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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA Jurnal Simetris Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan WARTA KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Science and Technology Indonesia JOIV : International Journal on Informatics Visualization Jurnal Komputasi Jurnal Teknoinfo Jurnal Tekno Kompak Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Buguh: Jurnal Pengabdian Kepada Masyarakat Jurnal Pepadun Journal of Data Science and Software Engineering Warta LPM Laporan Upaya Nyata Inovasi Ilmu Komputer (LUNIK) Integra: Journal of Integrated Mathematics and Computer Science
Favorisen R. Lumbanraja
Jurusan Ilmu Komputer, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Lampung
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Social Sciences Other

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Traffic Violation Modeling Using K-Means Clustering Method: A Case Study in Bandung, Indonesia Junaidi, Akmal; Manurung, Yunita Rosalina; Shofiana, Dewi Asiah; Lumbanraja, Favorisen Rosyking
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 3 (2024): November
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241326

Abstract

Violations of traffic regulations are both an issue and a problem that persists as a feature of life, especially in metropolitan regions such as Bandung. Traffic violation has both behavioral and environmental patterns, with different types of violations occurring at different times during the day. This negligence stems largely from not properly equipping the vehicle with the necessary documents, especially for drivers who do not pay attention to proper document preparation. With the goal of increasing road safety, law enforcement bodies face the ongoing challenge of managing rising traffic violation rates which results in a growing backlog of violation cases and a corresponding backlog workload for police departments. Comprehensive preventive strategies for the problem are extremely difficult to implement in the absence of streamlined mechanisms for the efficient allocation of limited police resources. Currently, agencies responsible for managing violation records are still using a manual desktop system based on Microsoft Excel spreadsheets. This method impedes the analysis of large datasets to derive actionable insights that could inform targeted, data-driven strategies needed to guide proactive measures. In this regard, this study attempts to implement the K-Means clustering technique in order to identify and classify high-incidence traffic violation areas in Bandung. Using this technique, the research classifies the city into three violation risk clusters: very prone, prone, and moderately prone areas. The map of the classes demonstrates the distribution of these clusters spatially, illustrating clearly and vividly how stakeholders can visualise the pattern of traffic violations. This method improves the understanding of data and at the same time boosts purposeful planning for the safety and public traffic order anticipations.
Evaluating User Satisfaction in The Halodoc Application Using a Hybrid CNN-BiLTSM Model for Sentiment Analysis Kurniasari, Dian; Su'admaji, Arif; Lumbanraja, Favorisen Rosyking; Warsono
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.42762

Abstract

The growing demand for digital healthcare services in Indonesia has driven the adoption of Online Healthcare Applications (OHApps) such as Halodoc. Despite over 65 million users, maintaining user satisfaction remains a challenge. This study employs sentiment analysis using a hybrid Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) model to classify user review ratings. A dataset of 10,000 Google Play Store reviews was divided into COVID-19 and post-pandemic segments. The methodology includes data collection, pre-processing, and dataset segmentation for training, validation, and testing. Results indicate that the CNN-BiLSTM model surpasses traditional machine learning by combining CNN’s feature extraction with BiLSTM’s long-term dependency capture, achieving 98.71% accuracy on COVID-19 data and 98.16% post-pandemic. Additionally, the model demonstrates strong performance across other key evaluation metrics, with precision, recall, and F1-score. Misclassification analysis highlights minor errors, particularly in ratings 4 and 5. These findings help healthcare providers enhance digital services by identifying user concerns, improving platform features, and optimizing customer engagement. Beyond healthcare, this approach has real-world applications in e-commerce and financial services, where sentiment analysis informs user experience improvements.
Understanding Consumer Sentiments: A TextBlob-Based Sentiment Analysis Study Kurniasari, Dian; Hdiana, Yazid Zinedine; Lumbanraja, Favorisen R.; Warsono, Warsono; Hadi, Normi Abdul
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 3 (2025): November
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252340

Abstract

This study employs advanced sentiment analysis techniques to enhance the understanding of drug reviews, with a specific focus on TextBlob-based sentiment classification. As the accessibility of health products through pharmacies and online platforms continues to increase, individuals with limited health literacy are increasingly relying on user-generated feedback to inform their decision-making. By utilizing the TextBlob labelling method, this research categorizes user sentiments into positive, neutral, or negative, addressing the limitations inherent in traditional sentiment analysis approaches. The analysis is supported by an innovative model known as BERT, which effectively captures the emotional expression within textual data. The results indicate that the proposed approach consistently achieves an accuracy of 98% across training, validation, and testing phases, highlighting its strong performance in sentiment classification. This accomplishment underscores TextBlob’s ability to consistently and reliably assess user sentiment, thereby enriching the understanding of consumer perspectives in the pharmaceutical industry. The findings highlight the importance of effective sentiment analysis methods in healthcare, offering valuable insights for both consumers and stakeholders. Moreover, this study provides a foundation for future investigations focused on improving sentiment analysis methods across varied datasets, which will enhance the precision and applicability of classification results in different scenarios.
SINERGITAS PENGGIATAN EKONOMI KERAJINAN BATIK LAMPUNG, EKSPLORASI BUDAYA DAN EDUKASI KONSERVASI: ANDANAN BATIK TULIS, NEGERI SAKTI, PESAWARAN, LAMPUNG Rusitati, Elly Lestari; Suroso, Erdi; Warsono, Warsono; Junaidi, Junaidi; Lumbanraja, Favorisen Rosyking; Priyambodo, Priyambodo
Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Vol. 3 No. 2 (2019)
Publisher : Lembaga Penelitian dan Pengabdian Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jss.v3i2.146

Abstract

Batik Lampung merupakan salah budaya yang khas dengan motifnya dan menjadi salah satu kegiatan ekonomi yang kuat di Provinsi Lampung, termasuk kerajinan Andanan Batik Tulis, yang mencirikan keunikan budaya Lampung. Saat ini selain sebagai kegiatan kebutuhan ekonomi, kerajinan Andanan Batik Tulis sekaligus menjadi media edukasi budaya dan konservasi melalui pengkayaan motif berbasis budaya Lampung, konservasi dan penyediaan media belajar membatik. Penerapan edukasi budaya dan konservasi dilakukan melalui paket eduwisata yang disediakan bagi wisatawan baik lokal maupun asing. Program eduwisata ini mendapat tanggapan positif. Kata Kunci: Andanan Batik Tulis, eduwisata, budaya, konservasi, Lampung
Co-Authors - Damayanti Adawiyah, Laila Admi Syarif Aflaha Asri Ahyarudin Akbar, Mohammed Raihan Akmal Junaidi Amelia Jasmine Andrian, Rico Annisa Rizqiana Ardiansyah Ardiansyah Aristoteles, Aristoteles Asmiati Asmiati Astria Hijriani Astria Hijriani Aulia Putri Ariqa Ayu Amalia Bambang Hermanto Danu Sasmita Desti Fatmalasari Destian ade anggi Sukma Dian Kurniasari Didik Kurniawan Dwi Kartini, Dwi Dwi Sakethi Dwi Sakethi, Dwi Eliza Fitri Elly Lestari Rusitati Erdi Suroso Fanni Lufiana Fanni Lufiana Febi Eka Febriansyah Hadi, Normi Abdul Hamim Sudarsono . Hdiana, Yazid Zinedine Heningtyas, Yunda Ilman, Igit Sabda Indah Pasaribu Ira Hariati Br Sitepu Irawati, Anie Rose Jihan Aferiansyah Junaidi Junaidi Junaidi Junaidi Kristina Ademariana Kurnia Muludi Kurnia Muludi Kurnia Muludi Lilies Handayani M. Juandhika Rizky Machudor Yusman Manurung, Yunita Rosalina Megawaty, Dyah Ayu Meria Nensi Muhammad Reza Faisal, Muhammad Reza Muhammad Rizki Muhaqiqin, Muhaqiqin Muliadi Mustofa Usman Nadila Rizqi Muttaqina Naurah Nazhifah Nova Ayu Lestari Siahaan Nuning Nurcahyani Nurhasanah Nurhasanah Parabi, M. Iqbal Prabowo, Rizky Pratama, Rinaldo Adi Priyambodo Priyambodo Priyambodo Priyambodo Qory Aprilarita Rahmat Safe'i Rangga Agustiantino Reza Aji Saputra RM Sulaiman Sani Rosdiana, Siti Rudy Herteno Rudy Herteno Rusitati, Elly Lestari Saragih, Triando Hamonangan Shofiana, Dewi Asiah Sholehurrohman, Ridho Sintiya Paramitha Siti Aisyah Solechah Siti Rosdiana Su'admaji, Arif Susanto, Gregorius Nugroho Sutyarso, - Syangap Diningrat Sitompul TANJUNG, AKBAR RISMAWAN Tiyara Saghira Tristiyanto Tristiyanto Wamiliana Warsono Warsono Warsono Warsono Warsono YOHANA TRI UTAMI, YOHANA TRI Zuliana Nurfadlilah