Article Per Year (5 Year)
p-Index From 2021 - 2026
0.817
P-Index
This Author published in this journals
All Journal Community Engagement and Emergence Journal (CEEJ) Journal of Community Development International Journal of Healthcare and Information Technology Advance Sustainable Science, Engineering and Technology (ASSET)
Dian Kartika Sari
Politeknik Negeri Jember
Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Nursing Public Health Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Implementation Artificial Intelligence with Natural Language Processing Method to Improve Performance of Digital Product Sales Service Putri Ariatna Alia; Dian Kartika Sari; Nur Azis; Bernadus Gunawan Sudarsono; Purwo Agus Sucipto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.521

Abstract

Improving the performance of digital product sales services is the main focus of the company's attention in the face of increasingly fierce competition in the online market. In order to optimize these services, Artificial Intelligence (AI) technology with the Natural Language Processing (NLP) method is an attractive option. This research aims to find out how the application of AI with Natural Language Processing (NLP) can contribute to improving the performance of digital product sales services. The methods used in this research include collecting data on customer interactions via WhatsApp that have implemented artificial intelligence with the Natural Language Processing (NLP) method. The data is then analyzed using Natural Language Processing (NLP) techniques to understand the needs, preferences, and problems faced by customers. Natural Language Processing (NLP) assists the chatbot in correcting incoming questions if they do not match the database on the question. Differences that can be helped by Natural Language Processing (NLP) if there is inappropriate capitalization, excessive conjunctions. The results show that the application of AI with Natural Language Processing (NLP), can enable companies to be more responsive to customer needs and improve overall customer satisfaction. With in-depth analysis of customers' natural language data, companies can provide more relevant services and empower sales teams to provide faster and more accurate responses. This can be seen from the quality of service results which have a point of 4.1, this value indicates a good response from customers so that the system is considered to have improved sales services by buyers.
Peningkatan Kesadaran Masyarakat Tentang Anemia dan Pencegahan Stunting di Masa Depan Melalui Aplikasi Anemiago Sabran Sabran; Dian Kartika Sari; Malinda Capri Nurul Satya
Journal of Community Development Vol. 5 No. 3 (2025): April
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v5i3.1386

Abstract

Anemia is a condition where the level of HB or hemoglobin in the blood is less than the normal standard. Based on the 2018 Riskesdas data, the prevalence of anemia in women aged ≥15 years (adolescent girls) was 41.6% while the prevalence of anemia in pregnant women was 48.9%. This figure has increased from 31% in 2013. Adolescent girls who suffer from anemia are at risk of anemia during pregnancy which will potentially increase stunting rates. The impact of anemia on adolescent girls is stunted growth, easily infected, decreased academic achievement, becoming a high-risk prospective mother for pregnancy and childbirth. Anemia that occurs in women of childbearing age is a challenge in the field of reproductive health nutrition. With the development of technology in this day and age, it is certainly unfortunate if it is not used to provide positive values to the community. Therefore, the development of the AnemiaGo application for early detection of anemia is very important. This is done to increase public awareness about anemia and reduce the incidence of anemia early. The method used in this community service is planning and implementing activities consisting of introductions, counseling by providing education and training, giving Blood Additive Tablets (TTD) and assessing by giving pretest and posttest questionnaires. The results obtained from this activity are an increase in knowledge and attitudes in adolescents and WUS.
Web Platform for Automated Detection of Abnormal Red Blood Cells Using Computer Vision Qonitatul Hasanah; Zilvanhisna Emka Fitri; Victor Phoa; Dian Kartika Sari
International Journal of Healthcare and Information Technology Vol. 3 No. 2 (2026): January
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijhitech.v3i2.6718

Abstract

Accurate identification of red blood cell (RBC) morphological abnormalities is essential for anemia screening and hematological assessment; however, manual microscopic examination remains time-consuming, subjective, and highly dependent on expert availability. While recent deep learning studies have demonstrated promising accuracy in RBC classification, many focus primarily on model performance without addressing practical deployment constraints or system-level integration for routine laboratory use. In this study, a web-based prototype system for automated RBC abnormality classification is proposed using a lightweight MobileNetV2 architecture. The dataset consisted of 1,320 microscopic blood smear images collected from Klinik & Laboratorium Parahita in Jember and Surabaya, covering six RBC categories with balanced class distribution. All images were anonymized and verified by a certified clinical pathologist prior to use. The model was trained using transfer learning and evaluated on a held-out test set to assess generalization performance. The proposed model achieved a test accuracy of 89.77%, with consistent precision, recall, and F1-score across classes, indicating reliable multi-class classification performance. Analysis of misclassified samples revealed uncertainty primarily between morphologically similar RBC types, reflected by lower confidence scores. These results demonstrate that lightweight deep learning models can provide effective and efficient support for RBC morphology analysis when integrated into an accessible web-based system. The proposed approach contributes a deployment-oriented diagnostic support tool that has the potential to assist laboratory professionals by improving screening efficiency and consistency while preserving clinical oversight.
Analisis Spasial Intensitas Kasus Hipertensi untuk Identifikasi Wilayah Prioritas Intervensi Kesehatan di Kabupaten Probolinggo Berbasis QGIS Dian Kartika Sari; Iwan Abdi Suandana; Malinda Capri Nurul Satya; Mochammad Choirur Roziqin
Community Engagement and Emergence Journal (CEEJ) Vol. 7 No. 2 (2026): Community Engagement & Emergence Journal (CEEJ)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ceej.v7i2.11735

Abstract

Hipertensi merupakan salah satu penyakit tidak menular yang masih menjadi masalah kesehatan masyarakat karena prevalensinya terus meningkat. Hipertensi didefinisikan sebagai kondisi tekanan darah ≥140/90 mmHg yang dapat meningkatkan risiko penyakit jantung, stroke, dan gangguan ginjal. Distribusi kasus hipertensi yang tidak merata antarwilayah menuntut adanya pendekatan analisis spasial untuk mengidentifikasi wilayah dengan intensitas kasus tinggi sebagai dasar penentuan prioritas intervensi kesehatan. Penelitian ini bertujuan untuk menganalisis intensitas spasial kasus hipertensi dan mengidentifikasi wilayah prioritas intervensi kesehatan di Kabupaten Probolinggo berbasis aplikasi QGIS. Penelitian ini menggunakan desain kuantitatif deskriptif dengan pendekatan Sistem Informasi Geografis (SIG). Data penelitian berupa data sekunder jumlah kasus hipertensi per kecamatan tahun 2023 yang diperoleh dari Dinas Kesehatan Kabupaten Probolinggo serta data batas administrasi wilayah dalam format shapefile. Analisis dilakukan melalui tahapan data cleaning, join attribute, perhitungan Indeks Intensitas Kasus Hipertensi (IIKH) menggunakan normalisasi Min–Max, klasifikasi intensitas kasus dengan metode Natural Breaks (Jenks), dan visualisasi peta tematik. Hasil penelitian menunjukkan nilai Indeks Intensitas Kasus Hipertensi tertinggi terletak di Kecamatan Tongas (IIKH=1) dan Kecamatan Sukapura terendah (IIKH=0). Sebanyak 2 kecamatan termasuk kategori sangat tinggi, yaitu Tongas dan Leces, serta 3 kecamatan berada pada kategori tinggi, yaitu Gending, Sumberasih, dan Banyuanyar. Analisis spasial berbasis QGIS efektif untuk memetakan intensitas kasus hipertensi dan mendukung penentuan prioritas intervensi kesehatan berbasis wilayah secara objektif.
Co-Authors Bernadus Gunawan Sudarsono Mochammad Choirur Roziqin Nur Azis Purwo Agus Sucipto Putri Ariatna Alia Qonitatul Hasanah Sabran Sabran Satya, Malinda Capri Nurul Suandana, Iwan Abdi Victor Phoa Zilvanhisna Emka Fitri