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All Journal Jurnal Teknik Sipil ELT Forum: Journal of English Language Teaching Jurnal Pilar Nusa Mandiri IT JOURNAL RESEARCH AND DEVELOPMENT JMM (Jurnal Masyarakat Mandiri) Jurnal Nasional Komputasi dan Teknologi Informasi Abdi Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Community Empowerment Bulletin of Computer Science Research Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Pengabdian Masyarakat Bhinneka Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Sains Student Research Jurnal of Information Technology and Society (JITS) Jurnal Ilmiah Nusantara JURNAL AKADEMIK EKONOMI DAN MANAJEMEN Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer HUMAN: Journal of Social Humanities and Science Journal of Informatics and Vocational Education Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Yudistira Bagus Pratama
Computer Science Study Program, Universitas Muhammadiyah Bangka Belitung, Indonesia
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Implementasi Data Science untuk Analisis Efektivitas Media Pembelajaran Etnobook Digital dalam Mendukung Literasi Siswa Sekolah Dasar Safitri, Ananda Dwi; Hendrik, Maulina; Pratama, Yudistira Bagus
TIN: Terapan Informatika Nusantara Vol 5 No 11 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i11.7182

Abstract

Rendahnya tingkat literasi siswa sekolah dasar menjadi tantangan utama dalam dunia pendidikan. Salah satu inovasi yang dapat digunakan untuk meningkatkan literasi adalah Etnobook Digital, sebuah media pembelajaran berbasis digital yang menggabungkan elemen interaktif dan konten budaya lokal. Media ini dirancang untuk memberikan pengalaman belajar yang lebih menarik dan bermakna bagi siswa, sehingga dapat meningkatkan minat baca serta pemahaman mereka terhadap materi. Penelitian ini bertujuan untuk menganalisis efektivitas Etnobook Digital dalam meningkatkan literasi siswa menggunakan pendekatan data science. Metode yang digunakan mencakup analisis statistik, machine learning, serta eksplorasi pola penggunaan media pembelajaran. Sampel penelitian terdiri dari 100 siswa yang terbagi dalam kelompok eksperimen dan kontrol. Hasil penelitian menunjukkan bahwa siswa yang menggunakan Etnobook Digital mengalami peningkatan nilai posttest yang lebih tinggi dibandingkan dengan kelompok kontrol, dengan rata-rata peningkatan 26,53 poin pada kelompok eksperimen dan 13,20 poin pada kelompok kontrol. Analisis log data juga menunjukkan bahwa siswa dengan durasi penggunaan lebih lama dan frekuensi akses lebih tinggi memiliki tingkat keberhasilan kuis sebesar 90%. Model Random Forest Regressor digunakan untuk memprediksi skor posttest, sedangkan K-Means Clustering berhasil mengelompokkan siswa berdasarkan pola penggunaan. Dengan demikian, dapat disimpulkan bahwa media pembelajaran Etnobook Digital memiliki potensi besar untuk meningkatkan literasi siswa, terutama jika diterapkan secara konsisten dan disertai dengan strategi pembelajaran yang tepat.
Strengthening youth associations in creating the “Merehat” (be educated literacy in numeracy, technology, and health) generation at SMA Muhammadiyah Bangka Belitung Agustine, Putri Cahyani; Mega, Iful Rahmawati; Walton, Erick Prayogo; Pratama, Yudistira Bagus; Azzani, Arlina Feijriah; Fermanda, Syandhu Dea; Putri, Elsa Hana Rahma; Christivo, Ryevilgo
Abdi Masyarakat Vol 7, No 1 (2025): Abdi Masyarakat
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/abdi.v7i1.8969

Abstract

This community service activity was carried out to introduce an understanding of literacy and numeracy, the use of technology in learning and understanding the importance of adolescent health awareness which is a contribution to the problems in the field, there is a lack of productivity of adolescents in the organization 1) less time to study especially for numeracy literacy content, 2) lack of ability to utilize technology in learning, 3) lack of understanding of adolescents in the organization in handling injuries during activities and lack of awareness of adolescents in maintaining health. The training was conducted at SMA Muhammadiyah Pangkalpinang, and 30 high school students participated. The results of this activity are the presentation of material on understanding literacy and numeracy, an introduction to making flyers with Canva, and an introduction to a healthy lifestyle. This activity has been published in local mass-media articles in Bangka Belitung, and the videos have been uploaded on the official LPPMPP YouTube account of Universitas Muhammadiyah Bangka Belitung. The participants from this event hope that the activity will always be carried out periodically because the participants' feedback was great, indicating a percentage of 83.57%.
PERBANDINGAN PERFORMA ALGORITMA NAIVE BAYES DAN SVM UNTUK ANALISIS SENTIMEN KOMENTAR YOUTUBE TERHADAP INDUSTRI ESPORTS DI INDONESIA Tito Dian Permana; Yudistira Bagus Pratama; Zikri Wahyuzi; Eka Altiarika; Arvi Pramudyantoro
JURNAL ILMIAH NUSANTARA Vol. 2 No. 6 (2025): Jurnal Ilmiah Nusantara
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jinu.v2i6.6753

Abstract

The esports industry in Indonesia is rapidly growing and gaining significant attention on social media, particularly YouTube, where comments reflect public perceptions. This study compares the performance of Naive Bayes and Support Vector Machine (SVM) in classifying sentiments from YouTube comments and explores key themes using Latent Dirichlet Allocation (LDA). Data were collected via the YouTube Data API v3, labeled with TextBlob and manually verified into positive, negative, and neutral categories. After preprocessing and TF-IDF representation, class imbalance was handled with SMOTE, and models were trained and evaluated using accuracy, precision, recall, F1-score, and confusion matrix. Results indicate that Naive Bayes achieved 73.85% accuracy with an F1-score of 0.71, while SVM slightly outperformed with 73.97% accuracy and the same F1-score. SVM showed better consistency in classifying negative and neutral comments, whereas Naive Bayes was more effective for positive ones. LDA revealed dominant discussion topics such as appreciation, enthusiasm, community interaction, criticism, and support for esports development. These findings highlight SVM’s superior overall performance and the value of LDA in uncovering public discourse, providing both academic contribution and practical insights for the esports industry in understanding public sentiment.
ANALISIS KUALITAS AIR LIMBAH WUDHU DALAM SISTEM DAUR ULANG BERKELANJUTAN Irwan, Andesta Granitio; Pratama, Yudistira Bagus; Okta, Evan Dwi
Jurnal Teknik Sipil Vol. 17 No. 4 (2024)
Publisher : Program Studi Teknik Sipil Fakultas Teknik Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jts.v17i4.9671

Abstract

Water is one of the important elements in supporting human life so that optimal use of water can have a big impact on life. Water-saving practices, especially during ablution, are often uncontrollable, resulting in water-wasting behavior. In addition, the acidic pH conditions in some of the water samples used are feared to have a long-term adverse impact on individual users. This research provides a solution in saving water with an ablution wastewater recycling system for reuse by utilizing Internet of Things (IoT)-based monitoring that can record water usage discharge using a flowmeter while connected to a smartphone. In the simulation, a prototype is used which is designed as a water recycling system that can be monitored with the addition of a filtration system to filter waste and improve water quality, namely Total Dissolved Solids (TDS), Dissolved Oxygen (DO), and pH. The results showed that in total 52 samples, the average water usage was 2.45 liters / person and 42.31% were in the wasteful category. Comparison of water quality before and after filtering has a significant increase with TDS values reaching 118%, DO 41% and pH 42.31%. This increase shows better water quality after filtering so that it can be reused and the recycling results in the system used have an efficiency of 44% based on the comparison of monitoring volume and actual volume of water.
PELATIHAN PEMBUATAN VIDIO INTERAKTIF VISUAL DAN VIDIO PEMBELAJARAN BERBASIS FILMORA DALAM RANGKA OPTIMALISASI KEGIATAN BELAJAR MENGAJAR MENUJU KURIKULUM MERDEKA BAGI KELOMPOK KERJA GURU (KKG) GUGUS 1 KRIO PANTING KECAMATAN PAYUNG Yurdayanti, Yurdayanti; Nabela, Silvio Juliana; Pratama, Yudistira Bagus
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 5 (2024): Vol. 5 No. 5 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i5.35448

Abstract

Pengabdian ini dilatarbelakangi oleh kebutuhan terhadap pengembangan media pembelajaran yang interaktif sehingga dapat memfasilitasi gaya belajar peserta didik pada implementasi kurikulum merdeka. Pengabdian ini penting dilakukan untuk membekali kelompok kerja guru (KKG) Gugus 1 Krio Panting Kecamatan Payung dalam mengembangkan media pembelajaran interktif sehingga dapat menunjang proses pembelajaran di kelas. Kegitan pengadian ini dissambut baik oleh para guru, peserta kegaiatan sangat antusias dalam mengikuti kegaitan yang dilaksanakan. 100% guru belum pernah menggunakan Filmora dan sejenisnya dalam pembelajaran namun setelah mendapatkan pelatihan 80% guru tertarik membuat media pembelajaran berbasis filmora dalam pembelajaran. Hal ini didukung oleh pengetahuan guru setelah mengikuti pelatihan, 99% persen peserta memahami fitur-fitur pada aplikasi Microsoft powerpoint, google slides, canva, quiziz dan filmora. 96% peserta berpendapat bahwa Microsoft powerpoint, google slides, canva, quiziz dan filmora mudah digunakan. 99% peserta tertarik menggunakan Microsoft powerpoint, google slides, canva, quiziz dan filmora dalam proses pembelajaran
Pengembangan Virtual Assistant menggunakan Teknologi NLP dengan Metode Algoritma Machine Learning untuk Layanan Informasi Akademik di SMA Negeri 1 Parittiga Berbasis Web Yuniarni Yuniarni; Yudistira Bagus Pratama; Arvi Pramudyantoro
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 3 No. 5 (2025): Oktober: Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v3i5.1152

Abstract

This study aims to develop a web-based Virtual Assistant to improve the efficiency of academic information services at SMA Negeri 1 Parittiga. The research was motivated by the delays and inaccuracies in information delivery caused by the manual system still used in the school. The system development was carried out using the Research and Development approach with the Waterfall model, which includes the stages of needs analysis, design, implementation, and evaluation. The main technologies used are Natural Language Processing (NLP) and the Long Short-Term Memory (LSTM) machine learning algorithm, which allow the assistant to understand and respond to user questions in natural language in a contextual way. The system architecture uses Flask as the backend, Vue.js as the frontend, and Laravel for administrative data management. The testing results show that the system has an accuracy level of 88.4% in providing correct answers and a user satisfaction level of 92%, surpassing the target success rate of 80%. These findings prove that integrating NLP and LSTM can enhance the system's ability to understand conversational context and speed up the distribution of academic information. The study concludes that a web-based Virtual Assistant is an effective solution for the digitalization of school information services and has the potential to support the implementation of artificial intelligence technology in secondary education in Indonesia.
ANALISIS DATA PELANGGAN DENGAN ALGORITMA K-MEANS UNTUK PENINGKATAN PENJUALAN LAYANAN ICONNET DI BANGKA BELITUNG Muhamad Mustaqim; Yudistira Bagus Pratama; Arvi Pramudyantoro
JURNAL AKADEMIK EKONOMI DAN MANAJEMEN Vol. 2 No. 4 (2025): JURNAL AKADEMIK EKONOMI DAN MANAJEMEN 
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jaem.v2i4.7106

Abstract

Sales increase is an essential factor for telecommunication service providers, including ICONNET, a subsidiary of PLN, amid intense market competition. Companies face the challenge of designing effective marketing strategies without structured customer data analysis. This study aims to apply the K-Means Machine Learning algorithm to analyze and cluster ICONNET customer data in Bangka Belitung, with the expected results supporting strategic sales increase decisions. The methodology employed is Data Mining with the CRISP-DM framework, where the modeling process implements the K-Means algorithm. The determination of the optimal number of clusters (K) was consistently performed using the Elbow Method and Silhouette Score, yielding an optimal value of K=2. The clustering results successfully divided customers into two main groups: Cluster 0, dominated by users of low-value packages (Package 1 and 2), and Cluster 1, consisting of users of higher-value packages (specifically Package 5). This segmentation provides a basis for ICONNET to formulate differentiated service strategies and targeted marketing offers tailored to the characteristics and preferences of each customer segment, which directly supports operational efficiency and long-term business growth.
Identifikasi Pola Perubahan Tutupan Lahan (Land Cover) Akibat Penggunaan Lahan (Land Use) Menggunakan Algoritma Random Forest Di Kabupaten Bangka Tengah Ari Ardiansyah; Yudistira Bagus Pratama; Zikri Wahyuzi; Arvi Pramudyantoro; Andesta Granitio Irwan
JOURNAL SAINS STUDENT RESEARCH Vol. 3 No. 6 (2025): Jurnal Sains Student Research (JSSR) Desember
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v3i6.7072

Abstract

Central Bangka Regency has been facing growing environmental pressures resulting from the expansion of oil palm plantations, mining operations, and accelerated urban development. These activities have caused considerable changes in land cover, posing a threat to the sustainability of local ecosystems. This study aims to examine land cover dynamics between 2019 and 2022 and to forecast future conditions for 2030 as a basis for sustainable spatial planning. Sentinel-2A satellite imagery was processed using the Google Earth Engine(GEE) platform, employing the Random Forest(RF) algorithm to classify land cover into five categories: forest, water, built-up, oil palm plantations, and barren. Model validation through the Overall Accuracy metric demonstrated strong classification performance, reaching 0.90297 in 2019 and 0.90849 in 2022. The analysis showed a 21.63% reduction in forest area, alongside significant increases in oil palm and built-up land. The projection for 2030 suggests that forest cover may decline to just 3.35% of the total area, with oil palm plantations and built-up land becoming dominant. These results emphasize the necessity of implementing sustainable land-use management strategies to maintain a balance between economic growth and environmental conservation in Central Bangka Regency.
Analisis Sentimen terhadap Kasus Korupsi Timah di Kepulauan Bangka Belitung menggunakan Algoritma Indobert dan Bidirectional LSTM Sevtian, Andre; Pratama, Yudistira Bagus; Wahyuzi, Zikri
HUMAN: Journal of Social Humanities and Science Vol. 3 No. 1 (2025): HUMAN: Journal of Social Humanities and Science, July 2025
Publisher : ASIAN PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58738/human.v3i1.1116

Abstract

Kasus korupsi timah di Kepulauan Bangka Belitung menjadi sorotan publik karena dampaknya terhadap lingkungan, perekonomian daerah, serta kepercayaan masyarakat terhadap institusi negara. Komentar publik yang tersebar di platform YouTube menjadi sumber data potensial untuk dianalisis guna memahami kecenderungan sentimen masyarakat. Oleh karena itu, penelitian ini bertujuan untuk melakukan analisis sentimen terhadap kasus tersebut dengan menggunakan algoritma IndoBERT dan Bidirectional LSTM. Tahapan penelitian menggunakan metode CRISP-DM yang mencakup business understanding, data understanding, data preparation, modeling, evaluation, dan deployment. Data dikumpulkan melalui YouTube Data API, kemudian diberi label sentimen menggunakan pendekatan hybrid, yaitu pelabelan otomatis dengan model pretrained IndoBERT serta verifikasi manual. Dua algoritma utama yang digunakan untuk mengklasifikasikan sentimen adalah IndoBERT dan Bidirectional LSTM, dengan evaluasi performa berdasarkan metrik accuracy, precision, recall, F1-score, dan AUC menggunakan skema Stratified K-Fold Cross Validation. Hasil evaluasi menunjukkan bahwa IndoBERT unggul dalam klasifikasi sentimen dengan rata-rata akurasi validasi sebesar 96,67% dan nilai F1-score sebesar 90,62%. Model ini mengungguli Bidirectional LSTM yang mencatat akurasi sebesar 95,60% dan F1-score sebesar 88,11%. Berdasarkan hasil tersebut, IndoBERT dipilih untuk diimplementasikan ke dalam sistem analisis sentimen berbasis web menggunakan framework Streamlit. Sistem ini mendukung masukan berupa URL video YouTube atau tema tertentu, serta mampu mengekstrak komentar, mengklasifikasikan sentimen, dan menyajikan visualisasi hasil secara otomatis. Dengan demikian, dapat disimpulkan bahwa IndoBERT lebih efektif dalam menganalisis sentimen publik terkait kasus korupsi timah di Kepulauan Bangka Belitung.
Kelas Kreatif Digital: Pelatihan Pembuatan Infografis Sosial bagi Guru dan Siswa SD Negeri 2 Payung Hendrik, Maulina; Pramesti, Diana; Pratama, Yudistira Bagus; Fas’ya, Alvia; Fabian, Cecep
Jurnal Pengabdian Masyarakat Bhinneka Vol. 4 No. 3 (2026): Bulan Februari
Publisher : Bhinneka Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58266/jpmb.v4i3.872

Abstract

Administrasi guru dan potensi sekolah belum dimanfaatkan secara optimal sebagai sumber data dan sarana belajar untuk mengembangkan literasi di lingkungan SD. Selain itu, kemampuan guru dan siswa dalam mengolah informasi menjadi media digital yang informatif masih terbatas. Kelas kreatif ini dilaksanakan di SD Negeri 2 Payung, Kabupaten Bangka Selatan yang bertujuan untuk: 1) mengembangkan kemampuan guru dalam menganalisis data pembelajaran dan aktivitas sosial sekolah agar dapat diolah menjadi bahan ajar berbasis infografis, 2) Menumbuhkan kesadaran siswa dalam membaca, memahami, dan menyajikan informasi sosial berbasis digital sebagai sarana literasi. Pelaksanaan kelas kreatif digital di SD Negeri 2 Payung menunjukkan peningkatan kemampuan peserta dalam memanfaatkan administrasi guru dan potensi sekolah sebagai sumber data pembelajaran. Guru berhasil mengolah data pembelajaran dan fenomena sosial di lingkungan sekolah menjadi infografis edukatif yang informatif dan menarik. Sementara itu, siswa mampu terlibat aktif dalam proses eksplorasi informasi sosial, mulai dari pengumpulan data sederhana hingga menyajikannya dalam bentuk media digital. Kegiatan ini juga berdampak pada tumbuhnya kesadaran literasi kritis dan literasi digital, terlihat dari kemampuan peserta membaca realitas sekolah secara reflektif dan mempresentasikan informasi secara visual yang komunikatif. Melalui proses kolaboratif berbasis proyek, guru dan siswa lebih siap menjadi produsen pengetahuan yang kreatif dan adaptif terhadap perkembangan teknologi.
Co-Authors A. Resti Supraeni resti Abdulah, Abdulah Agustine, Putri Cahyani Al Ahfaz Reza Ramdani Alfan Asa Ramadhoni Andesta Granitio Irwan Andika Saputra Ari Ardiansyah Ari Gunawan Ari Gunawan Arif, Maulana Arvi Pramudyantoro Azzani, Arlina Feijriah Bayu Saputra Christivo, Ryevilgo Dalimunthe, Nurzaidah Putri Ega Noviani Eka Altiarika Eka Altiarika Elda Elda Emikawati Erick Prayogo Walton Erick Prayogo Walton, Erick Prayogo Fabian, Cecep Fani Februari Farhan Aflah Pratama Fas’ya, Alvia Fermanda, Syandhu Dea Haiyudi Haiyudi Haiyudi Haiyudi Haiyudi, Haiyudi Hendrik, Maulina Hevitria Hevitria Jauhar Ridloni Marzuq Marwani Marwani Mega Sukma Mega, Iful Rahmawati Micha Arnola Muhamad Mustaqim Nabela, Silvio Juliana Nurjanah Nurjanah Okta, Evan Dwi Pramesti, Diana Putri, Elsa Hana Rahma Rajab Vebrian Ramdani, Al Ahfaz Reza Randi Atul Aufa Ratno Purnamasari Riski Andriani Safitri, Ananda Dwi Setiawan, Rifki Hanif Sevtian, Andre Shinta Pramudya Wardani Silvio Juliana Nabela Sitthipon Art-in Sofwan Arif Agil Suheni Suheni Suheni Sukamto, Ika Sumiyarsi Suprayuandi Pratama Tito Dian Permana Ulyma Tahara Arisandi Vika Martahayu Wiwit Febriyanti Yurdayanti Yurdayanti Yurdayanti, Yurdayanti Zaliman, Iski Zikri Wahyuzi Zikri Wahyuzi