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All Journal Belitung Nursing Journal Journals of Ners Community Journal of Telenursing (JOTING) Indonesian Journal of Global Health research Jurnal Minfo Polgan (JMP) Jurnal Keperawatan Malahayati International Journal of Nursing and Health Science Portal Riset dan Inovasi Sistem Perangkat Lunak
Chodidjah, Siti
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Computer Science & IT Decision Sciences, Operations Research & Management Education Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Public Health Social Sciences

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Diagnostic Accuracy of Delirium Assessment Tools Among Critically Ill Infant : A Systematic Review Rahmadhani, Dewi Astika; Ningsih, Risna; Setiawati, Atik; Chodidjah, Siti; Agustini, Nur; Huda, Mega Hasanul
Indonesian Journal of Global Health Research Vol 7 No 3 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i3.6214

Abstract

Delirium is an acute change in neurologic function that can potentially lead to longterm impacts on children’s cognitive development and the quality of life. Infants under 12 months are particularly vulnerable because their cognitive and language abilities are not fully developed. Therefore, healthcare professionals need to enhance their knowledge of delirium symptoms, child development stages, and how to identify it in this age group to better detection and management. This study aims to evaluate the diagnostic accuracy of delirium assessment tools, namely the Cornell Assessment of Pediatric Delirium (CAPD), the Preschool Confusion Assessment Method for the ICU (psCAM-ICU), and the Sophia Observation Withdrawal Symptoms Pediatric Delirium (SOSPD), in detecting delirium in critically ill infants. This systematic review follows the PRISMA 2020 guidelines and includes a literature search in PubMed, Scopus, ProQuest, ScienceDirect, and Taylor & Francis from 2013 to 2023. Inclusion criteria consist of observational studies involving infants aged 0-11 months in ICU settings that utilized CAPD, psCAM-ICU, or SOSPD for delirium detection. The quality of the studies was assessed using the JBI Critical Appraisal Checklist for Studies Reporting Diagnostic Test Accuracy. Result : The analysis indicates that the SOSPD tool has a sensitivity ranging from 76.9% to 96.8% and specificity between 92% and 96.4%. The CAPD shows sensitivity from 87% to 94.1% and specificity from 88% to 98%. The psCAM exhibits sensitivity from 75% to 95% and specificity from 81% to 91%. The results demonstrate variability in accuracy depending on the age group and clinical condition of the children. Based on the research findings, psCAM is recommended as the most effective tool for detecting delirium in the infant population due to its ease of use and high accuracy. Early detection of delirium is crucial for enhancing clinical management and improving outcomes in critically ill infants.
Perbandingan Metode Algoritma Decision Tree C4.5 Dan Naïve Bayes Untuk Memprediksi Penyakit Tiroid Safitri, Leli; Cahayani Murtiwiyati, Krista; Chodidjah, Siti; Indayanti, Deasy
Journals of Ners Community Vol 13 No 5 (2022): Jurnal of Ners Community
Publisher : Fakultas Ilmu Kesehatan Universitas Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55129/jnerscommunity.v13i5.2121

Abstract

Penyakit tiroid adalah kelenjar endokrin murni terbesar di tubuh manusia, terletak di leher bagian depan. Gangguan fungsi tiroid seringkali sulit dikenali karena gejalanya tidak spesifik, dan sering diabaikan karena gejala penyakit tiroid sangat mirip dengan banyak penyakit gaya hidup modern. pasien seringkali tidak menyadari ada masalah pada dirinya dan tidak memeriksakan diri ke dokter. Oleh karena itu, penelitian dibidang kesehatan dilakukan untuk pengobatan lebih dini, guna mencegah kematian akibat terlambatnya penanganan. Penelitian ini menggunakan metode klasifikasi data mining Algoritma Decision Tree C4.5 dan Naïve Bayes dengan tujuan agar algoritma terpilih merupakan algoritma yang menghasilkan nilai akurasi dan nilai Area Under Curve (AUC) yang lebih baik. Data penelitian menggunakan Thyroid Disease Dataset UCI (University of California, Irvine) Machine Learning Repository. Hasil pengujian menunjukkan bahwa akurasi lebih baik diperoleh dari Algoritma Decision Tree C4.5 sebesar 97,12% sedangkan nilai akurasi Algoritma Naïve Bayes sebesar 76,02%. Nilai Area Under Curve (AUC) pada kurva Receiver Operating Characteristic (ROC) menunjukkan Algoritma Decision Tree C4.5 memiliki nilai lebih tinggi dari Algoritma Naïve Bayes dengan hasil klasifikasi Good Classification.
Implementasi Metode Lexicon-Based dalam Analisis Sentimen Komunitas Line Roleplay atas Penghapusan Fitur Line Voom El Vanya, Rahmalia; Chodidjah, Siti; Deasy Indayanti
Portal Riset dan Inovasi Sistem Perangkat Lunak Vol. 3 No. 4 (2025): Artikel Penelitian
Publisher : SoraTekno Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59696/prinsip.v3i4.215

Abstract

Perkembangan teknologi komunikasi digital mendorong aplikasi pesan instan berfungsi tidak hanya sebagai media komunikasi, tetapi juga sebagai ruang interaksi sosial berbasis komunitas. Salah satu fitur yang dimanfaatkan dalam konteks tersebut adalah LINE VOOM, yang digunakan oleh komunitas roleplay untuk membangun identitas virtual, membagikan konten, dan menjalin interaksi sosial. Penghapusan fitur LINE VOOM pada tahun 2025 memicu beragam respons dari pengguna, khususnya komunitas roleplay. Penelitian ini bertujuan untuk menganalisis sentimen komunitas roleplay terhadap kebijakan penghapusan fitur tersebut menggunakan pendekatan lexicon-based dan algoritma Logistic Regression. Data penelitian diperoleh dari 200 responden melalui kuesioner daring. Proses penelitian meliputi tahap pre-processing teks, yang mencakup data cleaning, case folding, normalisasi, tokenisasi, stopword removal, dan stemming. Pelabelan sentimen dilakukan menggunakan kamus sentimen (lexicon), dilanjutkan dengan penyeimbangan kelas menggunakan metode undersampling serta ekstraksi fitur menggunakan metode Term Frequency–Inverse Document Frequency (TF-IDF). Evaluasi model dilakukan menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa sentimen negatif mendominasi dengan akurasi model sebesar 73%. Temuan ini menunjukkan bahwa penghapusan LINE VOOM berdampak negatif terhadap keterikatan komunitas pengguna.
Determinant factors of psychological well-being and parental resilience in parents of children with cancer: A systematic review Nurrohmah, Azizah; Chodidjah, Siti; Lestari, Ayu Widya; Huda, Mega Hasanul
Malahayati International Journal of Nursing and Health Science Vol. 8 No. 12 (2026): Volume 8 Number 12
Publisher : Program Studi Ilmu Keperawatan-fakultas Ilmu Kesehatan Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/minh.v8i12.1798

Abstract

Background: Childhood cancer remains a major global health concern, significantly impacting parents psychological well-being. A child’s cancer diagnosis often triggers emotional distress, anxiety, and long-term uncertainty for the family. Purpose: To identify the determinant factors of psychological well-being and parental resilience among parents of children with cancer. Method: Observational studies evaluating psychological well-being and resilience in parents of children with cancer were systematically searched in the databases PubMed, ScienceDirect, EBSCOhost, Sage Journals, and Scopus. Data were extracted independently by two reviewers. We included seven studies involving a total of 892 parents from various countries who have children with cancer. Results: Protective factors that were found to significantly enhance resilience and psychological well-being include spiritual well-being, social support, self-efficacy, and coping strategies. Conversely, psychological factors such as trauma, depression, anxiety, and general health status were significantly negatively correlated with both psychological well-being and resilience (p < 0.05). Conclusion: The reviewed studies consistently demonstrate that parental resilience and well-being are strongly influenced by spiritual well-being, social support, self-efficacy, and coping strategies. Negative psychological variables such as depression, anxiety, and trauma significantly contribute to the decline in psychological well-being and resilience.
Co-Authors Abraar, Arinda Adawiyah, Robiyatul Allenidekania Allenidekania Arnoldy, Vincentia Exandy Salvera Astuti Astuti Athallah, Muhammad Hanif Herdianto Cahayani Murtiwiyati, Krista Deasy Indayanti Deasy Indayanti El Vanya, Rahmalia Etty Rekawati Garis, Ariq Finkhan Imami Nur Rachmawati Lestari, Ayu Widya Mega Hasanul Huda Nani Nurhaeni Ningsih, Risna Novia Pratiwi, Novia Noviyanti, Mita Nur Agustini Nurrohmah, Azizah Rahmadhani, Dewi Astika Safitri, Leli sari, endang puspita Setiawati, Atik Sitinjak, Eva Perawaty