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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Biosains Pascasarjana Martabe : Jurnal Pengabdian Kepada Masyarakat Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Masyarakat IPTEKS JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Discovery : Jurnal Ilmu Pengetahuan Jurnal Cafetaria Journal of Community Development Journal of Computer Science and Informatics Engineering Jurnal Ilmu Komputer The Journal of System Engineering and Technological Innovation Smart Techno (Smart Technology, Informatic and Technopreneurship) Jurnal Aplikasi Sistem Informasi dan Elektronika Modem : Jurnal Informatika dan Sains Teknologi ABDIMASTEK JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Computing and Information System Journal
Arifianto, Deni
Universitas Muhammadiyah Jember
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Analisis Sentimen Polemik Kebijakan Pemerintah Makan Siang Gratis pada Twitter Menggunakan Metode Neural Network Classification Dandy Tri Prasetyo; Deni Arifianto; Reni Umilasari
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.924

Abstract

This study aims to investigate public sentiment toward the Indonesian government's free lunch program by analyzing discussions on the X social media platform. A total of 1,500 tweets were collected through a web scraping process using relevant keywords and hashtags. The research workflow consisted of text preprocessing, including data cleaning, case folding, tokenization, stop-word removal, and stemming. The processed text was then transformed into numerical features using the Term Frequency–Inverse Document Frequency (TF-IDF) weighting method, followed by sentiment classification using the Neural Network Classification algorithm. Model performance was evaluated through K-Fold Cross Validation and a Confusion Matrix based on accuracy, precision, recall, and F1-score metrics. To address the issue of class imbalance, Random Over Sampling (ROS) was applied before the classification stage. The experimental results indicate that incorporating ROS improved the classification performance compared with the model trained on the original imbalanced dataset. Furthermore, the Neural Network Classification model effectively categorized public opinions into positive, negative, and neutral sentiments. The findings of this study are expected to provide valuable insights for policymakers in understanding public perceptions of the free lunch program and supporting future policy evaluation.
Topic Analysis in Political Speech Video Transcripts Using the Latent Dirichlet Allocation (LDA) Method Dhea Intan Septiara; Deni Arifianto; Wiwik Suharso
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 11 No. 1 (2026): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v11i1.4044

Abstract

Political speeches are an important medium for conveying a country’s leader’s vision, mission, and policy directions to the public. This study aims to identify and analyze the main topics in the video transcripts of President Joko Widodo’s political speeches during the 2014–2024 period using the Latent Dirichlet Allocation (LDA) method. The data consist of 185 press conference speech videos obtained from the Indonesian Cabinet Secretariat’s YouTube channel and converted into text using speech-to-text technology. The dataset is divided into 81 videos from the 2014–2023 period as training data and 104 videos from 2024 as testing data. The analysis process includes text preprocessing, rule-based automatic labeling, LDA model training, and evaluation using coherence score and perplexity. The results show that in the training data, the topics of Infrastructure and Economy are the dominant topics, reflecting the government’s focus on physical development and economic growth. In contrast, in the 2024 testing data, Healthcare emerges as the most dominant topic, followed by the topics of Infrastructure, Economy, Education, and Technology. The Infrastructure topic consistently achieves the highest coherence score of 0.85, indicating strong semantic consistency among its constituent terms. This study contributes to understanding the temporal dynamics of political communication and demonstrates the effectiveness of LDA in analyzing political speech data derived from video transcripts.
Inovasi Pengembangan Web Sekolah Dan Media Pembelajaran Interaktif Dalam Kurikulum Merdeka SD Muhammadiyah Kaliwates Jember Wiwik Suharso; Trias Setyowati; Deni Arifianto; Wahju Dyah Laksmi Wardhani
Journal of Community Development Vol. 6 No. 2 (2025): Desember
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v6i2.1476

Abstract

Revolusi Industri 4.0 mempengaruhi kebijakan pembelajaran pada satuan pendidikan dasar. Pendidik merancang pembelajaran interaktif agar dapat menghasilkan peserta didik yang berprestasi. Pemerintah menerapkan Kurikulum Merdeka 2022 untuk menguatkan karakter dan kompetensi peserta didik. Penerapan Kurikulum Merdeka menuntut pendidik memiliki kompetensi teknologi dan kurikulum. Kompetensi teknologi berfokus pada kemampuan TIK untuk menciptakan pembelajaran interaktif. Kompetensi kurikulum berfokus pada pengembangan capaian pembelajaran sesuai dengan tujuan pembelajaran dalam suatu mata pelajaran, dikenal sebagai Alur Tujuan Pembelajaran (ATP). Wawancara bersama mitra SD Muhammadiyah Kaliwates Jember menemukan permasalahan prioritas. Diantaranya adalah sebagian besar Guru kesulitan dalam menyusun dokumen ATP sesuai Kurikulum Merdeka, Tenaga Kependidikan (Tendik) tidak optimal memberikan dukungan teknologi, dan tidak tersedianya web sekolah sebagai media informasi dan promosi. Oleh karena itu, kegiatan pengabdian ini bertujuan mengembangkan web sekolah dan dokumen ATP untuk mendukung pembelajaran interaktif dan operasional sekolah. Tim Pelaksana telah melaksanakan sosialisasi program, pengembangan web sekolah, penyusunan dokumen ATP terdiri dari IPAS (IPA dan IPS), Matematika dan Bahasa Inggris, pendampingan pengelolaan web sekolah dan implementasi dokumen ATP dalam pembelajaran, pemberian LCD Proyektor. Hasil kegiatan ini berupa web sekolah dan dokumen ATP yang mengintegrasikan profile sekolah, penerimaan peserta didik baru, ensiklopedia, dan pembelajaran berbasis dokumen ATP. Tim pelaksana sebagai pendamping, sedangkan Guru dan Tendik sebagai peserta. Metode pelatihan, pendampingan dan penugasan digunakan sebagai pendekatan yang efektif. Kegiatan ini berhasil memenuhi tujuan dan luaran yang diharapkan, dan peningkatan kualitas pembelajaran dan promosi sekolah
Integrating Word Embeddings and IMDb Web Scraping for Keyword-Based Movie Recommendation Andani Chacha Cahya Dewi; Deni Arifianto; Nanda Kurnia Wardati
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1839

Abstract

The rapid growth of the film industry and streaming platforms has led to information overload and filter bubbles that make it difficult for users to find content matching their narrative preferences. Prior content-based filtering approaches relying on word-frequency methods (TFIDF) suffer from a semantic gap and commonly depend on a single public dataset and a reference title (seed movie) as input. This study combines a public dataset with IMDb web-scraping results (a maximum population of 5,000 titles) and applies a Skip-gram Word2Vec model to represent movie synopses as 200-dimensional semantic vectors, paired with Cosine similarity to measure the closeness between a user's free-text keyword and movie synopses without requiring a seed movie. Data were split using an 80:20 Holdout method, and algorithm performance was evaluated on a Top-3 Recommendation window using Precision@K, Recall@K, and Mean Reciprocal Rank (MRR), with ground truth validated by two experts through Inter-Annotator Agreement. Testing on 25 queries produced a Precision@3 of 0.5333, Recall@3 of 0.7800, and MRR of 0.7300. These results indicate that integrating word embeddings with web scraping yields semantically relevant movie recommendations from free keyword input, though comparisons with baseline methods are needed for more definitive performance claims
Analisis Implementasi SEO (Search Engine Optimization) dalam Kebutuhan Promosi Online pada Website Masteriwak.id Achmad Haris; Mohammad Dasuki; Deni Arifianto
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Digital marketing is the main key in reaching a wider market in the digital era, especially through the use of websites. This research focuses on the implementation of Search Engine Optimization (SEO) to increase the visibility of the Masteriwak.id website, a platform engaged in online koi fish sales. This research uses a quantitative approach with the main stages being an initial performance audit, on-page and off-page SEO optimization, and evaluation of results using Google Search Console and SERPRobot. On-page SEO optimization involves improving internal elements such as meta title, meta description, and website speed, while off-page SEO focuses on strengthening backlinks from quality external sources. The implementation results show a significant increase in impressions, clicks, and keyword rankings on SERPs. For example, the keyword “where to sell koi fish nearby” rose from no rank to position 13 with 35 impressions and 4 clicks. Statistical evaluation using paired-samples t-test shows the difference before and after SEO optimization. The t-test values for the impression parameters were -1.641 (p = 0.243), clicks -2.524 (p = 0.128), and SERP rank -2.535 (p = 0.127), which showed improvement but not yet statistically significant. This study confirms the importance of systematically implementing SEO, although continuous optimization is still required for maximum results.
Co-Authors Abadi, Taufan Abd. Rohman Fahruddin Abdullah, M. Hasan Achmad David Mico Achmad Haris Adi Cahyanto, Triawan Adi Sulistyono Agil Dwi Saputra Agung Nilogiri Ahmad Amrul Muyassir Ahmad Haris aji brahma nugroho, aji brahma Aji, Alif Syadillah Amaliah, Ulfi Rizqi Andani Chacha Cahya Dewi Astria Hindratmo Ayu, Wanda Afrilia A`yun, Qurrota Dandy Tri Prasetyo Dasuki, Moh. Dhea Intan Septiara Eko Wahyudi Elok Rahmawati Erna Cholida, Ferdy Maulana Fadila Oktaviana, Kadek Fariz, Muhammad Ivan Gatot Susanto Hartono, Ahmad Dedi Himawan Ganjar Prabowo Khailla Savana, Bella Risma Khusnul Ain Miftah Chatibul Umam Moh Dasuki, Moh Dasuki Moh. Dasuki Muchtar, Nabillah Ufairoh Muharom, Lutfi Ali Murwanti, Retno Nanang Saiful Rizal Nanda Kurnia Wardati Nitya S, Putu Nirvanda Octavia, Chendrasari Wahyu Onny Purnamayudhia Pangestu, Dwi Saka Pater, Dewi Lusiana Pradana Aryanto, Risqi Pradina K, Renny Qurrota A'yun Qurrota A`yun Qurrota A’yun Rahayu, Yeni Dwi Ramadhayanti Saputro, Safitri Renny Pradina K Rivansyah, Muhammad Saifudin, Ilham Saputro, Safitri Ramadhayanti Sari, Wina Ayunda setiyandi, aditiya Sinta Bella Criska Suharso, Wiwik Sulistyo, Henny Wahyu Suryani Dyah Astuti Susanto, Tony Dwi Suwondo, Ampar Jaya Tony Dwi Susanto Trias Setyowati Triawan Adi Cahyanto Umam, Miftah Chatibul Umilasari, Reni Wahju Dyah Laksmi Wardhani Wahyuni Adriani, Sri Warisaji, Taufik Timur Wiwik Suharso Yaqubi, Ahmad Khalil Yeni Dwi Rahayu Yonatan Yuliasih Kripsiandita Zakiyyah, Amalina Maryam Zakiyyah, Amalina Maryam