid yang menggabungkan sesi luring dan daring. Siswa kelas XII jurusan IPA dari lima SMA mitra dilibatkan sebagai peserta. Materi pelatihan mencakup dasar-dasar statistika, pengenalan bioinformatika, serta studi kasus analisis data biologis. Hasil pelatihan menunjukkan adanya peningkatan pemahaman konseptual dan minat peserta terhadap bidang sains data. Selain itu, terjadi interaksi aktif antara siswa dan narasumber yang mencerminkan keberhasilan pendekatan partisipatif dalam kegiatan pembelajaran. Kegiatan ini juga menciptakan hubungan kolaboratif antara universitas dan sekolah mitra, memperluas dampak edukatif ke lingkungan pendidikan menengah. Pelatihan ini membuktikan pentingnya integrasi bioinformatika dalam pendidikan menengah untuk mempersiapkan generasi muda menghadapi tantangan ilmu pengetahuan berbasis data.
Integrating counseling with technology: An evaluation of the Bicarakan.id application through user review analysis with machine learning Al Azies, Harun; Rochmanto, Hani Brilianti; Pravesti, Cindy Asli; Fitriani, Fenny
KONSELI: Jurnal Bimbingan dan Konseling (E-Journal) Vol 11 No 2 (2024): KONSELI : Jurnal Bimbingan dan Konseling (E-journal)
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/kons.v11i2.24357

Abstract

Online counseling has transformed mental health services by offering a convenient and cost-effective alternative to traditional in-person therapy. This study investigates the role of technology in counseling by analyzing user reviews of the Bicarakan.id app from the Google Play Store. A machine learning approach was employed to identify critical patterns and themes within the reviews. Text pre-processing methods such as tokenization, stop-word removal, and TF-IDF vectorization were applied to a dataset of 125 user reviews. The Elbow method helped determine the optimal number of clusters, which was three. Clustering performance was assessed using the Silhouette score, with three clusters yielding the highest average score of 0.4939, indicating a moderate level of clustering effectiveness. Cluster 1 primarily contained positive reviews, emphasizing user satisfaction with the app's services. Cluster 2 included more specific feedback on users' experiences with counselors and app features. Cluster 3 focused on the app's accessibility and ease of use while raising concerns about data privacy and the lack of offline consultation options. The study underscores the significance of using user feedback to enhance and improve technology-driven mental health solutions.
SPATIAL MODELING OF SCHOOL DROPOUT RATES IN UNDERDEVELOPED AREAS OF PAPUA USING GEOGRAPHICALLY WEIGHTED REGRESSION Al Azies, Harun; Brilianti Rochmanto, Hani; Fitriani, Fenny
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6784

Abstract

This study examines the factors hypothesized to contribute to school dropout rates in disadvantaged regions of Papua Province and explores potential geographical influences. The primary aims are to derive parameter estimates and statistical tests for the model of underdeveloped regions in Papua using Geographically Weighted Regression (GWR) and to determine the factors influencing school dropout rates in these areas, providing a basis for governmental policy development to mitigate school dropout issues in disadvantaged regions. Findings reveal that the highest dropout rates occur at the junior high school level, with indications of spatial clustering in dropout cases due to heterogeneity among observation sites. This suggests that regions with elevated dropout rates, or conversely low rates, are likely to have neighboring areas with comparable patterns, necessitating the use of spatial regression modeling with a Fixed Gaussian Kernel function. GWR analysis resulted in two clusters based on significant variables, which include the student-teacher ratio at the junior high school level, the student-classroom ratio at the junior high school level, and the elementary school dropout rate (APTs).
Manajemen Data Sekolah SMK Sepuluh Nopember Sidoarjo dengan Menggunakan Excel Hapsery, Alfisayhrina; Fitriani, Fenny; E. P., Maria Hernita; Ardiansyah, Oky
Manggali Vol 2 No 2 (2022): Manggali
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/manggali.v2i2.2167

Abstract

Era digital memasuki industri 5.0 menuntuk seluruh masyarakat untuk mampu beradaptasi. SMK Sepuluh Nopember Sidoarjo juga gencar untuk mengikuti perkambangan digitalisasi, khusnya dalam manajemen data baik dalam penyimpanan data maupun penyajian data. Tujuan pengabdian dalam pelatihan ini untuk membantu Tenaga pendidik, Guru dan siswa SMK Sepulih Nopember Sidoarjo dalam manajemen data sekolah. Manajemen data dapat dilakukan dengan beberapa tools, antara lain dengan pivot table dalam ms. Excel. Pelatihan manajemen data dilakukan denan Teknik pemaparan materi, simulasi dan evaluasi. Hasil dari pengabdian ini diketahui bahwa materi yang disampaikan dapat diterima dengan baik, ditinjau dari hasil diagram saat simulasi data. Antusias peserta bertanya dan mensimulasikan juga merupakan tolok ukur keberhasilan dari program pelatihan ini.
Pengenalan Manipulasi Data dengan Menggunakan Bahasa Pemrograman R pada Guru SMK Sumber Ilmu Tulangan Fitriani, Fenny; Indrasetianingsih, Artanti; Pramesty, Maria Hernita Elvine; Amin, Mochammad Iqbal Nasrulloh Al
Manggali Vol 3 No 1 (2023): Manggali
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/manggali.v3i1.2411

Abstract

Data processing is one of the basics that must be mastered by researchers and people who work with data. One of the people who work with data is a teacher. The data owned by the teacher can be utilized by a teacher in carrying out the classroom action research process. However, the contents of the data that are owned may not necessarily be directly processed. So, it is necessary to have treatment carried out on data such as data manipulation. In the data manipulation process this can be done with the help of software R. Based on this, dedication is carried out in the form of an introduction to data manipulation given to teachers at SMK Sumber Ilmu Reinforcement by using software R. Activities After the activities are carried out, the teacher can better understand how the process correct data manipulation with the help of R software
ANALISIS SENTIMEN PENGGUNA TWITTER MENGENAI KOTAK KOSONG DI PILKADA INDONESIA TAHUN 2024 MENGGUNAKAN ALGORITMA LSTM Rosyadi, Achmad Chikham Nouriel; Muhammad Athoillah; Fenny Fitriani
Komputika : Jurnal Sistem Komputer Vol. 14 No. 2 (2025): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v14i2.16976

Abstract

Fenomena kotak kosong dalam Pilkada 2024 menjadi perbincangan ramai di Twitter, memunculkan pandangan pro dan kontra di masyarakat mengenai keberadaan calon tunggal yang dinilai berpotensi memengaruhi stabilitas politik di daerah. Diskusi publik di media sosial umumnya menggunakan bahasa informal, dialek bahasa daerah, serta tidak mengikuti kaidah baku, sehingga menyulitkan analisis manual dan berisiko menimbulkan bias. Maka dari itu, penelitian ini mengimplementasikan pendekatan deep learning dengan memanfaatkan model Long Short-Term Memory (LSTM) dan word embedding GloVe. Proses pelabelan dilakukan secara otomatis menggunakan Indonesia Sentiment Lexicon (INSET) untuk mengklasifikasikan sentimen masyarakat terhadap kebijakan kotak kosong berdasarkan data Twitter. Data penelitian terdiri dari 2.168 tweet yang diperoleh melalui teknik crawling, kemudian dievaluasi menggunakan metode 10-fold cross-validation. Analisis sentimen menghasilkan distribusi opini publik, yaitu 35,9% negatif, 32,8% positif, dan 31,3% netral. Hasil pengujian menunjukkan akurasi tertinggi sebesar 94,93% pada fold ke-6, dengan rata-rata akurasi keseluruhan mencapai 90,08%. Penelitian ini berkontribusi dalam pengembangan sistem analisis berbasis deep learning untuk pemantauan opini publik, serta menunjukkan potensi data media sosial sebagai sumber informasi strategis dalam memahami persepsi masyarakat terhadap fenomena politik.
Co-Authors Alfisyahrina Hapsery Aliffia Rahma Anandyani Amin, Mochammad Iqbal Nasrulloh Al Anandyani, Aliffia Rahma Ardiansyah, Oky Brilianti Rochmanto, Hani Cahyaningtias, Sari Canta, Himawan Widia Dini Krisnawati Alfiki Astutik Dito Anurogo, Dito E. P., Maria Hernita Eka Sudilowati Eka Susilowati Elisabeth Vianey Mali Elvira Mustikawati Putri Hermanto Emeliani, Anggi Eufrosiana Ga’a Bara Faramaysty, Laura Sekar Firli Azizah Gabriela Desi Ratna Aso Sore Gangga Anuraga Gangga Anuraga Gangga Anuraga Hani Brilianti Rochmanto Hapsery, Alfisayhrina Hariyanti Dewi Priyanto Harun Al Azies Heppy Reihana Kartika Sari Ian Yanuar Pratama Ina, Sesilia Indrasetianingsih, Artanti Intan Amelia Haryanto Kiki Laila Nirmala Marcella Gloria Leto Bele Muhammad Athoillah, Muhammad pramesti, wara Pramesty, Maria Hernita Elvine Prasdianitaningtiyas Junita Kusuma Pravesti, Cindy Asli Putri Amelia Divaio Rabiatul Adawiyah Rosyadi, Achmad Chikham Nouriel Siti Fatonah Utami, Diva Aprilia Trisha Wanda Nur Hamidah Wara Pramesti Wara Pramesti Wara Pramesti Windi Utami Wiranda, Natasha Bunga Yasmin Findiariska Zulhan Widya Baskara