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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan
Caroline Caroline
Universitas Mikroskil
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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MULTICLASS CLASSIFICATION FOR STUNTING PREDICTION USING DEEP NEURAL NETWORKS Wulan Sri Lestari; Yuni Marlina Saragih; Caroline Caroline
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 2 (2024): JITK Issue November 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i2.5636

Abstract

Stunting is a chronic nutritional issue that hinders child growth and leads to serious long-term health and developmental impacts, particularly in developing countries. Therefore, early and accurate prediction of stunting is crucial for implementing effective interventions. This research aims to develop a multiclass classification model based on Deep Neural Networks (DNNs) to predict stunting status. The model is trained using a comprehensive dataset that encompasses various health variables related to stunting. The research process includes data collection, data preprocessing, dataset splitting, and training and evaluation of the DNNs model. The model can classify stunting status into four categories: stunted, severely stunted, normal, and tall. Further analysis is conducted to evaluate the influence of various parameters on the model's performance, including dataset splitting ratios (80:20 and 70:30) and learning rates (0.001, 0.0001, and 0.00001). The results show that a learning rate of 0.0001 yields the highest prediction accuracy, at 93.64% and 93.83% for the two data-splitting schemes. This indicates that this learning rate has achieved an optimal balance between convergence speed and the model's generalization capability. Additionally, the developed DNNs model can identify complex patterns hidden within the data without being affected by noise. These findings confirm that appropriate parameter selection, particularly the dataset splitting ratio and learning rate, can significantly enhance the DNNs model's ability to identify complex data patterns.
Pemasangan jaringan komputer untuk peningkatan pembelajaran pada Yayasan Perguruan Letjen Haryono MT Caroline Caroline; Apriyanto Halim; Khairul Hawani Rambe
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 5 (2025): September
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i5.33603

Abstract

Abstrak Yayasan Perguruan Letjen Haryono MT. merupakan institusi sekolah swasta yang bergerak di bidang pendidikan mulai dari tingkat TK sampai SMA. Kendala yang dihadapi oleh mitra adalah jaringan komputer yang sering mengalami gangguan dengan rata-rata 2–3 kali setiap minggu dan durasi downtime sekitar 5–10 menit per kejadian. Gangguan ini berdampak pada proses belajar mengajar di laboratorium lama yang hanya memiliki 20 unit komputer aktif. Kondisi tersebut mengakibatkan keterlambatan praktik, berkurangnya efektivitas pembelajaran, dan ketidaknyamanan siswa. Tujuan dari kegiatan ini adalah untuk menciptakan laboratorium komputer yang baru dengan pemasangan jaringan yang baik sehingga dapat mendukung operasional sekolah. Adapun metode yang digunakan dalam kegiatan ini meliputi pengumpulan kebutuhan mitra, pembangunan sketsa pemasangan jaringan, menyiapkan alat dan bahan yang diperlukan, memasang kabel UTP ke konektor RJ45, konfigurasi jaringan LAN, pengujian jaringan LAN, implementasi sesuai sketsa, dan pemeliharaan. Hasil dari pengabdian ini sesuai dengan tujuan kegiatan yaitu terbentuknya laboratorium komputer baru dengan instalasi ulang jaringan yang menerapkan topologi bintang. Penggunaan laboratorium tidak terlepas dari pengguna yang mengoperasikannya. Oleh sebab itu, disarankan agar perangkat komputer dan kabel yang ada dijaga dan dirawat dengan baik. Kata kunci: jaringan; local area network; pengabdian; topologi bintang. Abstract Yayasan Perguruan Letjen Haryono MT. is a private educational institution that provides learning services from kindergarten to senior high school levels. The main problem faced by the partner is the instability of the computer network, which experiences an average of 2–3 disruptions per week with a downtime duration of approximately 5–10 minutes per incident. This disruptions significantly hampers the teaching and learning process in the old computer laboratory, which was limited to 20 active computer units. This condition causes delays in practical sessions, reduced learning effectiveness, and student inconvenience. The purpose of this community service activity is to establish a new computer laboratory with a properly installed network to support the school’s operational activities. The methods implemented in this activity include collecting partner requirements, designing a network installation sketch, preparing the necessary tools and materials, crimping UTP cables to RJ45 connectors, configuring the LAN, testing the LAN, implementing the network design, and conducting maintenance. The results of this activity successfully achieved the objectives, namely the development of a new computer laboratory with a reinstalled network using a star topology. Since the laboratory usage depends on users, it is recommended that computers and cables be properly maintained to ensure long-term functionality. Keywords: network; local area network; service; star topology.
Co-Authors Apriyanto Halim Khairul Hawani Rambe Wulan Sri Lestari Yuni Marlina Saragih