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All Journal Jurnal Pendidikan Anak Usia Dini Undiksha JOIV : International Journal on Informatics Visualization JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JISTech (Journal of Islamic Science and Technology) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Mantik Edunesia : jurnal Ilmiah Pendidikan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Sistem Pendukung Keputusan dengan Aplikasi Wahana Jurnal Pema Tarbiyah Jurnal Pengabdian kepada Masyarakat (PEMAS) Jurnal Teknoinfo
Nanda Novita
Universitas Medan Area
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Public Health Social Sciences Other

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Animaker Animation Video Design as a Digital-Based Learning Media with the Theme of Comparison and Scale in Elementary School Yuan Anisa; Meilisa Malik; Tantri Octora Dwi Syah Putri; Muhammad Hafiz; Nanda Novita
Edunesia: Jurnal Ilmiah Pendidikan Vol. 4 No. 1 (2023)
Publisher : research, training and philanthropy institution Natural Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.873 KB) | DOI: 10.51276/edu.v4i1.328

Abstract

This study aimed to determine the effectiveness of developing digital-based teaching materials in Animaker-assisted animated videos aimed at grade V elementary school students on Comparison and Scale subject matter. This was done because problems often arise regarding the effectiveness of the teaching and learning process. Teachers have also been required to be active and creative in developing learning systems in the classroom that coexist with technological advances. In this study, the learning system developed is on teaching materials. This researcher uses the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). This research is subjected to elementary school students in Langkat Regency. Data collection is done using assessments by material experts, media experts, homeroom teachers, and students. Overall based on media experts reached 81.25%, material experts reached 81.25%, homeroom teachers reached an average of 82%, and the average student response of 87% was classified as high so that it could be stated that Animaker-based animation videos on Comparison and Scale materials were feasible to be used as teaching material facilities in the classroom.
Analysis of twitter user sentiment on the monkeypox virus issue using the nrc lexicon Muhammad Khahfi Zuhanda; Anil Hakim Syofra Syofra; Devy Mathelinea; Prana Ugiana Gio; Yuan Anisa Anisa; Nanda Novita
Jurnal Mantik Vol. 6 No. 4 (2023): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i4.3502

Abstract

Monkeypox virus is closely related to variola (smallpox virus) and causes a smallpox-like disease. The increase in monkeypox cases has caused the general public to be involved in providing responses to seek and share information related to monkeypox on the internet, especially on social media platforms. This study aims to analyze a collection of 5000 tweets on August 5, 2022, for sentiment analysis using the NRC lexicon. Of the 5,000 tweets that have been extracted, it is obtained that the words that Twitter users often use are "health", "emergency", "public", "covid", and "declares". By using the classification using the NRC lexicon comparison, we found that the emotion type of fear was the most widely used emotion, which had a presentation of 19.73%, followed by anticipation emotion at 16.78%, sadness 14.77%, trust at 13.90%, anger 9.99%, shock 9.14%, disgust 8.12%, and happy 1288 7.90 %. The negative sentiment that often appears on Twitter is equal to 51.92%, and positive sentiment has a percentage of 48.08%. The negative sentiment words that appear most often are "emergency", "virus", "disease", "shit", and "risk". The positive sentiment words that appear most often are "public", "vaccine", "sex", "contact", and "united". The analytical method with the lexicon method is very well used in analyzing various emotions and sentiments on social media. %MCEPASTEBIN%
Thematic-Based Interactive Learning Multimedia In Early Childhood Language Development Sholihatul Hamidah Daulay; Raisah Armayanti Nasution; Nanda Novita
Jurnal Pendidikan Anak Usia Dini Undiksha Vol. 11 No. 1 (2023): April
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/paud.v11i1.53469

Abstract

Language development still applies conventional learning without using learning media such as interactive learning multimedia. So this study aims to develop thematic-based interactive learning multimedia in early childhood language development. This research belongs to the type of ADDIE development model development research. The subjects involved in this study were material experts, media experts, and 83 early childhood children—data collection using the method of observation, interviews, and questionnaires. The research instrument used was the validity sheet. The data obtained in the study were then analyzed using a descriptive presentation analysis with a questionnaire to experts to test the feasibility and analysis of the data to test the effectiveness of using the Normalized Gain test (N-gain score). The results of the data analysis show that the product feasibility test, with a percentage of 93.47% by material experts and 85.71% by media experts, is included in the very feasible category. The effectiveness test results have met the effective category seen from the acquisition of the average value according to the calculation of the N-Gain score. It was concluded that thematic-based interactive learning multimedia is valid and feasible to develop because it can maximize children's language development.
The Impact of k-means on Association Rules Mining Algorithms Performance Hasudungan, Andre; Muliono, Rizki; Khairina, Nurul; Novita, Nanda
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 5, No 2 (2024)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v5i2.20907

Abstract

Association Rule Mining (ARM) is one of unsupervised learning approach of machine learning. It acts as a data analysis technique that enables the identification of frequent patterns, correlations, associations, and causal structures within certain datasets. This method widely used in numerous studies and practices to explore knowledges and strengthen decision making. However, dealing a large dataset with high number of transactions may become the shortcoming for the ARM algorithms, such as Apriori, FP-Growth, and Eclat. It leads them to face several challenges, including computational complexity, long mining durations, and memory consumption. Hence, this paper proposes k-means clustering to generates several groups of data to handle the issue, then proceed the ARM algorithms for each individual produced cluster. The study used Elbow method and Silhouette Coefficient as the method to determining optimum number of clusters to be used. The result pointed out that k-means-ARM generates a greater number of rules and provides more contextually relevant and significant correlations. In term of Lift Ratio average score, the k-means-ARM shows the greater value rather than non k-means ARM. The k-means-ARM combination is robust; this approach improves the efficiency and scalability of ARM for large datasets and enhances the interpretability of the discovered association rules
Pengembangan Model Prediksi Harga Saham Dengan Menggunakan Regresi Linear Berganda Pada Saham BRI Anisa, Yuan; Hafiz, Muhammad; Novita, Nanda
JISTech (Journal of Islamic Science and Technology) Vol 9, No 2 (2024)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v9i2.22213

Abstract

Penelitian ini bertujuan untuk mengembangkan model prediksi harga saham menggunakan regresi linear berganda, dengan studi kasus pada saham PT Bank Rakyat Indonesia (Persero) Tbk. Data yang digunakan berasal dari Yahoo Finance dan PT Stockbit Sekuritas Digital, yang meliputi harga saham historis. Model regresi linear berganda digunakan untuk memprediksi harga saham di masa depan, dengan mengggunakan variabel independen mencakup harga pembukaan, harga tertinggi, harga terendah, dan net buy/sell asing, sedangkan untuk harga penutupan berperan sebagai variabel dependen. Hasil analisis menghasilkan persamaan regresi: Y = 1.725 - 0.529x₁ + 0.689x₂ + 0.840x₃ + 3.221E-8x₄, yang menunjukkan hubungan signifikan antara variabel independen terhadap harga penutupan saham. Penelitian ini memberikan wawasan bagi investor dan pelaku pasar untuk memahami faktor-faktor utama yang memengaruhi pergerakan harga saham, sehingga dapat digunakan sebagai alat bantu dalam pengambilan keputusan investasi. Model yang dihasilkan memiliki potensi untuk dioptimalkan lebih lanjut dengan melibatkan variabel makroekonomi dan teknik machine learning untuk meningkatkan akurasi prediksi.
Involvement of Various Selection Methods for Genetic Algorithms in Determining the Optimal Production Schedule Problem Muliono, Rizki; Silviana, Nukhe Andri; Novita, Nanda
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2632

Abstract

This research investigates using genetic algorithms (GA) to optimize production scheduling in Medan's shoe industry. The study compares traditional manual and First Come First Serve (FCFS) methods against a GA approach, incorporating selection variations such as Boltzmann, Fitness Uniform Selection Scheme (FUSS), Exponential Rank Selection, and Roulette Wheel Selection. The optimal production order is derived from the chromosome with the highest fitness. Results indicate that GA with FUSS selection significantly reduces production time from 73,630 minutes to 45,650 minutes, achieving a 35% improvement in efficiency. This optimization is attributed to FUSS’s ability to maintain a diverse population, preventing premature convergence and ensuring a broader solution for space exploration. Additionally, it was found that using a smaller population size relative to the number of generations yields better optimization results. The study also demonstrates that while Roulette Wheel Selection shows more variability, it achieves higher optimization over time than FCFS. The practical implications of these findings are substantial for the shoe industry, including faster production cycles, better resource allocation, and an enhanced ability to meet customer demands. These benefits are exemplified by implementing the SISPROMA application, an innovative production scheduling information system that leverages machine learning to optimize scheduling in the manufacturing industry. This study provides valuable insights into applying genetic algorithms for production scheduling, highlighting their potential to enhance operational efficiency and reduce costs. Future research should explore additional optimization techniques and real-world applications to validate and extend these findings, ensuring broader applicability and continuous improvements in manufacturing efficiency.
Classification Of Interest In Sports Using The Naive Bayes Classifier Method Lumbantobing, Martin; Novita, Nanda
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 3Spc (2025): Special Issues 2025: Innovations in Predictive Analytics and Sentiment Analy
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i3Spc.15054

Abstract

Interest in sports must be done from an early age and requires the right method to achieve the desired results, namely by using the Naive Bayes method. The purpose of this study was to explore the sports interests of students of SDN 3 Tarutung with the Naive Bayes method. The subjects of this study were students in grades 4, 5, and 6 of SDN Jenggolo Tuban who liked sports using data collection methods, namely the Naive Bayes method, Observation, Interviews and practical sports tests based on sport search, namely Height (TB), Sitting height (TD), Weight (BB), Arm span (RL), Tennis ball throw and catch (LTBT), Basketball throw (LBB), Vertical jump (LT), Agility run (LK), 60 meter sprint (L60M), and multi-stage run (MFT). The Naive Bayes modeling system is carried out in two phases, namely training data and testing data. The results of the study obtained were the results of the classification of each student who was talented in sports (football, volleyball, badminton, sprinting, swimming) or not talented in sports (football, volleyball, badminton, sprinting, and swimming). The results of the testing data showed that 7 students were talented in football, 2 students were talented in volleyball, 1 student was talented in badminton, 5 students were talented in sprinting, and 3 students were talented in swimming.
Analisis Fuzzy Inference System Mamdani untuk Menilai Kelayakan Pemilihan Mobil Berdasarkan Kriteria Pengguna Novita, Nanda; Firdaus, Muhammad Huda; Anisa, Yuan; Khairina, Nurul
JISTech (Journal of Islamic Science and Technology) Vol 10, No 1 (2025)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v10i1.23109

Abstract

Pengambilan keputusan pembelian mobil merupakan proses kompleks yang dipengaruhi oleh faktor subjektif dan objektif seperti harga, efisiensi bahan bakar, dan kenyamanan. Khusus bagi pengemudi transportasi online, kriteria seperti durabilitas dan biaya perawatan rendah menjadi krusial. Ketidakpastian preferensi linguistik (misalnya definisi "hemat" atau "nyaman") sering menjadi keterbatasan metode konvensional. Penelitian ini mengusulkan Sistem Inferensi Fuzzy Mamdani (FIS Mamdani) untuk memodelkan preferensi pengguna dan mengatasi ambiguitas tersebut. Dengan kemampuan menerjemahkan informasi linguistik ke dalam kaidah "IF-THEN" yang intuitif, FIS Mamdani memungkinkan interpretasi preferensi secara akurat. Berdasarkan data aktual mobil Toyota, sistem ini menggunakan tiga variabel input: Harga Mobil, Efisiensi Bahan Bakar, dan Kapasitas Mesin, dengan satu variabel output: Kelayakan Pembelian. Hasil penelitian menunjukkan bahwa dengan nilai crisp output 55.7 (pada kondisi Harga=450 juta, Efisiensi=18 km/l, Kapasitas Mesin=1.8L), mobil-mobil dengan kategori Cukup Layak adalah Toyota Avanza, Yaris, dan Rush. Pendekatan ini terbukti memberikan rekomendasi terstruktur dan personal, sekaligus mengurangi ketidakpastian dalam pengambilan keputusan pembelian mobil
Penyusunan Dokumen Kelayakan Pengembangan Kawasan Industri di Kabupaten Asahan Nasution, Aulia Muflih; Rambe, Yunita Syafitri; Novita, Nanda
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 6 No. 3 (2023): Juli 2023
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v6i3.2506

Abstract

Pengabdian ini dilakukan oleh kelompok dosen dengan bidang keahlian arsitektur dan informatika dalam rangka mengembangkan suatu kawasan industri di Kabupaten Asahan. Penelitian ini dilatarbelakangi oleh kebutuhan akan dokumen yang mengikat sebagai pedoman dalam pengembangan kawasan industri. Dalam pengembangan kawasan industri, terdapat banyak unsur dan kepentingan yang perlu dipertimbangkan, sehingga penting  adanya kebijakan dan dokumen pengembangan yang dapat menjadi dasar dalam proses pengembangan tersebut. Melalui dokumen ini, diharapkan pengembangan kawasan industri dapat mengurangi dampak negatif terhadap lingkungan dan masyarakat sekitarnya. Metode pengabdian yang digunakan meliputi metode survey dan wawancara kepada masyarakat yang dilakukan oleh tim tenaga ahli arsitektur, pengolahan data yang dilakukan oleh tenaga ahli informatika, dokumentasi, pembuatan dokumen, dan sosialisasi. Hasil dari pengabdian ini adalah dokumen pengembangan yang diserahkan kepada dinas terkait dan juga akan dipublikasikan dalam bentuk jurnal. Dengan adanya pengabdian ini, diharapkan akan tercipta suatu dokumen pengembangan yang komprehensif dan berdasarkan pada kepentingan dan kebutuhan masyarakat setempat. Dokumen ini dapat menjadi acuan dalam pengembangan kawasan industri di Kabupaten Asahan, serta memberikan manfaat dalam mengurangi dampak negatif terhadap lingkungan dan masyarakat sekitarnya.
Sistem Pendukung Keputusan Berbasis AHP untuk Pemilihan Hunian di Kawasan Perkotaan yang Padat Yessy Evita Leony Aruan; Nanda Novita
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 2 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i2.1289

Abstract

Home selection is a critical and complex decision, particularly in densely populated urban areas such as Medan, where multiple factors including location, price, facilities, and environmental risks must be considered simultaneously. This study aims to develop a Decision Support System model based on the Analytical Hierarchy Process (AHP) to assist prospective buyers in making more objective and structured housing decisions. The research evaluated 20 housing alternatives selected through purposive sampling. Assessments of criteria and alternatives were conducted by five respondents, consisting of two property experts, two information systems academics, and one experienced homebuyer, using pairwise comparison questionnaires based on the Saaty scale. The analysis reveals that Location holds the highest weight (0.6333), followed by Income/Property Price (0.2605), and Facilities (0.1062). At the sub-criteria level, Flood-Free Area emerged as the most influential factor with a weight of 0.3533, followed by Property Price (0.1954) and Safe Neighborhood (0.1668). Among the 20 alternatives, Cempaka Lestari ranked first with a score of 0.9040, closely followed by Griya Indah (0.9033) and Anggrek Residence (0.8930). The consistency ratio for all calculations was below 0.10, confirming the reliability and logical validity of the judgments. These findings emphasize that location-specific environmental criteria, particularly flood risk, play a decisive role in homebuyer preferences in Medan. Practically, the proposed model provides prospective buyers with a rational decision-making framework and offers strategic insights for developers to align housing products with market demands in flood-prone urban areas.
Co-Authors Amir Saleh Andre Hasudungan Lubis Anil Hakim Syofra Syofra Desniarti Devy Mathelinea Dian Noviandri Fadhillah Azmi Fadilla Azmi Firdaus, Muhammad Huda Hadijah Hadijah Hafiz, Muhammad Hasudungan, Andre Lumbantobing, Martin Mahliza Nasution Malik, Meilisa Maqhfirah DR Maqhfirah Maqhfirah Mufti Ali Nasution Muhammad Hafiz Muhammad Hafiz Muhammad Khahfi Zuhanda Muhammad Syifa Muhathir, Muhathir Nasution, Aulia Muflih Nurul Khairina Prana Ugiana Gio Rahman, Sayuti Raisah Armayanti Nasution Rambe, Yunita Syafitri Rizki Muliono Rizty Maulida Badri Saufa Yardha Moerni Sholihatul Hamidah Daulay Susilawati Susilawati Tantri Octora Dwi Syah Putri Yessy Evita Leony Aruan Yuan Anisa Yuan Annisa