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All Journal Journal of Education and Learning (EduLearn) Jurnal Teknologi Informasi dan Ilmu Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Pengabdian Magister Pendidikan IPA TESLA: Jurnal Teknik Elektro Jurnal Teknologi Informasi dan Multimedia Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Abdi Insani JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Abdimasku : Jurnal Pengabdian Masyarakat Idealis : Indonesia Journal Information System Jurnal Teknik Informatika (JUTIF) Jurnal Begawe Teknologi Informasi
Dwiyansaputra, Ramaditia
Dept Informatics Engineering, University Of Mataram
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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SOSIALISASI PEMASARAN DIGITAL BAGI PELAKU UMKM DI DESA JURIT, LOMBOK TIMUR, NTB: Digital Marketing Socialization for Small and Medium Enterprises on Jurit Village East lombok Bimantoro, Fitri; Wijaya, I Gede Pasek Suta; Dwiyansaputra, Ramaditia; Nugraha, Gibran Satya; Husodo, Ario Yudo; Hamidi, Mohammad Zaenuddin; Akhyar, Halil; Darmawan, Riski
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 5 No. 2 (2024): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v5i2.1272

Abstract

Terletak di sebelah Selatan kaki gunung Rinjani, desa Jurit yang terletak di Lombok Timur merupakan salah satu desa yang memiliki sumber daya yang melimpah. Desa Jurit dengan mayoritas petani memiliki produk unggulan berupa Nanas. Saat ini, dengan perkembangan teknologi yang begitu pesat, tentu penggunaan teknologi menjadi salah satu faktor yang mampu mendongkrak kualitas hidup Masyarakat pada umumnya. Tentu hal itu juga menjadi fokus utama pengabdian di desa Jurit, yakni akan menyoroti tentang penggunaan digital marketing sebagai alat untuk meningkatkan penjualan berbasis digital, tentunya harapannya dapat meningkatkan pendapatan para petani dan pelaku usaha kecil dan menengah yang ada di desa Jurit. Pada prosesnya, sosialisasi ini memperkenalkan dan melatih pelaku usaha untuk menggunakan media pemasaran seperti media sosial, e-commerce, dan aplikasi mobile lainnya, dengan tujuan pelaku usaha mampu memahami dan menggunakan strategi digital yang baik seperti pemasaran digital, search engine optimizer, penggunaan media sosial dan tentunya e-commerce. Sehingga pada praktiknya, kegiatan ini tidak hanya berfokus pada cara penggunaan teknolginya, namun juga bagaimana mengenalkan dan menanamkan mindset dan model bisnis digital yang akan membantu peningkatan dan keberlangsungan pelaku usaha pada masa depan.
Studi Pemodelan dan Prediksi Aktivitas Antibakteri Biopo-limer Kitosan Menggunakan Response Surface Methodology (RSM) Halil Akhyar; Selvira Anandia Intan Maulidya; Muhammad Mukaddam Alaydrus; Maz Isa Ansyori; Mohammad Zaenuddin Hamidi; I Gede Pasek Suta Wijaya; Ramaditia Dwiyansaputra; Pahrul Irfan
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.713

Abstract

Infections occured in the human are mostly caused by uncontrolled growth of Staphylococcus aureus bacteria. A strategy to inhibit bacterial growth can use antibacterial agents such as chitosan. The mechanism of the effectiveness of chitosan as an antibacterial is quite complex, even the data on its antibacterial activity is quite fluctuating so that it is difficult to analyze accurately and efficiently. Therefore, the purpose of the study was to predict the inhibition zone of s.aureus bacteria through laboratory experiments combined with modeling using the Central Composite Design (CCD) approach. The research was carried out with two main stages, including chitosan isolation and calculation of bacterial inhibition zones. The production of chitosan leverages the microwave isolation and FTIR to examine for the degree of deacetylation and its functional group using. Furthermore, the antibacterial activity of chitosan biopolymer was tested using the diffusion method combined with modeling using the RSM CCD approach. The results showed that chitosam from oyster shell was obtained by DD of 83.29% and the emergence of typical chitosan groups, such as amine (NH2) and hydroxyl (OH). Chitosan can hamper the growth of s. aureus bacteria with an inhibition zone of up to 0.40 mm. The experimental data were combined with computational modeling obtained the values of the determination coefficient R2 = 0.6083. The modeling was assessed by p-value of < 0.0001 and F-value of 13.46. Statistically, the obtained model is relevant to the relationship between the number of bacterial colonies and the concentration of chitosan solution with the bacterial inhibition zone. Based on numerical analysis and modeling, the predicted values of the number of s. aureus bacterial colonies and chitosan concentrations were 550,000 CFU/ml and 42.5%. Therefore, Pearl shells can be isolated into chitosan, as well as chitosan has the potential to be a good antibacterial agent. The model has good prediction performance, but it rquires to increase the number of point spreads and it is necessary to validate the prediction results to obtain actual predictions.
Multitask Aspect-Based Sentiment Analysis of Indonesian Tweets on Mandalika Circuit using CNN and IndoBERTweet Embeddings Salsabila, Raissa Calista; Dwiyansaputra, Ramaditia; I Gede Pasek Suta Wijaya
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 9 No 2 (2025): December 2025
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v9i2.658

Abstract

This study proposes a multitask Aspect-Based Sentiment Analysis (ABSA) model for Indonesian tweets related to the Mandalika Circuit, using IndoBERTweet embeddings and Convolutional Neural Networks (CNN). The model simultaneously predicts aspect categories and sentiment polarities. Two experimental setups were evaluated: one using raw tweets (Scenario 1) and another with preprocessed text (Scenario 2). The results show that Scenario 1 consistently outperforms Scenario 2, highlighting the ability of IndoBERTweet to handle informal tweet structures without requiring standard text cleaning. A paired t-test was conducted to evaluate statistical differences in performance between scenarios. While Scenario 1 showed higher average F1-scores, the p-value (0.7178) suggests no statistically significant improvement across all classes. Further analysis reveals that certain classes, primarily neutral and positive sentiments, tend to perform worse than negative sentiments. Data augmentation was shown to improve recall and help the model handle underrepresented classes, particularly for “Ekonomi-Negative” and “Fasilitas-Negative” labels. The study highlights the importance of preserving informal language structures and utilizing data augmentation to enhance ABSA performance on real-world tweet data.
Multiclass Text Classification of Indonesian Short Message Service (SMS) Spam using Deep Learning Method and Easy Data Augmentation Nurun Latifah; Ramaditia Dwiyansaputra; Gibran Satya Nugraha
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3835

Abstract

The ease of using Short Message Service (SMS) has brought the issue of SMS spam, characterized by unsolicited and unwanted. Many studies have been conducted utilizing machine learning methods to build models capable of classifying SMS Spam to overcome this problem. However, most of these studies still rely on traditional methods, with limited exploration of deep learning-based approaches. Whereas traditional methods have a limitation compared to deep learning, which performs manual feature extraction. Moreover, many of these studies only focus on binary classification rather than multiclass SMS classification which can provide more detailed classification results. The aim of this research is to analyze deep learning model for multiclass Indonesian SMS spam classification with six categories and to assess the effectiveness of the text augmentation method in addressing data imbalace issues arising from the increased number of SMS categories. The research method used were Indonesian version of Bidirectional Encoder Representations from Transformers (IndoBERT) model and exploratory data analysis (EDA) augmentation technique to address imbalance dataset issue. The evaluation is conducted by comparing the performance of the IndoBERT model on the dataset and applying EDA techniques to enhance the representation of minority classes. The result of this research shows that IndoBERT achieves 91% accuracy rate in classifying SMS spam. Furthermore, the use of EDA technique results in significant improvement in f1-score, with an average 12% increase in minority classes. Overall model accuracy also improves to 93% after EDA implementation. This research concludes that IndoBERT is effective for multiclass SMS spam classification, and the EDA is beneficial in handling imbalanced data, contributing to the enhancement of model performances.
Implementasi Konsep Community Driven Material Recovery Facilities (C-Dmrf) Sebagai Upaya Penanganan Terintegrasi Sampah Wisata Di Gili Trawangan Astrini Widiyanti; Siska Ita Selvia; Ramaditia Dwiyansaputra
Jurnal Pengabdian Magister Pendidikan IPA Vol 9 No 1 (2026): Januari - Maret 2026
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v9i1.12781

Abstract

The increase in tourist visits to Gili Trawangan, averaging 1.4% per year, is driven by its distinctive marine tourism attractions and unique socio-cultural appeal. This growth has led to a corresponding rise in waste generation, necessitating the implementation of effective waste management strategies. This community service initiative adopts the Community-based Material Recovery Facility (CdMRF) concept to optimize the performance and governance of the Gili Trawangan Waste Bank. The implementation method is structured into four stages: (1) problem identification and needs assessment, (2) formulation and dissemination of an action plan and standard operating procedures (SOP) for waste management, (3) Training of Trainers (ToT) on CdMRF-based waste management, and (4) training on digital application-based waste management combined with a village-scale organic waste management campaign through composting. The needs assessment identified five waste management subsystems: operational-technical, institutional, policy and regulatory, financial, and socio-community aspects. The CdMRF implementation is tailored to local policies, engages stakeholders, and promotes recycling at the neighborhood level. Digital application-based training enhances management transparency and efficiency, while composting campaigns strengthen organic waste management practices. The results indicate that CdMRF implementation has increased community participation, reinforced institutional capacity, and supported integrated and sustainable tourism waste management.
Development of the SDN Repok Puyung Website Based on WordPress with E-report Features and an Online Suggestion Service: PENGEMBANGAN WEBSITE SDN REPOK PUYUNG BERBASIS WORDPRESS PADA FITUR E-RAPOR DAN LAYANAN PENYAMPAIAN SARAN DARING Wahyuni Sulastri; I Gede Pasek Suta Wijaya; Muhammad Azmi; Ramaditia Dwiyansaputra
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 7 No. 1 (2026): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v7i1.1506

Abstract

Perkembangan teknologi informasi saat ini sangat vital dalam meningkatkan efisiensi administrasi di sektor pendidikan. SDN Repok Puyung saat ini masih menggunakan media informasi berupa blog sederhana yang memiliki keterbatasan desain serta konten, sehingga penyampaian informasi kepada siswa dan orang tua menjadi kurang optimal. Penelitian ini bertujuan untuk mengembangkan website sekolah yang profesional berbasis WordPress dengan fitur utama e-rapor dan layanan penyampaian saran daring. Metode pengembangan sistem yang digunakan adalah metode Kanban yang mencakup tahap perencanaan, implementasi, dan penyelesaian. Pengujian sistem dilakukan menggunakan metode User Acceptance Testing (UAT) yang melibatkan guru, siswa, dan staf sekolah sebagai responden. Hasil penelitian menunjukkan bahwa website berhasil diimplementasikan dengan fitur e-rapor yang memudahkan distribusi hasil belajar secara digital dan sistematis. Berdasarkan hasil pengujian UAT, sistem memperoleh tingkat penerimaan sebesar 87,418%, yang dikategorikan "Sangat Baik". Kesimpulannya, pengembangan website ini efektif dalam mendukung digitalisasi informasi, meningkatkan transparansi, serta mempermudah administrasi akademik di SDN Repok Puyung.
PERANCANGAN BACKEND MODULAR DAN REUSABLE UNTUK SISTEM SUPER ADMIN PADA APLIKASI LOMBOK HALAL ROOM DENGAN RESTFUL API Muhamad Singgih; Royana Afwani; Ramaditia Dwiyansaputra; Mochammad Dinta Alif Syaifuddin
IDEALIS : InDonEsiA journaL Information System Vol. 9 No. 1 (2026): Jurnal IDEALIS Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v9i1.3565

Abstract

The growth of halal tourism in Lombok, Indonesia, calls for scalable digital platforms with strong and centralized administrative governance. This study proposes and implements a domain-oriented, modular RESTful API backend to support Super Admin operations in the Lombok Halal Room (LHR) platform. Using a design-science approach and an iterative SCRUM process, we developed a layered API Service Repository Infrastructure architecture using Hapi.js, PostgreSQL, and Redis, delivering 42 endpoints across key administrative domains with uniform JSON contracts and JWT-based authentication. The proposed contribution is a metric-driven engineering template that links SCRUM execution to modular backend domains and validates the resulting system using performance and software-quality measurements. Experimental results under controlled workloads show that Redis caching substantially improves scalability for read-heavy administrative operations by reducing response time from seconds to low single-digit milliseconds and increasing throughput to above 40,000 requests per second. Code-quality metrics further indicate clean module boundaries (CBO=0; LCOM*=0), while the Maintainability Index (MI) highlights modules that require targeted refactoring. Overall, the backend provides a reusable reference architecture for centralized halal tourism administration such as partner verification, content moderation, transaction oversight, and system monitoring that can be adapted to similar platforms in other regions.
EYE DISEASE CLASSIFICATION USING DEEP LEARNING: A COMPARATIVE STUDY OF MOBILENETV2, XCEPTION, AND EFFICIENTNET-B0 Latifa Zahra Agustini; Fitri Bimantoro; Ramaditia Dwiyansaputra
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.518

Abstract

This study presents a comparative analysis of three convolutional neural network (CNN) architectures—MobileNetV2, Xception, and EfficientNet-B0—for classifying retinal fundus images into four categories: Cataract, Diabetic Retinopathy, Glaucoma, and Normal. Using a dataset of 4,217 images, the models were trained with transfer learning, image augmentation, and regularization techniques, and evaluated through 5-fold cross-validation. EfficientNet-B0 achieved the highest mean accuracy (0.85) and demonstrated stable performance across all metrics, while MobileNetV2 provided competitive accuracy with lower computational requirements, making it suitable for resource-limited environments. Xception showed the lowest and least stable performance, indicating a higher tendency to overfit. External validation with clinical images revealed a significant drop in accuracy for all models, highlighting challenges related to domain shift and limited generalization. Grad-CAM analysis also showed difficulties in detecting subtle pathological features in Diabetic Retinopathy and Glaucoma. The study is limited by the small dataset size, reliance on a single data source, and the absence of additional clinical information. Future work should incorporate larger and more diverse datasets, apply domain adaptation strategies, and integrate multimodal clinical data to enhance robustness and clinical applicability.
Co-Authors A.M., Mursyidhan Ariefbillah Afwani, Royana Agitha, Nadiyasari Ahmad Zafrullah Ahmad Zafrullah Mardiansyah Ahmad Zafrullah Mardiansyah Akhmad Saufi Amara, Nadya Aranta, Arik Arik Aranta Arik Aranta Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo, Ario Yudo Ariyan Zubaidi Astrini Widiyanti Azzam Al Husaini Budi Irmawati Budi Irmawati Budiman Rabbani Darmawan, Muhammad Ilham Darmawan, Riski Dewi, Zaskia Elvina Dwi Ratnasari Ekaputra, Galang Prasetya Fadhilah, A. Nur Fitri Bimantoro Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Hadi, Risman Halil Akhyar Hamidi, Mohammad Zaenuddin Hanifah, Fairuz Heri Wijayanto Hidayat, Lalu Ramdoni Hirkan, Muhamad Nurul I Gede Pasek Suta Wijaya I Putu Teguh Putrawan I Wayan Agus Arimbawa Ita Selvia, Siska Ivan Andrianto Jatmika, Andy Hidayat Kokong, Diah Anggreni Ratna Sari Kusuma, Fendi Putra Latifa Zahra Agustini Made Agus Dwiputra Manuaba, Ida Bagus Ryand Wirayana Maulana, Sutan Fajri Maz Isa Ansyori Mindi Richia Putri Mochammad Dinta Alif Syaifuddin Muhamad Singgih Muhammad Azmi Muhammad Daden Kasandi Putra Wesa Muhammad Dani Muhammad Giri Restu Adjie Muhammad Husnul Ramdani Muhammad Muaidi Muhammad Mukaddam Alaydrus Muhlis Fathurrahman Muvianto, Cahyo Mustiko Okta Noor Alamsyah Nugraha, Gibran Satya Nurun Latifah Pahrul Irfan Pahrul Irfan Paramarta, Muhammad Magistra Apta Rahayu, Sefani Cahyo Auliya Raphael Bianco Huwae Rassy, Regania Pasca Rizqullah, Muhammad Naufal Robby Igfirly Mustaib Rohmawati, S. Antya Royana Afwani Salsabila, Raissa Calista Selvira Anandia Intan Maulidya Siska Ita Selvia Suhada, Destia Susi Rahayu Sutiyasning Tiara, Baiq Najwa Tresna, I Made Agus Wahyuni Sulastri Wahyuningsih Wahyuningsih Widiarta, I Putu Angga Purnama Widiyanti, Astrini Wirarama Wedashwara Wirararama Wedashwara