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All Journal Riau Journal of Computer Science JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science GANDRUNG: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) ARSY : Jurnal Aplikasi Riset kepada Masyarakat Bulletin of Information Technology (BIT) Jurnal Ilmiah MADIYA: Masyarakat Mandiri Berkarya International Journal of Science and Society (IJSOC) Jurnal Sains dan Teknologi Internasional Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Engineering Science Letter JENTIK Komposit : Jurnal Pengabdian Dan Pemberdayaan Masyarakat Electronic Integrated Computer Algorithm Journal JGEN : Jurnal Pengabdian Kepada Masyarakat Jurnal Kecerdasan Buatan dan Teknologi Informasi Journal of Computer Science Advancements
Yuyun Yusnida Lase
Politeknik Negeri Medan
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Optimization Performance of Extreme Gradient Boosting and Random Forest for Child Stunting Classification Based on Economic Factors Lase, Yuyun Yusnida; Putra, Purwa Hasan; Lubis, Arif Ridho; Prayudani, Santi
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5864

Abstract

Stunting remains a major health concern in Indonesia due to its impact on children’s physical growth and cognitive development. One of the factors influencing the incidence of stunting is family economic status, which is linked to access to nutrition, sanitation, and a healthy environment. This study aims to optimize the performance of the XGBoost and Random Forest algorithms in classifying stunting in children based on economic factors and to compare the performance of the two models. The methods used in this study involve a machine learning approach, including data preprocessing, model training, hyperparameter optimization, and performance evaluation using a confusion matrix, accuracy, precision, recall, F1-score, and ROC-AUC curves. The results indicate that both algorithms perform well in classification, with an accuracy rate of approximately 70%. The Random Forest model demonstrated better performance than XGBoost with an AUC value of 0.7655, while XGBoost had an AUC value of 0.75. Additionally, the feature importance results indicated that economic and environmental factors, such as housing conditions and sanitation, have a significant influence on the incidence of stunting.
The Community Partnership Service Utilization of Social Media for Promoting Binjai Batik Products at UMKM Tan Collection, Binjai District, Binjai City, North Sumatra Yuyun Yusnida Lase; Andam Lukcyhasnita; Santi Prayudani; Harizahayu; Friendly
GANDRUNG: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2026): GANDRUNG: Jurnal Pengabdian Kepada Masyarakat
Publisher : Fakultas Olahraga dan Kesehatan, Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/gandrung.v7i1.6332

Abstract

The creative economy serves as a vital platform for promoting and preserving local cultural heritage. UMKM Tan Collection, a creative enterprise producing Binjai's signature "rambutan batik," faces significant marketing challenges as the sole producer of handcrafted rambutan batik in the city. Digital visibility remains particularly low, with minimal online information and motif documentation compared to other batik varieties, resulting in unstable market demand. This community service program aims to enhance the digital promotion and sales of rambutan batik through social media content creation training. The methodology includes problem identification, CapCut video editing workshops, content development assistance, and implementation evaluation. Results demonstrate improved digital literacy among artisans, creation of engaging social media content, and enhanced online brand visibility. The program successfully established a sustainable digital marketing framework, enabling continuous product promotion and cultural preservation through digital platforms.
Analisis Deteksi Penyakit Daun Pisang Menggunakan Ekstraksi Fitur CNN (MobileNetV2) dan Klasifikasi SVM Yuyun Yusnida Lase; Lampson Pindahaman Purba; Santi Prayudani; Arif Ridho Lubis; Hikmah Adwin Adam
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 6 (2025): Desember 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i6.6590

Abstract

Banana plants (Musa spp.) are one of the leading horticultural commodities in Indonesia that have high economic value and play an important role in national food security. However, banana productivity often decreases due to attacks by various diseases such as Sigatoka, Cordana, and Pestalotiopsis infections that can spread quickly. Early detection of these diseases is crucial to prevent greater losses. This study aims to develop a banana plant disease detection system based on digital image processing with the Support Vector Machine (SVM) algorithm. The research method includes the stages of banana leaf image acquisition, pre-processing using color segmentation, color and texture feature extraction, and disease type classification with the SVM algorithm. The test results show that the developed system is able to recognize banana leaf diseases with an accuracy of 97.8%, precision of 97%, and recall of 98%. These findings prove that the application of digital image processing and the SVM algorithm is effective in detecting banana plant diseases. This system is expected to be a fast, efficient, and accurate diagnostic tool for farmers to increase the productivity and quality of banana harvests.
Co-Authors Adwin Adam , Hikmah Ainul Hizriadi Al Khowarizmi Alex Sander Sitepu Andam Lukcyhasnita Asmara, Wira Bayu Citra Wasti Silaban F. Friendly Fatmi, Yulia Fildzah Nadiah Friendly Friendly, Friendly Gabriel Ardi Hutagalung Hamdi , Khairil Harfita, Nur Laily Harizahahyu Harizahayu Harizahayu, Harizahayu Harris Aminuddin Haryadi Haryadi - Hikmah Adwin Adam Husna, Meryatul Julham Julham Lampson Pindahaman Purba Lubis, Arif Ridho Mahulae, Doni Ganda Marbungaran Muhammad Fathoni Muhammad Luthfi Hamzah Muharman Lubis Nauli, Arif Aryaguna Prayudani, Santi Putra, Purwa Hasan Ramdani Safitri, Habibi Reza Kavarin Telaumbanua Samuel Cristian Saragih Silaban, Citra Wasti Sitepu, Alex Sander Syafli, Sekar Arini Syamsul Arifin Telaumbanua, Reza Kavarin Yohannes Christian Gurning Yulia Fatmi Yulia Fatmi