Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal ANTHROPOS: JURNAL ANTROPOLOGI SOSIAL DAN BUDAYA (JOURNAL OF SOCIAL AND CULTURAL ANTHROPOLOGY) Jurnal Nasional Teknologi Komputer Economic: Journal Economic and Business The Journal of Information Technology, Computer Science, and Electrical Engineering
Sri Wahyuni
universitas negeri medan
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences Other

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

Found 4 Documents
Search

 1 
Studi Komperatif Analisis UU Transportasi Konvensional dan Peraturan Menteri Perhubungan Nomor 108 Tahun 2017 di Kota Medan Sri Wahyuni; Fitri Andriyani; Dedek Andriani; Liber Siagian
Anthropos: Jurnal Antropologi Sosial dan Budaya (Journal of Social and Cultural Anthropology) Vol 4, No 1 (2018): Anthropos
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/antro.v4i1.10069

Abstract

Penelitian ini dilakukan di Desa, Sei Kera Hilir I Jalan Pimpinan Nomor 70 Medan Perjuangan. Penulis ingin mengetahi tentang adakah dampak yang terjadi antara UU transportasi konvensional dan Peraturan Menteri Perhubungan Nomor 108 Tahun 2017  dalam kenyamanan berlalu lintas pada masyarakat di Desa, Sei Kera Hilir I Jalan Pimpinan Nomor 70 Medan Perjuangan. Metode penelitian ini dilakukan dengan menggunakan metode kuantitatif. Dimana penggalian data menggunakan instrumen angket, dan studi pustaka, pengambilan sampel diambil secara acak (random Sampling). Variabel penelitian ini adalah variabel tunggal. Berdasarkan penelitian, diketahui bahwa untuk mengakses transportasi online lebih mudah dibandingkan transportasi Konvensional yang dilihat dari angka persentasi lebih tinggi.
Development of a Cloud-Native Student Activity Management Information System at Politeknik Negeri Medan Darmeli Nasution; Indri Sulistianingsih; Alex Sandro Dabukke; Sri Wahyuni; Bayu Putra Pratama
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 3 (2025): October 2025 - January 2026
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i3.241

Abstract

Politeknik Negeri Medan, like many higher education institutions in Indonesia, encounters persistent challenges in managing non-academic student activities due to fragmented data repositories, inconsistent reporting mechanisms, and manual administrative workflows. This study proposes the design of a cloud-native Student Activity Management Information System (SAMIS) engineered to streamline the processes of planning, monitoring, verification, and evaluation of extracurricular activities. The system adopts a microservices-based architecture supported by containerization, Kubernetes orchestration, and CI/CD pipelines to ensure scalability, resilience, and operational efficiency. Key functional modules include proposal submission, multi-level review workflows, real-time activity tracking, and centralized document management. Although the system has not yet been implemented, architectural simulations, workflow modelling, and comparative analysis with previous studies indicate strong potential for improving institutional governance and supporting data-driven decision-making. The proposed design also aligns with contemporary digital transformation initiatives in higher education. Future work includes prototype development, pilot testing, and comprehensive user evaluation to validate performance in real-world contexts.
Implementing Digital Marketing to Increase the Income of MSMEs in Suka Aren Dalig Raya Lenti Susanna Saragih; Aurora Elise Putriku; Sabda Dian Nurani Siahaan; Jufri Darma; Sri Wahyuni
Economic: Journal Economic and Business Vol. 4 No. 4 (2025): ECONOMIC: Journal Economic and Business
Publisher : Lembaga Riset Mutiara Akbar (LARISMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejeb.v4i4.1254

Abstract

This research was conducted in Dalig Raya Village to improve the effectiveness of digital marketing for micro, small, and medium enterprises (MSMEs) in Suka Aren, Dalig Raya. The research used a 4D model. The Define stage was used to identify conventional marketing constraints that limit market reach. The Design stage included designing a digital marketing strategy through social media platforms like Facebook, Instagram, TikTok, and the Shopee e-commerce platform. The Develop stage involved creating visual content, collaborating with influencers, and utilizing interactive features. The Disseminate stage included content publication, sales monitoring, and evaluating the effectiveness of each platform. The results showed an average increase in revenue before and after digital marketing implementation of 43.04% within a three-month trial period. Shopee contributed the highest sales channel due to the integration of social media accounts with the business's e-commerce account. During the development process, TikTok was found to be the highest-performing social media platform with 14,200 content views, followed by Instagram with 2,502 viewers, and Facebook with 150 viewers. Facebook was effective in building communication and education, Instagram and TikTok excelled in increasing brand awareness, while Shopee served as the primary channel for sales conversion. Multi-channel strategies have been proven to increase brand awareness, drive sales, and have an impact on increasing the income of MSMEs.
Model Explainable Machine Learning pada Aplikasi Nutrisiaga untuk Prediksi Risiko Stunting di Wilayah Pascabencana Sri Wahyuni; Wiwin Handoko; Hadijah; Muhammad Hafiz; Rizty Maulida Badri
Jurnal Nasional Teknologi Komputer Vol 6 No 2 (2026): April 2026
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v6i2.442

Abstract

Stunting merupakan masalah gizi kronis yang berpotensi meningkat pada periode pascabencana akibat terganggunya akses pangan, layanan kesehatan, sanitasi, serta meningkatnya kerentanan kelompok anak. Dalam kondisi tersebut, diperlukan kemampuan untuk memprediksi risiko stunting secara lebih dini agar intervensi gizi darurat dapat ditetapkan secara tepat sasaran. Penelitian ini mengembangkan Model Explainable Machine Learning pada aplikasi Nutrisiaga untuk memprediksi risiko stunting di wilayah pascabencana dengan pendekatan yang transparan bagi tenaga kesehatan. Model prediksi dibangun menggunakan tiga algoritma, yaitu Random Forest, XGBoost, dan Neural Network, yang dilatih dengan fitur terkait karakteristik anak dan faktor pendukung di lingkungan pascabencana. Untuk mengatasi keterbatasan interpretasi dari model berbasis machine learning, penelitian ini mengintegrasikan Explainable AI (XAI) menggunakan metode SHAP dan LIME sebagai alat interpretabilitas. SHAP digunakan untuk mengukur kontribusi tiap fitur terhadap hasil prediksi, sedangkan LIME digunakan untuk memberikan penjelasan lokal pada contoh data tertentu sehingga pengguna dapat memahami alasan model pada kasus yang spesifik. Hasil pengujian menunjukkan bahwa model dapat memberikan prediksi risiko stunting yang terukur, sementara visualisasi dan skor interpretasi dari SHAP serta LIME membantu pengguna dalam mengidentifikasi faktor dominan yang memengaruhi prediksi. Dengan demikian, penelitian ini berkontribusi pada pengembangan aplikasi nutrisi yang tidak hanya mampu memprediksi risiko stunting, tetapi juga menyediakan penjelasan yang mendukung pengambilan keputusan intervensi gizi darurat secara lebih akuntabel dan dapat dipahami.
Co-Authors Alex Sandro Dabukke Bayu Putra Pratama Darmeli Nasution Dedek Andriani Fitri Andriyani Hadijah Indri Sulistianingsih Jufri Darma Lenti Susanna Saragih Liber Siagian Muhammad Hafiz Putriku, Aurora Elise Rizty Maulida Badri Sabda Dian Nurani Siahaan Wiwin Handoko