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All Journal Indonesian Journal of Medicine JURNAL MUTIARA KESEHATAN MASYARAKAT Jurnal Keperawatan Priority Jurnal Kesehatan Masyarakat dan Lingkungan Hidup JURNAL ILMIAH SIMANTEK Jurnal Gentle Birth JUKESHUM: Jurnal Pengabdian Masyarakat Miracle Journal International Journal of Public Health Excellence (IJPHE) International Journal of Health, Engineering and Technology Sevaka: Hasil Kegiatan Layanan Masyarakat
Nailatun Nadrah
Institut Teknologi Dan Kesehatan Ika Bina
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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PENGETAHUAN IBU MENYUSUI PADA BAYI USIA 0-6 BULAN TENTANG MANFAAT ASI EKSLUSIF DI Bidan Hj Nani, S.Keb TAHUN 2022 Nailatun Nadrah; Rika Handayani; Sri Wulandari
Jurnal Gentle Birth Vol 6, No 1 (2023): Januari 2023
Publisher : Akademi Kebidanan Ika Bina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56695/jgb.v6i1.116

Abstract

Masih rendahnya cakupan keberhasilan pemberian ASI Ekslusif pada bayi, dipengaruhi banyak hal, diantaranya rendahnya pengetahuan dan kurangnya informasi pada ibu dan keluarga mengenai pentingnya pemberian ASI Ekslusif. Penelitian ini bertujuan untuk mengetahui pengetahuan ibu menyusui pada bayi usia 0-6 bulan tentang manfaat asi ekslusif di Bidan Hj Nani, S.Keb Tahun 2022. Jenis penelitian ini adalah deskriptif. Penelitian ini dilakukan di Bidan Hj Nani, S.Keb. Populasi dalam penelitian ini adalah semua ibu menyusui  pada bayi 0-6 bulan di Bidan Hj Nani, S.Keb. Teknik pengambilan sampel menggunakan total sampling sebanyak 51 responden. Analisis data yang dilakukan adalah analisis univariat. Hasil penelitian ini menunjukkan bahwa sebagian responden memiliki pengetahuan yang baik tentang pengertian ASI eksklusif yaitu sebanyak 28 orang (73,7%) dan responden memiliki pengetahuan yang baik tentang manfaat ASI eksklusif yaitu sebanyak 31 orang (81,6%). Berdasarkan hasil penelitian ini, sebaiknya petugas kesehatan terutama bidan bekerja sama dengan instansi kesehatan mengadakan kegiatan penyuluhan dan konseling agar dapat meningkatkan pengetahuan dan informasi ibu tentang pentingnya dan manfaat pemberian ASI eksklusif
Factors Related to Premenstrual Syndrome in Young Women at MTsN Labuhanbatu in 2024 Jolyarni, Novica; Nadrah, Nailatun; Nasution, Fitriyani
International Journal of Public Health Excellence (IJPHE) Vol. 4 No. 1 (2024): June-December
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijphe.v4i1.1011

Abstract

Premenstrual syndrome (PMS) is a complex and poorly understood condition consisting of one or more of a number of physical and psychological symptoms that begin in the luteal phase of the menstrual cycle. World Health Organization (WHO) in 2020 PMS has a higher prevalence in Asian countries compared to western countries. The purpose of this study was to determine the factors associated with Premenstrual syndrome in adolescent girls at MTsN 1 Labuhanbatu in 2024. This research design uses an analytic survey, namely research trying to explore how and why the phenomenon occurs. Then analyze the dynamics of the correlation between phenomena, both between related factors (Indipendent) and effect factors (Dependent). The approach used in this research is cross sectional. The population in this study was 291 people. The sample in this study amounted to 74 people. Data analysis used univariate analysis and bivariate analysis using the chi-square test. The results of statistical tests with stress categories obtained using the chi-square test at a confidence level of 95% are known that psig 0.000 is smaller than 0.05, the results of chi-square tests with consumption patterns at a confidence level of 95% are known that psig 0.000 is smaller than 0.05, the results of statistical tests with premenstrual syndrome incidence obtained using the chi-square test at a confidence level of 95% are known that psig 0.000 is smaller than 0.05. In conclusion, it is known that there is a relationship between stress, consumption patterns and exercise with the incidence of premenstrual syndrome in adolescent girls at MTsN 1 Labuhanbatu in 2024. It is suggested that the results of this study can add insight, knowledge and experience about premenstrual syndrome that can occur at any time.
Pemetaan Ibu Hamil Anemia dan Kek Serta Pengenalan Makanan Tambahan Berbasis Lokal di Wilayah Kerja Puskesmas Simundol Nailatun Nadrah; Rika Handayani; Novica Jolyarni Dornic
Jukeshum: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): Edisi Juli 2024
Publisher : Universitas Haji Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51771/jukeshum.v4i2.959

Abstract

Salah satu penyebab stunting adalah anemia dan Kekurangan Energi Kronis (KEK) pada ibu hamil, karena asupan makanan yang tidak mencukupi untuk meningkatkan hemoglobin, berat badan, dan Lingkar Lengan Atas. Berbagai upaya telah dilakukan dalam rangka penanggulangan Anemia dan KEK dalam kehamilan, namun prevalensi kejadiannya masih tinggi. Pemberian makanan tambahan pada ibu hamil dengan KEK dan pemberian suplementasi besi folat selama kehamilan menjadi upaya dalam penurunan permasalahan gizi dalam kehamilan di Indonesia. Di wilayah kerja puskesmas simundol terdapat 65 ibu hamil kek dan anemia. Tujuan dari kegiatan pengabdian masyarakat ini sebagai pemetaan ibu hamil anemia dan kurang energi kronis (KEK) serta mengenalkan makanan tambahan berbasis lokal. Kegiatan yang dilakukan untuk mendeteksi kejadian anemia dengan Pemeriksaan kadar hemoglobin menggunakan alat ukur hemoglobin digital, data LiLA menggunakan pita LiLA/metlyn pada ibu hamil di Wilayah Kerja Puskesmas Simundol. Hasil dari pemetaan mayoritas ibu hamil pada usia 20-35 tahun 81,5 %. Ibu hamil anemia 100% dan ibu hamil dengan kek 40%. didapatkan ibu hamil anemia saja sebanyak 65 orang, ibu hamil anemia dan KEK sebanyak 26 (50%) orang. Makanan tambahan berbasis lokal memiliki nutrisi yang baik dan relative mudah didapat, sehinga membantu ibu dan keluarga dalam memenuhi kebutuhan nutrisi
Classification of Heart Disease Risk Factors Using Decision Tree at Rantauprapat Regional Hospital Quratih Adawiyah; Riyan Agus Faisal; Nailatun Nadrah; Juni Purwanto; Baginda Restu Al Ghazali
International Journal of Health Engineering and Technology (IJHET) Vol. 3 No. 4 (2024): IJHESS NOVEMBER 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i4.273

Abstract

Heart disease is one of the leading causes of death in Indonesia, so it is important to identify risk factors that contribute to the increasing incidence of heart disease. This study aims to classify risk factors for heart disease using the Decision Tree method with the CART (Classification and Regression Tree) algorithm at Rantauprapat Regional Hospital. The data used includes factors such as Age, High Blood Pressure, High Cholesterol Levels, Body Mass Index (BMI), Family History, Smoking, Unhealthy Diet, and Low Physical Activity. The results of the analysis show that the factors Age, High Blood Pressure, and High Cholesterol Levels have a significant effect on the increased risk of heart disease, with a model accuracy of 80%. Although this model successfully classifies high risk well, there are some errors in identifying low risk, as reflected in the Recall value (0.67).
Predicting the Risk of Premature Birth Using Naive Bayes Based on Maternal Health Data at Rantauprapat Regional Hospital Adawiyah, Quratih; Handayani, Rika; Nadrah, Nailatun; Nasution, Fitriyani; Ramadani, Putri
International Journal of Public Health Excellence (IJPHE) Vol. 4 No. 2 (2025): January-May
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijphe.v4i2.1112

Abstract

Premature birth is one of the leading causes of infant mortality and complications. Early identification of pregnant women at risk of premature delivery is crucial for appropriate management. This study aims to develop a predictive model for premature birth risk using the Naïve Bayes method based on maternal health data from RSUD Rantauprapat. The data used includes variables such as mother's age, nutritional status, blood pressure, and history of premature birth. The study applies Naïve Bayes to predict the classes of premature birth risk, namely "Premature" and "Not Premature", with data divided into 70% for training and 30% for testing. The results show that the Naïve Bayes model achieved an accuracy of 78.33% in predicting premature birth risk. Additionally, the model shows precision of 89.29%, recall of 83.33%, and F1-score of 86.1%, indicating good performance in detecting pregnant women at risk of premature birth. Comparison with other models, such as Logistic Regression and Decision Tree, demonstrates that Naïve Bayes provides the best results in terms of accuracy and balance between precision and recall. This study shows that Naïve Bayes can be an effective tool for early detection of premature birth and can be implemented in medical decision-making systems at hospitals to improve the management of high-risk pregnant women. The results of this study can serve as a foundation for further research that develops predictive models by adding features or other algorithms.
Pengetahuan Bidan Tentang Pencegahan Infeksi Selama Persalinan Di Puskesmas Lingga Tiga Handayani, Rika; dornic, Novica Jolyarni; Nadrah, Nailatun; Tussolihin Dalimunthe, Khodijah
Miracle Journal Vol. 4 No. 1 (2024): Edisi Januari 2024
Publisher : Universitas Haji Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51771/mj.v4i1.1025

Abstract

Risiko infeksi pada ibu, bayi dan pada ibu,bayi dan penolong persalinan akan meningkat persalinan akan meningkat apabila tenaga kesehatan tidak mematuhi pencegahan infeksi pada saat menangani passien terutama pada saat pertolong utama pada saat pertolongan persalinan. Infeksi dapat melalui darah, sekresi vagina melalui darah, sekresi vagina air mani, air mani, cairan amnion dan cairan tubuh lainnya. Saat survei awal dengan wawancara dengan ditemukan bahwa bidan tersebut sudah mengetahui tentang pencegahan infeksi selama persalinan, namun saat observasi, peneliti melihat masih ada beberapa bidan yang belum memakai alat pelindung diri yang lengkap, serta hand hyigiene yang belum sesuai dengan standar. Tujuan penelitian ini adalah untuk melihat gambaran Pengetahuan Bidan tentang Pencegahan Infeksi selama persalinan di Puskesmas Lingga Tiga. Jenis penelitian bersifat deskriftif dengan metode cross sectional, populasi adalah bidan yang bertugas di pusksesmas lingga tiga sebanyak 34 orang, pengambilan menggunakan total sampling. Data yang dikumpulkan adalah data primer yaitu data yang diperoleh secara langsung dari responden. Analisis data yang digunakan yaitu analisis univariat. Dari hasil penelitian diperoleh data sebanyak 45 responden (83,3%). Mayoritas berumur berumur 32-39 tahun sebanyak 24 responden (44,4%), dan memiliki masa kerja 46 (85,19%) > 10 tahun
Kejadian Kurang Energi Kronik Pada Ibu Hamil di Wilayah Kerja Puskesmas Simundol Nadrah, Nailatun; Handayani, Rika; Jolyarni Dornic, Novica
Miracle Journal Vol. 5 No. 1 (2025): Edisi Januari 2025
Publisher : Universitas Haji Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51771/mj.v5i1.1401

Abstract

Salah satu tantangan gizi umum yang dihadapi oleh wanita hamil adalah kekurangan energi kronis (KEK), yang bermanifestasi sebagai konsekuensi dari kekurangan gizi yang berkepanjangan dan ditandai dengan berkurangnya lingkar lengan tengah atas kurang dari 23,5 cm. Dampak malnutrisi pada ibu hamil juga berdampak pada kesehatan ibu dan janin, mencakup risiko tinggi anemia, perdarahan, dan penambahan berat badan yang tidak memadai selama kehamilan, serta persalinan yang lama dan sulit, kelahiran prematur, perdarahan pascapersalinan, dan gangguan perkembangan janin. Data WHO 2021 ibu hamil KEK sebanyak 629 ibu (73,2 %) dari AKI. di Indonesia sebanyak 17,3%, di Sumatera Utara 1.383 ibu hamil KEK, Data dari tempat penelitian ditemukan ibu hamil KEK sebanyak 26 orang ibu KEK. Tujuan penelitian ini adalah untuk mengetahui kejadian KEK pada ibu hamil di wilayah kerja puskesmas simundol. Jenis penelitian ini adalah deskriptif dengan desain cross sectional, populasi pada penelitian ini adalah seluruh ibu hamil KEK yang berjumlah 26 orang. Teknik sampel menggunakan total sampling. Dari penelitian diperoleh hasil bahwa mayoritas responden berumur 20-35 tahun (69,22%), responden dengan p86engetahuan kurang sebanyak 61,5%. Responden memiliki pendidikan menengah sebanyak 50,0%. Pendapatan responden 57,7% memiliki pendapatan yang tinggi. Sebanyak 53,8% responden merupakan primipara. Pengkajian faktor yang berkontribusi dengan kejadian KEK bergantung pada karakteristik spesifik komunitas, konsumsi yang berlaku pola, dinamika sosial-ekonomi, dan budaya dalam komunitas masing-masing.
Penyuluhan Penerapan Naive Bayes Untuk Identifikasi Keterlambatan Perkembangan Anak Berdasarkan Data Kesehatan Pada Program Studi Kebidanan Fahruzi Sirait; Eka Ramadhani Putra; Nailatun Nadrah; Rika Handayani; Yusril Iza Mahendra Hasibuan
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 4 (2024): November: Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i4.525

Abstract

Child developmental delay is a public health issue that needs to be identified early to prevent long-term impacts on children’s quality of life. In Rantau Prapat Sub-district, cases are still found among toddlers with undernutrition, incomplete immunizations, and suboptimal developmental stimulation, which may pose risks of growth and developmental delays. This study aims to apply the Naive Bayes method in identifying child developmental delays based on health data collected through medical records and questionnaires. The research method includes data collection, pre-processing (cleaning, transformation, and normalization), classification using the Naive Bayes algorithm, and model validation with the k-fold cross-validation technique. The results showed that out of 150 toddler data samples, 30.7% experienced developmental delays, with the dominant influencing factors being nutritional status and immunization completeness. The Naive Bayes algorithm achieved an accuracy rate of 87.3% with a precision of 84.1%, recall of 85.7%, and F1-score of 84.9%. These findings demonstrate that Naive Bayes can be used as a decision support system in the early identification process of child developmental delays. Therefore, the results of this study are expected to assist healthcare workers, particularly midwives, in improving the quality of early detection and delivering more targeted interventions for children in the Rantau Prapat area.
Penyuluhan Klasifikasi Risiko Infertilitas Pada Pasien Wanita Berdasarkan Data Rekam Medis Menggunakan Algoritma Naive Bayes Fahruzi Sirait; Hafizhah Mardivta; Nailatun Nadrah; Nadya Fitriyani; Baginda Restu Al Ghazali
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 3 (2025): Agustus : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i3.555

Abstract

Infertility in women is a reproductive health issue that requires early intervention to prevent long-term effects. With the advancement of technology, electronic medical records data can be utilized to assist in the diagnosis and classification of infertility risks. This study aims to classify the risk of infertility in female patients using the Naive Bayes algorithm based on medical record data, which includes factors such as age, health history, and medical test results. The data used in this study were obtained from hospitals and health clinics focused on managing infertility patients. The methods applied include data preprocessing, applying the Naive Bayes algorithm for classification, and evaluating the model using accuracy, precision, recall, and F1-score metrics. The results of the study show that the Naive Bayes algorithm provides fairly accurate classification in predicting infertility risks. The analysis-generated graph shows the distribution of infertility risks, with 60% of patients having a positive risk (1) and 40% having a negative risk (0). This study also suggests implementing the classification results in the form of counseling for patients to increase awareness and encourage early preventive actions. Thus, the Naive Bayes algorithm can be an effective tool in assisting healthcare providers in data-driven decision-making to address infertility risks in female patients.
Pengembangan Platfrom Teknologi Inovatif Untuk Efisiensi Produksi UMKM (2024) Nana Erika; Nailatun Nadrah; Ramada Sandi
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 4 (2024): November: Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i4.557

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in supporting national economic growth and expanding employment opportunities in Indonesia. However, many MSMEs still face significant challenges in improving production efficiency due to limited human resources, low levels of technology adoption, and suboptimal operational management. To address these issues, this study developed an innovative digital technology platform designed to help MSMEs enhance productivity, reduce material waste, and accelerate the production process. The platform integrates Internet of Things (IoT), Artificial Intelligence (AI), and simplified Enterprise Resource Planning (ERP) technologies tailored for small business operations. Through IoT, production processes can be monitored in real time; AI is applied to analyze sales data and predict material requirements and production schedules; while the ERP system automates inventory, transaction, and financial reporting processes. Trials conducted across MSMEs in the food, handicraft, and textile sectors demonstrated a 30% improvement in production efficiency and a 20% reduction in operational costs. The results indicate that the implementation of innovative technological platforms can significantly enhance efficiency, accuracy, and competitiveness among MSMEs. Digital transformation not only increases production efficiency but also enables broader business integration into the global market through cloud-based systems. Government and institutional support are essential to expand the adoption of such technologies, ensuring that Indonesian MSMEs become more adaptive, productive, and sustainable in the era of Industry 4.0.
Co-Authors Adawiyah, Quratih Aswin Syahputra Baginda Restu Al Ghazali Dornic, Novica Jolyarni Eka Ramadhani Putra Fahruzi Sirait Fatwiany Fatwiany Fatwiany Fatwiany Fitriyani Nasution Gerry Silaban Hafizhah Mardivta Handayani, Rika Jolyarni Dornic, Novica jolyarni, novica Juni Purwanto Lina Sartika Nadya Fitriyani Nana Erika Nasution, Fitriyani novica jolyarni Novica Jolyarni D Novica Jolyarni Dornic Quratih Adawiyah Ramada Sandi Ramadani, Putri Rika Handayani Rika Handayani Rika Handayani Rindi Fadila Riyan Agus Faisal SRI WULANDARI Taufik Ashar Tussolihin Dalimunthe, Khodijah Yusril Iza Mahendra Hasibuan