https://journal2.stikeskendal.ac.id/index.php/keperawatan/issue/feedJurnal Keperawatan2024-09-16T08:00:50+00:00Livana PHlivana.ph@gmail.comOpen Journal Systems<p><img 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" />Jurnal keperawatan (JK) merupakan bagian integral dari jurnal yang diterbitkan oleh LPPM STIKES Kendal. JK merupakan sarana pengembangan dan publikasi karya ilmiah bagi para peneliti, dosen dan praktisi keperawatan. JK menerbitkan artikel-artikel yang merupakan hasil penelitian, studi kasus, hasil studi literatur, konsep keilmuan, pengetahuan dan teknologi yang inovatif dan terbaharu dalam lingkup keperawatan yang berfokus pada (10) pilar keperawatan, : meliputi<em>keperawatan anak, keperawatan maternitas, keperawatan medikal-bedah, keperawatan kritis, keperawatan gawat darurat, keperawatan jiwa, keperawatan komunitas, keperawatan gerontik, keperawatan keluarga, dan kepemimpinan dan manajemen keperawatan.</em> JK diterbitkan pertama kali dengan ISSN versi cetak pada Volume 1 No 1 Maret 2009 dan ISSN versi online pada Volume 9 No 1 Maret 2017. JK awalnya terbit 2 kali dalam setahun yaitu bulan terbitan Maret dan September. JK mulai Desember 2018 terbit 4x dalam setahun, yaitu bulan terbitan Maret, Juni, September, dan Desember. Artikel yang terbit di JK telah melalui proses telaah sejawat yang memiliki keahlian yang relevan. </p>https://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2363Hubungan antara Tingkat Stres dengan Kinerja Perawat dalam Menangani Pasien Resiko Perilaku Kekerasan2024-09-03T19:06:54+00:00Laili Nur Hidayatilailinurhidayati@umy.ac.idHanief Ilma Mahardikahaniefilmam64@gmail.comAbdul Jaliljalila90@yahoo.com<p>Stres dapat dialami oleh perawat yang setiap hari bertemu dengan pasien. Perawat jiwa di tuntut professional dan dapat memberikan asuhan keperawatan yang baik sehingga mutu pelayanan rumah sakit dapat terjaga karena kinerja perawat jiwa mempunyai kualitas yang baik. Penelitian ini bertujuan untuk mengetahui hubungan antara tingkat stres dengan kinerja perawat dalam menangani pasien resiko perilaku kekerasan. Metode penelitian ini menggunakan desain kuantitatif cross-sectional. Responden penelitian sebanyak 110 perawat jiwa di Rumah Sakit Jiwa Dr.Soerojo Magelang. Penelitian menggunakan kuesioner The Work Stress Scale dengan nilai uji validitas 0,579-0,739 dan uji realibilitas 0,727. Kuesioner Kinerja Perawat dengan nilai uji validitas 0,312-0,632 dan nilai uji reliabilitas 0,774. Analisis bivariat menggunakan Uji korelasi Spearman. Hasil penelitian didapatkan nilai signifikan p-value = 0.000 (p<0.05), dapat diartikan bahwa kedua variabel terdapat hubungan dengan nilai korelasi sebesar 0.447 yang menunjukan arah positif dengan kekuatan korelasi sedang. Terdapat hubungan tingkat stres dengan kinerja perawat dengan arah hubungan negatif yaitu semakin tinggi stres kerja perawat maka kinerja perawat semakin kurang dalam menangani pasien risiko perilaku kekerasan.</p>2024-11-02T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/1608Pengaruh Penggunaan Early Warning System (EWS) terhadap Tingkat Patient Safety2023-09-04T00:29:47+00:00Suhaimi Fauzansuhaimi.fauzan@ners.untan.ac.idIkbal Fradiantolivana.ph@gmail.comYoga Pramanalivana.ph@gmail.comM. Ali Maulanalivana.ph@gmail.com<p>Pengembangan teknologi merupakan salah satu fenomena yang berkembang saat ini. Pengembangan aplikasi dalam dunia keperawatan merupakan salah satu tuntutan perkembangan zaman. EWS berbasis elektronik merupakan salah satu pengembangan yang dilakukan guna mengefektifkan waktu dalam pengisian. Pengembangan aplikasi tidak terlepas dengan proses evaluasi guna meningkatkan kualitas aplikasi tersebut. Penelitian ini bertujuan untuk menilai kepuasan dari penggunaan aplikasi pengembang tentang EWS terhadap tingkat patient safety goals. Metode : penelitian ini menggunakan pendekatan cross sectional dengan pengambilan sampel secara non-probability sampling. Uji statistik yang digunakan untuk pengambilan kesimpulan menggunakan uji spearman’s rho correlation. Hasil : rata-rata tingkat kepuasan perawat menggunakan aplikasi EWS oleh pengembang Untan adalah 53,4 ± 6,7, sementara rata-rata capaian patient safety goals sebesar 57,7 ± 5,4. Uji statistik menunjukkan nilai p-value sebesar 0,000 dengan r korelasi sebesar 0,950. Kesimpulan : penelitian ini menunjukkan bahwa terdapat hubungan kuat antara tingkat kepuasan penggunaan aplikasi terhadap patient safety goals.</p>2024-09-20T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2302Ventilator Associated Pneumonia dengan Faktor Determinan terkait Pemasangan Ventilator Mekanik2024-07-06T04:19:55+00:00Rini Usmansrirahmasari03@gmail.comMartalena Martalenalivana.ph@gmail.comNurhamidah Nurhamidahlivana.ph@gmail.comLisa Afrianilivana.ph@gmail.comUtami Ariyasralivana.ph@gmail.comSri Rahma Sarilivana.ph@gmail.com<p>Ruangan Intensive Care Unit merupakan unit perawatan intensif dan diidentifikasi sebagai target mutu pelayanan dan keselamatan pasien dirumah sakit. Pasien ICU didominasi menggunakan ventilator mekanik yang berdampak kejadian Ventilator Associated Pneumonia (VAP). Pencegahan infeksi nosokomial menjadi landasan salah satunya penerapan bundels VAP dalam perawatan untuk pencegahan VAP. Tujuan penelitian untuk mengetahui faktor determinan kejadian VAP pada pasien yang terpasang ventilator mekanik. Penelitian ini menggunakan desain observasional analitik dengan menggunakan teknik total sampling. Sampel penelitian semua subjek menggunaan ventilator mekanik di ICU yang memenuhi kriteria inklusi 54 orang. Pengumpulan data menggunakan kuesioner tervalidasi setelah dilakukan uji validitas dan uji reliabilitas menggunakan Cronbach’s Alpha (r = 0,694). Analisa data bivariat menggunakan uji Chi-Square dan analisa multivariat menggunakan uji Regresi Logistik Berganda. Hasil penelitian menunjukkan faktor paling dominan yang mempengaruhi kejadian VAP dengan pasien terpasang ventilator yaitu Glasgow Coma Scale (GCS) p < 0,05 OR= 2,596 95%CI (1,021-6,601) yang artinya GCS memberikan pengaruh sebesar 25,96 kali terhadap kejadian VAP dan penyakit gagal ginjal p < 0,05, OR= 1,182 95%CI (1,070-5,560) yang artinya penyakit gagal ginjal memberikan pengaruh sebesar 11,82 kali terhadap kejadian VAP. Simpulan penelitian menunjukkan penyakit komorbid seperti gagal ginjal adalah salah satu faktor determinan terjadinya VAP. Berdasarkan tindakan yang telah dilakukan oleh perawat di ruangan ICU dalam penatalaksanaan pencegahan VAP sudah dilaksanakan sesuai dengan skor GCS dan bundles VAP.</p>2024-11-02T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/3011Chat GPT 4.0 dan Chat GPT 3.5 dalam Menjawab Pertanyaan Medis2024-09-16T08:00:50+00:00Joko Tri Atmojojokotriatmojo1@gmail.comAmallia Wijiwinarsihlivana.ph@gmail.comIka Yuliantilivana.ph@gmail.comLivana PHlivana.ph@gmail.comAris Widiyantolivana.ph@gmail.com<p>Kecerdasan Buatan (AI) merupakan bidang ilmu komputer yang dikhususkan untuk memecahkan masalah kognitif yang umumnya terkait dengan kecerdasan manusia. Chat Generative Pre-Trained Transformer (Chat GPT) adalah model pemrosesan bahasa alami produk kecerdasan buatan yang dikembangkan oleh OpenAI. Chat GPT berpotensi membantu menjawab pertanyaan medis dengan tingkat kesesuaian yang akurat. Penelitian ini bertujuan untuk mengetahui perbandingan akurasi kecerdasan buatan Chat GPT-4 dan Chat GPT-3 dalam menjawab pertanyaan medis. Penelitian ini merupakan penelitian metaanalisis dan telaah sistematis dengan menggunakan diagram PRISMA. Pencarian studi primer melalui beberapa indexing database diantaranya: PubMed, Google Scholar dan BASE. Kata kunci yang digunakan untuk mempermudah pencarian artikel yaitu; “Chat GPT AND Medical Question”, atau “Chat GPT AND Accuracy”, atau “Chat GPT AND Medical Question AND Accuracy”. Kriteria inklusi penelitian ini adalah artikel yang terpublikasi menggunakan desain studi cross-sectional dari bulan Januari 2023-Agustus 2024. Analisis statistik yang digunakan pada penelitian ini menggunakan program metaanalisis RevMan 5.4.1 dengan pendekatan fixed effect dan Random effect serta menyajikan data funnel plot dan forest plot. Hasil penelitian menunjukan bahwa Chat GPT-4 memiliki tingkat akurasi yang lebih tinggi dalam menjawab pertanyaan medis. Tingkat akurasi Chat GPT-4 dalam menjawab pertanyaan medis menunjukan 3.07 kali lebih tinggi dibandingkan dengan Chat GPT-3 (OR: 3.07; 95%CI: 2.20-4.30; p<0.0001) dan signifikan secara statistik. Forest plot tersebut juga menunjukkan heterogenitas estimasi efek antar studi yang tinggi (I = 81%). Funnel plot menunjukkan terdapat bias publikasi yang cenderung melebih-lebihkan efek yang sesungguhnya (overestimate). Metaanalisis dari 9 studi menunjukan bahwa Chat GPT-4 lebih akurat dibandingkan Chat GPT-3 dalam menjawab pertanyaan medis.</p>2024-10-14T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2274Perawatan Tali Pusat Bayi Baru Lahir: Narrative Review2024-06-04T08:08:55+00:00Tetti Solehatitetti.solehati@unpad.ac.idDinar Indriani livana.ph@gmail.comRuth Jamlaaylivana.ph@gmail.comVina Fuji Lestarilivana.ph@gmail.comCecep Eli Kosasih livana.ph@gmail.com<p>Masa neonatal merupakan masa paling rentan bagi kelangsungan hidup seorang anak, salah satunya rentan terhadap infeksi. Tujuan penelitian adalah untuk mengidentifikasi metode perawatan tali pusat dalam mencegah infeksi pada bayi baru lahir. Desain penelitian narrative review. Pencarian artikel menggunakan kata kunci “Umbilical cord care “AND “Newborn “AND Infection risk “OR” Infection “OR” Complication melalui Database CINAHL, PubMed, dan Science Direct dengan memperhatikan kriteria inklusi, seperti: fokus pada penelitian perawatan tali pusat, artikel primer, dan fullteks, rentang tahun 2015-2024. Hasil pencarian sebanyak 175 artikel, diseleksi dan ditinjau sehingga menghasilkan 20 artikel untuk dianalisis. Hasil akhir ditemukan enem artikel yang eligible, diperoleh 3 tema, yaitu: metode perawatan tali pusat dengan pemberian Air Susu Ibu (ASI) topikal, pemberian chlorhexidine 4%, dan perawatan luka kering. Berdasarkan hasil penelitian dapat disimpulkan ada beberapa metode perawatan tali pusat pada bayi baru lahir yang efektif untuk mencegah infeksi pada bayi baru lahir. Disarankan pemberian edukasi untuk meningkatkan pemahaman tentang pentingnya perawatan tali pusat yang benar dalam mencegah infeksi.</p>2024-08-01T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2470Stigma Diskriminasi dan Dampaknya terhadap Kesediaan Merawat Penderita HIV/AIDS bagi Mahasiswa Keperawatan2024-09-03T18:57:41+00:00Ari Athiutamaari@poltekkespalembang.ac.idImelda Ermanimeldaerman@gmail.comIndra Febrianiindrafebriani@gmail.com<p>Diperkirakan sebanyak 39,9 juta penderita HIV/AIDS pada akhir tahun 2023 dengan angka kesakitan dan kematian masih tinggi utamanya di negara berpenghasilan menengah kebawah. Ini disebabkan oleh mereka yang tidak menyadari status mereka karena adanya stigmatisasi sehingga mengakibatkan ketidaksediaan tenaga kesehatan dalam merawat penderita HIV/AIDS termasuk mahasiswa keperawatan. Penelitian ini memiliki tujuan untuk melihat hubungan antara stigma diskriminasi dengan kesediaan mahasiswa keperawatan merawat penderita HIV/AIDS. Penelitian ini adalah penelitian kuantitatif memakai pendekatan secara cross sectional. Populasi melibatkan seluruh mahasiswa keperawatan di Prodi Keperawatan Poltekkes Kemenkes Palembang dengan jumlah sampel sebanyak 230 responden. Pengumpulan data menggunakan Nursing Willingness Questionnaire (NWQ) dalam bahasa Indonesia (nilai r hitung ≥ lebih dari r tabel (0,46) dan nilai Croncbach Alpha = 0,931) dan kuisioner stigma diskriminasi (nilai r hitung ≥ r tabel dan nilai Conbrach Alpha = 0,822). Hasil yang didapatkan yaitu sebanyak 91,3% mahasiswa keperawatan memiliki stigma diskriminasi dan sebanyak 93% mahasiswa keperawatan masuk dalam kategori tidak bersedia merawat penderita HIV/AIDS. Terdapat hubungan antara stigma diskriminasi dengan kesediaan merawat penderita HIV/AIDS bagi mahasiswa keperawatan (p value 0,001). Semakin banyak terjadi stigma diskriminasi kepada penderita HIV/AIDS maka akan semakin banyak juga ketidaksediaan merawat dari mahasiswa keperawatan. Ini tentunya menjadi bukti bahwa masih tingginya stigma diskriminasi dikalangan mahasiswa keperawatan.</p>2024-10-02T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/1961Efektivitas Edukasi Kesehatan Metode Simulation Game dan Audio Visual dalam Pencegahan Stunting2023-12-18T04:30:13+00:00Putri Widita Muharyaniputriwidita@unsri.ac.idKarolin Adhistylivana.ph@gmail.comNurna Ningsihlivana.ph@gmail.comHerliawati Herliawatilivana.ph@gmail.comAnjar Dwi Fahnilivana.ph@gmail.com<p>Stunting adalah suatu kondisi dimana balita memiliki tinggi badan dan panjang badan yang tidak sesuai jika dibandingkan dengan umur. Stunting pada balita dapat menimbulkan dampak jangka pendek maupun jangka panjang apabila tidak segera di atasi. Faktor yang menjadi penyebab utama balita mengalami stunting yakni kekurangan gizi terutama pada 1000 hari pertama kehidupan (HPK). Pemberian MP-ASI atau makanan pendamping ASI berguna untuk pemenuhan kebutuhan nutrisi dan gizi yang diperlukan untuk pertumbuhan dan perkembangan balita. Penelitian ini merupakan penelitian kuantitatif dan menggunakan quasy experiment dengan rancangan two group pretest-posttest. Sampel penelitian adalah 30 ibu pada kelompok media EMPASI SEHATI dan 30 ibu pada kelompok media video. Pengumpulan data menggunakan kuesioner yang telah dimodifikasi dan melewati tahap uji validitas dan reliabilitas. Analisis data menggunakan paired t test dan independent t test. Hasil penelitian didapatkan bahwa karakteristik responden penelitian pada kedua kelompok yakni mayoritas berusia 31-40 tahun dengan tingkat pendidikan tinggi. Hasil analisis menunjukan bahwa ada pengaruh yang signifikan dari edukasi kesehatan menggunakan simulation games EMPASI SEHATI dan audio visual terhadap pengetahuan ibu sebelum dan sesudah intervensi, p value 0,000 ≤ α (0,05). Adapun pemberian pendidikan kesehatan dengan membandingkan kedua media didapatkan bahwa terdapat perbedaan pengaruh yang signifikan antara media edukasi EMPASI SEHATI dan media video terhadap pengetahuan ibu mengenai stunting dan MPASI. Media edukasi EMPASI SEHATI dapat digunakan sebagai salah satu media untuk edukasi kesehatan.</p>2024-08-15T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2436Pengaruh Video Edukasi terhadap Tingkat Pengetahuan tentang Teknik Menyusui pada Ibu Hamil Trimester III2024-08-13T11:16:39+00:00Mariana Septyanimarianaseptyani95@gmail.comHeny Ekawatilivana.ph@gmail.comWahyu Retno Gumelarlivana.ph@gmail.comDimas Febrianlivana.ph@gmail.com<p>Salah satu hal yang mempengaruhi produksi ASI saat menyusui adalah cara ibu melakukannya. Teknik yang salah dapat menyebabkan puting susu tidak nyaman, yang pada akhirnya membuat ibu tidak mau menyusui dan mengurangi frekuensi bayi baru lahir untuk menyusu. Tujuan penelitian ini adalah untuk mengetahui seberapa besar pengetahuan ibu hamil trimester ketiga di Desa Sedayulawas, Kecamatan Brondong, Kabupaten Lamongan tentang menyusui setelah menonton video. Penelitian ini menggunakan rancangan pre-post test dengan satu kelompok sebagai unit eksperimen. Subjek penelitian ini adalah 34 orang yang semuanya adalah ibu hamil trimester ketiga. Data penelitian ini dikumpulkan dengan kuesioner pengetahuan metode menyusui. Instrumen pengukuran tingkat pengetahuan yang digunakan dalam penelitian ini adalah instrumen yang sudah dilakukan uji validitas dengan nilai r hasil > r tabel (0,361) dan reliabilitas nilai Alpha Cronbach = 0.972 > 0.36, sehingga instrumen penelitian yang digunakan terbukti valid. Analisis data dilakukan dengan 4 tahap. tahap pertama editing yaitu peneliti melakukan kegiatan memeriksa kembali daftar kuesioner yang diserahkan oleh responden. Tahap kedua pengkodean, dengan kode 1= baik, kode 2= cukup, dan kode 3= kurang. Pada tahap ketiga dilakukan scoring dengan nilai baik jika responden menjawab dengan total nilai 76-100%, cukup 56-75%, dan kurang <55%. Pada tahap terakhir tabulating dilakukan pengelompokkan data kedalam suatu tabel sesuai dengan kriteria yang telah ditentukan. Pengethaun ibu hamil trimester tiga di Desa Sedayulawas, Kecamatan Brondong, Kabupaten Lamongan, terdapat pengaruh pengetahuan tentang teknik menyusui yang dipengaruhi oleh video, berdasarkan hasil penelitian (p = 0,000) yang dianalisis menggunakan uji Wilcoxon dengan taraf signifikansi α<0,05. Pelayanan kesehatan yang bertujuan untuk meningkatkan pemahaman ibu hamil tentang tata cara menyusui idealnya dapat memanfaatkan media video sebagai masukan.</p>2024-08-22T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/1615Dukungan Sosial dalam Pencarian Pertolongan Kesehatan Mental Mahasiswa2023-09-03T19:37:10+00:00Indah Kurniawatiindahkurniawati1184@gmail.comSuryani Suryanilivana.ph@gmail.comKhrisna Wisnusaktilivana.ph@gmail.comFarahul Jannahlivana.ph@gmail.com<p>Mahasiswa yang merupakan bagian dari kelompok usia muda (youth). Usia ini merupakan usia yang rentan mengalami permasalahan kesehatan jiwa karena berada pada masa transisi dari remaja menuju dewasa dengan tekanan dan tantangan baru dalam kehidupan sehari-hari. Stres akademik, kekhawatiran akan kondisi ekonomi, hubungan dengan orang lain, meninggalkan keluarga untuk pertama kali akan menyebabkan tingkat stress yang tinggi yang dapat mengakibatkan terjadinya masalah kesehatan mental. Namun, mahasiswa kerapkali enggan dalam mencari pertolongan atas permasalahan kesehatan mental mereka, karena merasa malu atau takut dianggap aneh jika mengalami masalah kesehatan mental. Dorongan dari orang lain merupakan salah satu factor penting dalam pencarian pertolongan, salah satu bentuknya adalah dukungan sosial. Tujuan penelitian ini adalah untuk mengetahui dukungan sosial dalam pencarian pertolongan kesehatan mental. Desain penelitian ini menggunakan pendekatan crossectional, dengan sampel penelitian sebanyak 412 orang mahasiswa. Hasil penelitian didapatkan bahwa ada korelasi antara dukungan sosial terhadap pencarian pertolongan kesehatan mental dengan nilai p value (0,000). Mahasiswa perlu melibatkan sumber-sumber dukungan sosial yang ada disekitarnya untuk dapat meningkatkan kesehatan mental dan membantu dalam upaya pencarian pertolongan kesehatan mental.</p>2024-08-15T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2361Efektifitas Kombinasi Terapi Rendam Kaki Air Hangat dan Terapi Relaksasi Benson terhadap Penurunan Tekanan Darah dan Mean Arterial Presure pada Penderita Hipertensi2024-08-07T11:38:45+00:00Selvi Irfani Nur Rahmahselviirfani09@gmail.comIftitah Nour Safitriiftitahsafitri23@gmail.comOetari Kintan Prahastiprahastikintan@gmail.com<p>Hipertensi merupakan tingginya tekanan darah sistolik lebih dari 140 mmHg dan diastolik lebih dari 90 mmHg. Tujuan penelitian untuk mengetahui pengaruh penurunan kombinasi rendam kaki air hangat dan terapi relaksasi benson terhadap penurunan tekanan darah di Wilayah Kerja Puskesmas Tikung Lamongan. Desain penelitian ini menggunakan Pre Eksperimental one group pra test-post test desain. Dengan teknik consecutive sampling didapatkan sampel sebanyak 44 penderita. Intrumen penelitian ini adalah Pengukuran Tekanan Darah Dan Lembar Observasi. Data ini diambil dengan mendatangi penderita dengan pre test memberikan terapi kombinasi rendam kaki air hangat dan terapi relaksasi benson dan setelah pemberian perlakukan selama 20-30 menit diberi jeda 5 menit kemudian pengecekan kembali. Hasil penelitian menunjukan bahwa perbedaan rata tekanan darah sebelum perlakukan 154.18/91.09 mmHg dan sesudah perlakuan 141.43/88.30 mmHg. Analisis data menggunakan uji paired t test dengan signiffikasi p=0.005. Berdasarkan hasil didapatkan uji statistik pre-post sistol dan pre-post diastol dengan nilai signifikasi p=0.000 (p<0.005) artinya ada pengaruh pemberian terapi kombinasi terapi rendam kaki dan terapi relaksasi benson terhadap penurunan tekanan darah dan mean arteria pressure pada penderita hipertensi di wilayah kerja Puskesmas Tikung Lamongan. Dalam pemberian terapi kombinasi ini untuk meningkatkan pengetahuan dan memudahkan masyarakat dalam menurunkan tekanan darah.</p> <p> </p>2024-08-23T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2297Hubungan Dukungan Suami dan Dukungan Keluarga dengan ASI Ekslusif pada Anak Stunting2024-09-03T19:09:55+00:00Rani Fitriani Arifinlivana.ph@gmail.comMeske Aulia Mutiaralivana.ph@gmail.comTara Indra Dirgantaralivana.ph@gmail.comAsmarawanti Asmarawantilivana.ph@gmail.comYosep Purnairawanyoseppurnairawan@gmail.com<p>Stunting merupakan salah satu masalah gizi yang berdampak buruk terhadap kualitas hidup anak dalam mencapai titik tumbuh kembang yang optimal sesuai potensi genetiknya. Salah satu asupan gizi pada masa pertumbuhan anak awal adalah ASI ekslusif. balita yang memiliki riwayat ASI non eksklusif akan berisiko lebih besar untuk menyebabkan anak mengalami stunting. Pemberian ASI eksklusif dipengaruhi oleh beberapa faktor, seperti faktor dukungan suami dan dukungan keluarga. Tujuan penelitian ini untuk mengetahui hubungan dukungan suami dan dukungan keluarga dengan ASI ekslusif pada anak stunting. Jenis penelitian yang digunakan adalah kolerasional. Populasi dan sampel sebnayak 122 responden cara pengambilan sampel menggunakan total sampling. Analisis hipotesis menggunakan Chi-square. Hasil penelitian sebagian besar ibu yang menyusui mendapatkan dukungan suami, dukungan keluarga, dan mendapatkan ASI ekslusif. Hasil uji Chi-square didapatkan P-value 0,003 untuk variabel dukungan suami dan untuk variabel dukungan keluarga didapatkan P-value 0,016, sehingga ada hubungan dukungan suami dan dukungan keluarga dengan ASI ekslusif pada anak stunting. Disimpulkan ada hubungan dukungan suami dan dukungan keluarga dengan ASI ekslusif pada anak stunting. Diharapkan Puskesmas Benteng Kota Sukabumi melakukan penyuluhan ASI ekslusif, dukungan dari suami dan keluarga sehingga ibu yang menyusui memberikan ASI ekslusif kepada anaknya.</p>2024-11-02T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2834Pengaruh Model Gibbs Reflection Cycle pada Peningkatan Profesonalitas Perawat2024-09-15T17:12:38+00:00I Wayan Dedus Suriyanasy@gmail.comHayyu Sitoresmis@gmail.comHaeril Amirideapengabdianmasyarakat@gmail.com<p>Pendidikan Keperawatan Berkelanjutan (PKB) merupakan proses yang harus dilalui dan terus dijalankan oleh perawat sebagai bentuk dan upaya mempertahankan profesionalismenya. PKB dapat dilakukan dengan Diskuisi Refleksi Kasus (DRK). Tujuan penelitian ini yakni mengetahui pengaruh model Gibbs Reflection Cycle pada DRK perawat dalam meningkatkan profesionalisme kerja. Metode penelitian yang digunakan yakni quasi eksperimen dengan one group pretest dan post test. Sampel dalam penelitian ini yakni 72 orang dengan kriteria inklusi adalah perawat yang melaksanakan DRK. Penelitian ini dilakukan pada juli-agustus 2024. data disajikan dan diolah dengan software SPSS V.26. Hasil penelitian yakni varaibel pengetahuan berdasarkan uji wilcoxon <em>p- value </em>0,000<0,05 dan variabel otonomi dan tanggung jawab <em>p-value </em>0,000<0,05 maka dapat disimpulkan bahwa adanya perbedaan sikap otonomi dan tanggung jawab pada saat <em>pre-test </em>dan <em>post-test. </em>Kesimpulan penelitian ini yakni DRK yang dilakukan dengan Model Gibbs Reflection Cycle dapat meningkatkan profesionalisme perawat khususnya pengetahuan, otonomoi dan tanggung jawab.</p> <p> </p>2024-10-31T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2208Terapi Sari Kurma dalam Meningkatkan Kadar Hb pada Remaja2024-02-27T08:43:16+00:00Iroma Maulidalivana.ph@gmail.comNora Rahmanindarnorarahmanindar@gmail.comUmi Barorohlivana.ph@gmail.comUlfatul Latifahlivana.ph@gmail.com<p>Anemia ditandai dengan menurunnya jumlah eritrosit atau kadar hemoglobin dibawah 11g/dl. Anemia pada remaja putri (rematri) akan berdampak pada kesehatan dan prestasi di sekolah. Remaja kelas XII biasanya disibukkan dengan pembelajaran sebagai persiapan ujian kelulusan serta persiapan ujian masuk Perguruan Tinggi. Aktivitas yang padat tersebut tentu rawan mengakibatkan kekurangan asupan termasuk kadar Hb dalam darah. Sari kurma mengandung serat tinggi dan zat berguna lainnya seperti kalium, mangan, fosfor besi dan kalsium. Olehkarena itu penelitian ini ditujukan untuk mengetahui hubungan konsumsi sari kurma dengan kadar Hb pada siswa SMU kelas XII. Tujuan penelitian ini adalah mengetahui hubungan konsumsi sari kurma terhadap peningkatan kadar Hb pada Siswa SMA Kelas XII. Penelitian ini merupakan jenis penelitian kuantitatif analitik dengan disain eksperimen semu yaitu Non randomized Pretest-Posttest Control Group Design. Populasi adalah siswa kelas XII IPA SMU Muhammadiyah dan diambil 40 siswa sebagai sampel dengan purpossive sampling, serta memiliki kriteria inklusi tidak sedang berpuasa, tidak sedang menstruasi, tidak sedang menderita penyakit infeksi/kronis, tidak sedang mengkonsumsi obat-obatan termasuk tablet tambah darah dan tidak sedang sakit pada saat proses pengambilan data. Pengukuran kadar Hb dilaksanakan 2 kali, di awal penelitian dan setelah 10 hari, baik pada kelompok intervensi maupun pada kelompok kontrol. Hasil penelitian menunjukkan rata-rata Hb siswa sebelum minum sari kurma sebesar 15.72 sedangkan setelah minum sari kurma adalah 15.74. Diketahui tidak ada berbedaan yang bermakna antara konsumsi sari kurma dengan rata-rata perubahan kadar Hb antara kelompok intervensi dan kelompok control (p-value 0.604; 95% Confident Interfal).</p>2024-08-01T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/2458Pengaruh Pursed Lip Breathing dan Number Counting terhadap Tekanan Darah, Nadi dan Frekuensi Pernafasan pada Pasien Hipertensi 2024-09-03T19:03:36+00:00Rizky Asta Pramestirinirizkyastapramestirini@gmail.comHeny Ekawatiunamubarok@gmail.comWahyu Retno Gumelarwrgumelar@gmail.com<p>Hipertensi dapat menimbulkan gejala yang bervariasi mulai ringan hingga parah. Sehingga hipertensi dapat mengakibatkan kerusakan organ vital secara permanen. Oleh karena itu pentingnya penanganan secara farmakologi dan non farmakologi. Farmakologi dalam jangka panjang dapat memberikan dampak negative terhadap kesehatan secara umum terlebih tanpa adanya pengawasan dan kontrol yang ketat dari tenaga medis. Tujuan dari penelitan adalah Mengetahui pengaruh Pursed Lip Breathing Dan Number Counting Terhadap Tekanan Darah, Nadi dan Frekuensi Pernafasan Pada Pasien Hipertensi Di Desa Sidomlangean. Desain dan metode yang digunakan dalam penelitian ini adalah pre eksperimental, dengan metode one group pre-post test design. Dengan total sampling yakni 30 sampel. Tekanan darah, nadi dan frekuensi nafas pre intervensi dan post intervensi dianalisis menggunakan uji Paired t Test. Hasil penelitain menunjukkan ada pengaruh Pursed Lip Breathing Dan Number Counting terhadap tekanan darah sistolik dengan p value 0,004 dan terhadap tekanan darah diastolik dengan p value 0,002. Selain itu intervensi pursed lip breathing menunujukan pengaruh terhadap nadi dengan p value 0,043 dan frukuensi nafas dengan p value 0,021. Pursed Lip Breathing Dan Number Counting dapat menjadi salah satu pendamping terapi dalam upaya menurunkan tekanan darah, nadi dan frekuensi nafas.</p>2024-10-02T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatanhttps://journal2.stikeskendal.ac.id/index.php/keperawatan/article/view/1834Preloading Pre Spinal Anestesi Mempengaruhi Tekanan Sistolik dan Diastolik Pasien2023-11-08T18:19:30+00:00Aric Frendi Andriyanaricfrendi@yahoo.comIswenti Noveralivana.ph@gmail.comElok Insanilivana.ph@gmail.com<p>Komplikasi yang paling umum dari spinal anestesi adalah hipotensi, hal ini disebabkan terjadinya vasodilatasi pembuluh darah sehingga menyebabkan ketidakstabilan hemodinamik. Salah satu cara untuk mencegah hipotensi adalah dengan memberikan preloading cairan. Tujuan: untuk mengetahui pengaruh pemberian preloading cairan terhadap hemodinamik yaitu tekanan darah pasien dengan teknik spinal anestesi di RSUD dr. Rasidin Padang. Metode: Penelitian ini merupakan penelitian Pre Eksperiment dengan desain One-Group Pre Test-Post Test. Penelitian dilakukan pada bulan Desember 2022 – Januari 2023 dengan sampel 36 responden. Pengambilan sampel dengan purposive sampling. Uji yang dilakukan menggunakan uji paired sample t-test. Pengukuran hemodinamik dilakukan sebelum preloading cairan lalu dilakukan observasi dan dilakukan lagi pengukuran hemodinamik setalah dilakukan anestesi spinal. Hasil: Penelitian ini menunjukkan bahwa terdapat pengaruh pemberian preloading cairan terhadap tekanan sistole pasien dengan teknik spinal anestesi di RSUD dr. Rasidin Padang (p=0,000), terdapat pengaruh pemberian preloading cairan terhadap tekanan diastole pasien dengan teknik spinal anestesi di RSUD dr. Rasidin Padang (p=0,000). Kesimpulan: Terdapat pengaruh pemberian preloading cairan terhadap hemodinamik tekanan sistolik dan diastolic pasien dengan teknik spinal anestesi di RSUD dr. Rasidin Padang.</p>2024-10-30T00:00:00+00:00Copyright (c) 2024 Jurnal Keperawatan