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All Journal MEDISAINS International Journal of Advances in Intelligent Informatics Jurnal Rekayasa Mesin ZOO INDONESIA JOIV : International Journal on Informatics Visualization Journal of Applied Information, Communication and Technology (JAICT) Home Economics Journal Journal of Maternal and Child Health Journal of Telenursing (JOTING) Indonesian Journal of Global Health research MAHESA : Malahayati Health Student Journal Abditeknika - Jurnal Pengabdian Kepada Masyarakat Society: Jurnal Pengabdian Masyarakat Journal Of Human And Education (JAHE) Innovative: Journal Of Social Science Research Berita Biologi
Kurnianingsih Kurnianingsih, Kurnianingsih
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Development of A Detection Tool in Pregnant Women and Its Recommendations in Utilizing Artificial Intelligence Oktaviani, Nur Hilda; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
Journal of Maternal and Child Health Vol. 9 No. 3 (2024)
Publisher : Masters Program in Public Health, Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26911/thejmch.2024.09.03.11

Abstract

Background: Chronic Energy Deficiency (CED) can be experienced by women of reproductive age (WUS) aged 15–45 years old since adolescence then continues during pregnancy and breastfeeding due to low energy and nutrient reserves. Health technology innovation that utilizes artificial intelligence, i.e. Digital mid-uppr arm circumference (MUAC) which is a digital measurement tool that can make it easier to read anthropometric measurement results, especially in measuring upper arm circumference to detect pregnant women who experience CED. Subjects and Method: This was a Research and Development with a pre-experimental design with an on shot case study. The number of samples is 100 Subjects, which is done 3 times each month for 3 months. The sample was selected by purposive sample. The analysis used artificial intelligence. Results: Digital MUAC level of accuracy in detecting CED in pregnant women and its recommendations that utilize artificial intelligence, an accuracy level of 100%. Conclusion: The CED detection tool Digital MUAC, is a tool capable of detecting CED and providing recommendations based on the results of CED detection in pregnant women who utilize artificial intelligence by having accurate measurement results with an accuracy value of 100%.
Implementation of Web-Based Marketing System Technology for Bakat Jaya MSMEs, Magelang Aji, Nurseno Bayu; Yudantoro, Tri Raharjo; Mardiyono, Mardiyono; Kurnianingsih, Kurnianingsih; Yanwari, Muhammad Irwan; Kuntarjo, Samuel Beta; Anif, Muhammad; Wiktasari, Wiktasari; Prayitno, Prayitno; Triyono, Liliek
Society : Jurnal Pengabdian Masyarakat Vol 4, No 3 (2025): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i3.571

Abstract

This study explores a digital transformation initiative implemented for UMKM Bakat Jaya, a micro-enterprise based in Magelang specializing in animal feed production. Initially hindered by limited market reach, low digital literacy, and a lack of integrated technological tools, the enterprise relied primarily on traditional social media platforms for promotion. To address these challenges, a comprehensive and user-friendly website was developed using WordPress, featuring a professional company profile, product gallery, contact information, and seamless integration with existing social media accounts. The project was executed in four key phases: needs identification, website design and development, training and mentoring, and implementation followed by evaluation. Remote interviews and surveys were conducted to assess the partner’s needs, while capacity-building activities empowered stakeholders to manage the digital platform independently. Preliminary outcomes indicate a substantial improvement in market visibility, customer engagement, and operational efficiency. The results highlight the potential of structured digital interventions to transform the promotional strategies of rural micro and small enterprises, offering a scalable and sustainable model for enhancing competitiveness in similar contexts.
Krekers Tepung Jantung Pisang Sebagai Usaha Diversifikasi Pangan Berbasis Sumber Daya Lokal Triastuti, Unggul Yuyun; Priyanti, Esteria; Diana, Tri Rettagung; Kurnianingsih, Kurnianingsih
Home Economics Journal Vol. 2 No. 1 (2018): May
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (90.989 KB)

Abstract

Tujuan dari penelitian ini yaitu mengetahui tingkat kesukaan krekers dengan penambahan tepung jantung pisang dan mengetahui kandungan karbohidrat, lemak dan protein dari krekers dengan prosentase penambahan jantung pisang yang terbaik. Penelitian ini merupakan penelitian eksperimental, dengan membandingkan krekers yang menggunakan penambahan tepung jantung pisang sebanyak 15%, 20% dan 25% dari berat bahan kering. Tahapan pelaksanaan penelitian terdiri dari 2 tahap yaitu tahap pembuatan tepung jantung pisang dan tahap pembuatan krekers jantung pisang. Setiap perlakukan dilakukan 3 kali pengulangan agar mendapatkan formula resep yang tepat. Setelah mendapatkan formula resep yang tepat kemudian dilakukan uji tingkat kesukaan. Berdasarkan hasil uji tingkat kesukaan panelis terhadap rasa, warna, tekstur dan aroma dari krekers jantung pisang menunjukkan nilai rerata tertinggi pada produk dengan penambahan 15% tepung jantung pisang. Nilai rerata sebesar 3,33 (netral) untuk rasa, 3,30 (netral) untuk warna, 3,07 (netral) untuk tekstur dan 3,00 (netral) untuk aroma. Oleh sebab itu, produk tersebut merupakan produk yang dapat diterima oleh panelis dari segi rasa, aroma, tekstur dan warna. Hasil uji kandungan gizi dari dari krekers dengan penambahan sebanyak 15% tepung jantung pisang yaitu kadar karbohidrat 32,44%, kadar lemak 13,02% dan kadar protein 6,20%.
Advanced Instance Segmentation of Aeroponics Tissue Culture-Based Seeds Potatoes Based on Improved YOLOv8l-small Avisyah, Gisnaya Faridatul; Kurnianingsih, Kurnianingsih; Hidayat, Sidiq Syamsul
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3085

Abstract

To improve agricultural production, this study develops an advanced instance segmentation system for aeroponic tissue culture-based potato seedlings. We present an IoT system that integrates multiple sensors for humidity, temperature, pH, and turbidity to enable real-time monitoring. Additionally, we adapt the YOLOv8l-small computer vision model, an optimized version of YOLOv8, designed explicitly for efficient potato leaf disease detection and segmentation, even in resource-constrained IoT environments. YOLOv8 is a significant advancement in the YOLO series, for instance, segmentation, combining better accuracy, efficiency, and flexibility. YOLOv8 outperforms previous methods in generating precise segmentation masks while maintaining real-time performance. These innovations make YOLOv8 a robust choice for a variety of computer vision tasks, including instance segmentation, in both research and practical applications. When tested on a custom dataset of potato leaf pictures, the suggested model produced mask mAP50 of 0.842 and mAP50-95 of 0.566, with a model size of 36.1 MB and an inference duration of 9.3 ms. These outcomes are similar to those of the original YOLOv8l model, which had a slower inference time of 11.0 ms and a much larger model size of 92.3 MB, albeit at the expense of a somewhat higher mAP50 of 0.843. The study concludes that the proposed model provides similar accuracy with greater computational efficiency, making it ideal for IoT-based agricultural systems. Future research will explore additional aspects, while practical experiments aim to reduce labor costs.
Big data analytics for relative humidity time series forecasting based on the LSTM network and ELM Kurnianingsih, Kurnianingsih; Wirasatriya, Anindya; Lazuardi, Lutfan; Wibowo, Adi; Enriko, I Ketut Agung; Chin, Wei Hong; Kubota, Naoyuki
International Journal of Advances in Intelligent Informatics Vol 9, No 3 (2023): November 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v9i3.905

Abstract

Accurate and reliable relative humidity forecasting is important when evaluating the impacts of climate change on humans and ecosystems. However, the complex interactions among geophysical parameters are challenging and may result in inaccurate weather forecasting. This study combines long short-term memory (LSTM) and extreme learning machines (ELM) to create a hybrid model-based forecasting technique to predict relative humidity to improve the accuracy of forecasts. Detailed experiments with univariate and multivariate problems were conducted, and the results show that LSTM-ELM and ELM-LSTM have the lowest MAE and RMSE results compared to stand-alone LSTM and ELM for the univariate problem. In addition, LSTM-ELM and ELM-LSTM result in lower computation time than stand-alone LSTM. The experiment results demonstrate that the proposed hybrid models outperform the comparative methods in relative humidity forecasting. We employed the recursive feature elimination (RFE) method and showed that dewpoint temperature, temperature, and wind speed are the factors that most affect relative humidity. A higher dewpoint temperature indicates more air moisture, equating to high relative humidity. Humidity levels also rise as the temperature rises.
Pelatihan Keterampilan Membuat Media Pembelajaran Digital bagi Guru Sekolah Dasar Di SD Ridan Permai Pebriana, Putri Hana; Nurhaswinda, Nurhaswinda; Kusuma, Yanti Yandri; Henra, Mustika; Kurnianingsih, Kurnianingsih; Miyar, Miyar
Journal Of Human And Education (JAHE) Vol. 4 No. 3 (2024): Journal of Human And Education
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v4i3.1686

Abstract

Penelitian ini dilakukan untuk meningkatkan kompetensi guru dalam merancang dan menggunakan teknologi digital dalam proses pembelajaran. Pelatihan ini diadakan sebagai respons terhadap perkembangan teknologi yang semakin pesat dan tuntutan pendidikan abad ke-21 yang menekankan literasi digital, kreativitas, serta penggunaan media interaktif. Peserta pelatihan adalah guru-guru dari berbagai sekolah dasar yang belum sepenuhnya menguasai perangkat dan aplikasi pembelajaran digital. Metode yang digunakan dalam pelatihan ini meliputi presentasi materi oleh narasumber, demonstrasi penggunaan perangkat lunak, dan praktik langsung oleh peserta dalam membuat media pembelajaran digital seperti slide interaktif, video pembelajaran. .Hasil dari pelatihan menunjukkan peningkatan signifikan dalam pemahaman dan keterampilan guru dalam memanfaatkan media digital, serta adanya motivasi yang lebih besar dari peserta untuk mengaplikasikan teknologi dalam proses pembelajaran di kelas. Pelatihan ini diharapkan mampu berkontribusi dalam meningkatkan kualitas pembelajaran di sekolah dasar dan mendukung pencapaian tujuan pendidikan nasional yang lebih baik di era digital
Effect of Moringa Leaves Oral Supplementation on Pro-Inflammatory Cytokines in PEM Conditions Aquarista, Nita; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
Indonesian Journal of Global Health Research Vol 6 No 4 (2024): 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.v6i4.3256

Abstract

Protein-Energy Malnutrition (PEM) is a nutritional problem resulting from protein or energy deficiency, often associated with the occurrence of infections. Infections due to weakened immune systems caused by protein deficiency can lead to inflammation. The flavonoid content in moringa oleifera leaf (MOL) has anti-inflammatory that can be utilized as an alternative treatment for PEM. Objective: To identified the potential of MOL as an anti-inflammatory in PEM conditions. Method: This study is a systematic literature review that were obtained through Google Scholar, ScienceDirect and PubMed databases for the last 10 years from 2012 to 2022 with a total 80 articles found based on keyword searches. References then re-selected using PICOS method, resulting in 9 articles be reviewed. The review process involves gathering pertinent information that is applicable to the study objectives and analyzing it based on population/problems, intervention or management to the case, comparating the similarities and differences, study the outcome and study design of the previous articles. Then the information will be synthesized to conclude the review. Results: The findings indicate that MOL can be used effectively for patient with PEM as an anti-inflammatory agent by reducing the secretion of pro-inflammatory cytokines such as IL-1, IL-6 and TNF-α Conclusions: Administration of oral supplementation of MOL has a positive impact as an anti-inflamatory in PEM condition.
Servical Dilatation Measuring Device Putri, Winda Astria; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
Indonesian Journal of Global Health Research Vol 6 No 5 (2024): 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.v6i5.3264

Abstract

Childbirth represents a physiological phenomenon encountered by females subsequent to the gestational process, necessitating the assistance of healthcare professionals for its monitoring also evaluation. Presently, the manual assessment of cervical dilation through digital palpation by obstetricians or midwives remains the prevailing approach. Nonetheless, manual cervical manipulation is administered by healthcare providers in various clinical settings, leading to subjective also potentially imprecise diagnostic results, which heavily depend on the skill also clinical judgment of the provider. This study aims to examine the development of cervical dilation measurement tools from 1998 to 2015. It underscores the imperative for a tool capable of delivering impartial also precise assessments devoid of human influence. This inquiry adopts a literature review methodology, employing Evidence Based Practice (EBP) as the framework for exploration, leveraging Google Scholar as the primary database. The retrieved literature, spanning from 1995 to 2005, exclusively comprises international journals. Within this systematic scrutiny, apparatuses utilized for dilation measurement are systematically cataloged as per their operational principles also clinical utility. The analysis suggests that image data processing technology holds considerable promise for refinement into instrumentation dedicated to cervical dilation assessment.
Expert System for Fetal Heart Rate Measuring Devices: Literature Review Susmiyati, Susmiyati; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
Indonesian Journal of Global Health Research Vol 6 No 4 (2024): 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.v6i4.3280

Abstract

With the current development of science and technology, many fetal heart rate detection devices have been designed and have become superior in the field of technology. The aim of the literature study is to find out which expert systems have been developed to detect fetal heartbeats. This research method is a literature study, with a search using Evidence Based Practice (EBP) from the Google Scholar data base. There are 10 articles based on searching results using the PICO technique for the last 5 years from 2019-2023. After conducting an article search, 10 research articles were selected that met the inclusion criteria. The results of the analysis found that there are several expert systems that have been developed to detect fetal heartbeats, including: Android-based, Bluetooth low energy, LabVIEW, Telefetalcare system, Blind Source Separation, smartwatch, Demster-Shafer, Phantom, Arduino Uno, and ATMega8 microcontroller. It was concluded that the health sector system had developed a lot.
Design and Develop An Early Detection System Application to Monitor Kidney Health in Pregnant Women Amalia, Dhanty Nurul; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
Indonesian Journal of Global Health Research Vol 6 No 5 (2024): 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.v6i5.3377

Abstract

Pregnancy is a physiological process that can become pathological if not well monitored. Kidney disease will increase the risk during pregnancy, namely preeclampsia, fetal growth restriction, and loss of maternal kidney function. Chronic kidney disease in pregnant women often goes undiagnosed. Kidney disease problems detected will worsen if not examined at the early signs and symptoms or delaying treatment for kidney disease. This study proves the effectiveness and accuracy of early detection systems for kidney health in pregnant women. In the design of this application, exploratory data analysis (EDA) and data visualization techniques are used, which will provide deeper insight into the distribution, trends and relationships between variables in the data which includes data on pregnant women, perceived symptoms and laboratory examination. From the results of the design of this early detection system application, it shows perfect performance of the model on the overall dataset with precision, recall, and F1-score scores all reaching 1.00 or 100% accuracy. The developed classification model shows outstanding performance. This success can be attributed to the selection of relevant features, effective data preprocessing, and the selection of the appropriate classification model.
Co-Authors Abu Hasan Adi Wibowo alfiah alfiah Alifiansyah, Muhammad Fikry Amalia, Dhanty Nurul Amin Suharjono Anindya Wirasatriya Anis Roihatin Apandi, Apandi Aquarista, Nita Ari Suwondo Arselatifa, Elviga Asmaul Husna Avisyah, Gisnaya Faridatul Azka Khoirunnisa Chin, Wei Hong Darmawan Darmawan Dhanio, Yeyen Wulandari Diana, Tri Rettagung Donny Kristanto Mulyantoro edy susanto Fahriah, Sirli Fatahul Arifin, Fatahul fatimah Fatimah Fitriyani, Rizki Putri Gustiyana, Fikri Nizar Haerul, Haerul Hajrianti, Siti Hashimoto, Takako Henra, Mustika Hesti Kurniasih I Ketut Agung Enriko Ika Rahmawati Istiqomah, Nursita Kubota, Naoyuki Kuntarjo, Samuel Beta Kusuma, Yanti Yandri Lutfan Lazuardi Maharadatunkamsi Maharadatunkamsi, Maharadatunkamsi Mardiyono Mardiyono Masuyama, Naoki Melyana Nurul Widyawati Miyar, Miyar Muhammad Anif Mulyadi Mulyadi Muryasari, Ika Nana Supriatna Nojima, Yusuke NOVA MUJIONO Nur Ghaniaviyanto Ramadhan Nurhaman, Ujang Nurhaswinda Nurseno Bayu Aji, Nurseno Bayu Oktaviani, Nur Hilda Prayitno Prayitno Prihandini, Riena Priyanti, Esteria Priyatna, Yayat Puspita Sari, Erika Lety Istikhomah Putri Hana Pebriana Putri, Winda Astria Rachmatiyah, Rina Rakasiwi, Rizky Khaerul Maulana Runjati Santosa, Naufal Adli Santoso, Pramono Hery Sarino . Sauri, Sopian Septiani, Camilla Sidiq Syamsul Hidayat, Sidiq Syamsul Sofyani, Umar Sri Sumarni Sudiyono Sudiyono Suparno Suparno Susmiyati, Susmiyati Tatag Bagus Putra Prakarsa Tri Raharjo Yudantoro Triastuti, Unggul Yuyun Trilaksono, Wahyu Triyono, Liliek Veryal, Veryal Wahyu Sulistiyo Wahyudin, Mohamad Walin Walin, Walin Wikanta, Hadi Wiktasari Wiktasari, Wiktasari Yanwari, M. Irwan Yanwari, Muhammad Irwan Yusuf Dewantoro Herlambang