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Andi Yusika Rangan
STMIK Widya Cipta Dharma
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Perancangan Iklan Layanan Masyarakat Tentang Pola Hidup Sehat Menggunakan Media Animasi 2 Dimensi Kevin Dwi Aristo; Jundro Daud Hasiholan; Andi Yusika Rangan
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 3 (2025): Juni 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i3.9047

Abstract

Abstrak - Perancangan iklan layanan masyarakat tentang pola hidup sehat menggunakan media animasi 2 dimensi bertujuan untuk meningkatkan kesadaran masyarakat tentang pentingnya menerapkan pola hidup sehat yang menarik dan mudah dipahami. Media animasi 2 dimensi dipilih karena kemampuannya dalam menyajikan pesan edukatif melalui visual yang atraktif dan narasi yang interaktif, sehingga mampu menjangkau berbagai kalangan usia, khususnya anak-anak dan remaja. Proses perancangan ini meliputi tahapan pra-produksi, produksi, dan pasca produksi. Iklan ini dirancang untuk menyampaikan pesan penting seperti mengkonsumsi makanan bergizi seimbang, aktivitas fisik, serta istirahat yang cukup dalam bentuk cerita fiktif yang  diperankan oleh karakter animasi 2 dimensi, Pengujian efektivitas iklan dilakukan melalui survei kepada masyarakat umum, yang akan menunjukkan hasil positif dengan tingkat penerimaan dan pemahaman yang tinggi. Dengan demikian, iklan layanan masyarakat berbasis animasi 2 dimensi ini terbukti efektif sebagai media sosialisasi pola hidup sehat yang menarik dan mudah diakses oleh masyarakat luas.  Kata kunci: Animasi 2 Dimensi; Pola Hidup Sehat; Iklan Layanan Masyarakat. Abstract - The design of a public service announcement (PSA) about healthy lifestyles using 2D animation media aims to increase public awareness regarding the importance of adopting a healthy lifestyle in an engaging and easily understandable manner. 2D animation media was chosen for its ability to present educational messages through attractive visuals and an engaging narrative, enabling it to reach various age groups, particularly children and teenagers. This design process encompasses pre-production, production, and post-production stages. This advertisement is designed to convey crucial messages such as consuming balanced nutritious food, engaging in physical activity, and getting adequate rest, presented as a fictional story portrayed by 2D animated characters. Testing the advertisement's effectiveness was conducted through surveys administered to the general public, which indicated positive results with high levels of acceptance and comprehension. Thus, this 2D animation-based public service announcement proves effective as an engaging and easily accessible medium for promoting healthy lifestyles to the wider community.Keywords: 2D Animation; Healthy Lifestyle; Public Service Announcement.
Comparison Analysis of K-Nearest Neighbor and Naïve Bayes Methods in Classifying Academic Reference Books Chandra Panca Wibawa; Heny Pratiwi; Andi Yusika Rangan
Poltanesa Vol 26 No 2 (2025): December 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v26i2.3556

Abstract

This study compares the performance of the K-Nearest Neighbor (KNN) and Multinomial Naïve Bayes (MNB) algorithms in classifying academic reference books based on their titles within the STMIK Widya Cipta Dharma library system. A dataset consisting of 2,153 cleaned book records was processed using the Knowledge Discovery in Databases (KDD) framework, including data selection, preprocessing, transformation, and classification. Book titles were normalized and transformed into numerical features using TF-IDF with unigram and bigram extraction. The dataset was split using a 75%–25% ratio, resulting in 1,614 training samples and 539 testing samples. Experimental results show that the KNN classifier achieves an accuracy of 72.72%, outperforming Multinomial Naïve Bayes with an accuracy of 62.70%. Confusion matrix analysis shows that KNN correctly classifies more book titles across categories. The superior performance of KNN is attributed to the sparse and short-text nature of book titles, which benefits distance-based similarity. These findings highlight the potential of machine-learning-based automated classification to improve cataloging and information retrieval in academic libraries.
Co-Authors Ahmad Kholil Amelia Yusnita Amelia Yusnita Basrie Chandra Panca Wibawa Daud, Jundro Hendy Heny Pratiwi Kevin Dwi Aristo M. Irwan Ukkas Irwan Ukkas Ukkas Mardianus Muhammad Awaludin Presa Taruna Oliver Salmon Salmon Siti Lailiyah Siti Qomariah Siti Qomariah