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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Education and Learning (EduLearn) JUTI: Jurnal Ilmiah Teknologi Informasi Journal of Telematics and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization Jurnal Sains Teknologi dan Lingkungan (JSTL) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal RESISTOR (Rekayasa Sistem Komputer) Journal of Computer Science and Informatics Engineering (J-Cosine) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Abdi Insani Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Begawe Teknologi Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Fitri Bimantoro
Informatics Engineering Dept., Faculty Of 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 Dentistry 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 Mechanical Engineering Public Health Social Sciences Transportation Other

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Comparative Analysis of Proposed CNN Performance with CNN and Naive Bayes from Kaggle in ChatGPT Tweet Sentiment Analysis Alwi Pratama; Ario Yudo Husodo; Fitri Bimantoro
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.v9i2.629

Abstract

The rapid growth of social media platforms such as Twitter has led to an increasing demand for efficient sentiment analysis methods. This study focuses on the performance comparison of the CNN-based sentiment analysis model developed by the authors with two models sourced from Kaggle; CNN model and Naive Bayes model. In addition, ChatGPT is used as a reference in discourse exploration and sentiment analysis strategy development. ChatGPT is used to answer user questions, generate code, revise journals and the like. Performance evaluation is done in terms of inference time and accuracy. The findings reveal that the CNN model developed by the authors achieves superior accuracy compared to the CNN model from Kaggle, while the inference time developed by the authors shows a significant difference with a much higher number when compared to the Naive Bayes model from Kaggle. This analysis highlights the trade-off between efficiency and accuracy in sentiment analysis tasks and provides insights for selecting the right model based on current trends in data analysis.
Klasifikasi Penyakit Tenggorokan Menggunakan CNN: EfficientNetB0 dan ResNet50 Aliyah Fajriyani; I Gede Pasek Suta Wijaya; Fitri Bimantoro
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.v9i2.661

Abstract

Throat diseases are one of the global health issues. Early diagnosis could be an effective solution to prevent more severe throat disease. Automatic diagnosis based on medical images is possible to obtain by using Convolutional Neural Networks (CNN). This study employs two pretrained models namely ResNet50 and EfficientNetB0. The dataset contained 79 throat images divided to seven classes (normal, chronic laryngitis, acute pharyngitis, chronic pharyngitis, acute tonsillitis, chronic tonsillitis, and acute tonsillopharyngitis). The study was conducted in several scenarios and implemented gradually. First scenario, seven classes were merged into four classes (normal, pharyngitis, tonsillitis, and acute tonsillopharyngitis). Second scenario, four classes were combined into three classes (normal, pharyngitis, and tonsillitis). Third scenario, three classes were grouped into two classes (normal and illness). The results indicated that both the ResNet50 and EfficientNetB0 architectures achieved the highest performance in the third scenario (two classes). Both models showed identical evaluation matrics with accuracy of 91,67%, precision of 90%, recall of 100%, and F1-score of 94,74%. Furthermore, this study suggests that a dataset with numerous classes and limited data can be addressed by merging classes, thereby increasing the data size within each class. Key words: Classification, Throat Disease, CNN, ResNet50, EfficientNetB0.
Optimalisasi Aktivitas Antibakteri Formulasi Hidrogel Kitosan Berbasis Jaringan Saraf Multilayer Perceptron dalam Bioteknologi Lingkungan Akhyar, Halil; Illahi, Ramadian Ridho; Hendrawan; Zubaidi, Ariyan; Bimantoro, Fitri; Hamidi, M. Zaenuddin; Rahayu, Susi
JURNAL SAINS TEKNOLOGI & LINGKUNGAN Vol. 11 No. 3 (2025): JURNAL SAINS TEKNOLOGI & LINGKUNGAN
Publisher : LPPM Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jstl.v11i3.947

Abstract

Pengembangan biomaterial antibakteri yang berkelanjutan sangat penting untuk kemajuan bioteknologi lingkungan dan meningkatkan pengendalian patogen. Komposit hidrogel berbasis kitin menunjukkan aktivitas antimikroba alami. Namun, penentuan formulasi optimal masih menjadi tantangan akibat interaksi nonlinier antara kitin, PVA, gelatin, dan honey (madu). Studi ini memperkenalkan jaringan saraf tiruan Multilayer Perceptron (MLP) sebagai kerangka kerja prediktif dan optimasi cerdas untuk menentukan komposisi hidrogel paling efektif terhadap Pseudomonas aeruginosa. Model MLP dilatih menggunakan dataset sekunder dan dievaluasi melalui R², MSE, RMSE, dan MAE untuk menilai akurasi prediksi dan kinerja generalisasi. Model mencapai R² sebesar 0.991 pada tahap pelatihan dan 0.914 pada tahap pengujian, menunjukkan kemampuan yang baik dalam menangkap hubungan variabel yang kompleks. Kemudian, optimasi berbasis grid mengidentifikasi formulasi optimal yang terdiri dari 0.06 g/mL kitosan, 0.05 g/mL PVA, 0.00 g/mL gelatin, dan 0.01 g/mL honey (madu), menghasilkan zona inhibisi maksimum sebesar 30.66 mm. Selain itu, validasi eksternal menunjukkan bahwa model MLP menghasilkan bias rata-rata sebesar 4.80%, melampaui Response Surface Methodologydan mengonfirmasi kemampuannya yang superior dalam pemodelan nonlinier. Hasil ini menunjukkan potensi jaringan saraf MLP sebagai salah satu algoritma pemodelan untuk mempercepat penemuan dan optimasi hidrogel antibakteri ramah lingkungan dalam aplikasi bioteknologi lingkungan.
EYE DISEASE CLASSIFICATION USING DEEP LEARNING: A COMPARATIVE STUDY OF MOBILENETV2, XCEPTION, AND EFFICIENTNET-B0 Agustini, Latifa Zahra; Bimantoro, Fitri; Dwiyansaputra, Ramaditia
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.
PENGEMBANGAN SISTEM INFORMASI PORTOFOLIO PEMBELAJARAN UNTUK MENDUKUNG MANAJEMAN CAPAIAN PEMBELAJARAN MATAKULIAH BERBASIS OBE (STUDI KASUS DI PROGRAM STUDI TEKNIK INFORMATIKA) Anjarwani, Sri Endang; Ali Albar, Moh; Bimantoro, Fitri; Agitha, Nadiyasari; Zafrullah M., Ahmad; Gerald Dennaya HD, Muh.
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.v8i1.530

Abstract

The Information Technology Study Program (PSTI) implements an OBE-based curriculum to measure graduate achievement (CPL) and course learning achievement (CPMK), requiring lecturers to compile learning achievement reports in the form of portfolios at the end of each semester. The compilation of portfolios is supplemented with CPL and CPMK results calculated using Microsoft Excel. During the preparation of the report, difficulties arise when changing data that affects the formula. Not all lecturers understand the available formulas and equations. The purpose of this research is to develop an information system to support the preparation of lecturers' course learning portfolio reports. The method used is Extreme Programming, which is an Agile software development approach with the stages of Planning, Design, Coding, Testing, and Release Phase (Deploy). This research resulted in a Learning Portfolio Information System to Support OBE-Based Course Learning Achievement Management (Case Study in the Informatics Engineering Study Program). In this information system, lecturers can manage CPL, CPMK, Sub_CPMK, Assessment, Evaluation, Results, and Portfolio data. From testing using User Acceptance Testing, the results obtained were an average of 37% strongly agree, 43% agree, and 19% somewhat agree. Therefore, it can be said that the information system created can be used properly.
Development of a Web‑Based Biodiversity Information System of the University of Mataram Using WordPress and Custom Plugins: PENGEMBANGAN SISTEM INFORMASI KEANEKARAGAMAN HAYATI UNIVERSITAS MATARAM BERBASIS WEBSITE MENGGUNAKAN WORDPRESS DAN CUSTOM PLUGIN Effendy, Michael; Bimantoro, Fitri; Prasetyo, Andrie Ridzki; Latifah, Sitti
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.v7i1.1408

Abstract

Dokumentasi dan akses terhadap data keanekaragaman hayati di lingkungan Universitas Mataram saat ini masih tersebar dan belum terorganisir dengan baik, sehingga menyulitkan kegiatan konservasi, penelitian, dan edukasi. Melalui kegiatan pengabdian kepada masyarakat ini, telah dikembangkan sebuah sistem informasi berbasis website untuk mengatasi permasalahan tersebut. Sistem dikembangkan menggunakan platform wordpress dengan metode prototyping, yang melibatkan partisipasi aktif dari Laboratorium Manajemen Hutan dalam tiga iterasi pengembangan. Untuk memenuhi kebutuhan yang spesifik, kami juga mengembangkan custom plugin menggunakan bahasa pemrograman PHP. Hasil dari kegiatan ini adalah Sistem Informasi Keanekaragaman Hayati (SEHATI UNRAM) yang dapat digunakan secara fungsional. Sistem ini memiliki fitur seperti pengelolaan data tanaman yang kompleks, manajemen gambar dalam jumlah banyak, backup data, dan pembuatan QR code secara massal. Berdasarkan pengujian menggunakan metode black box terhadap 52 test case, seluruh fitur berjalan dengan baik. Sistem ini diharapkan dapat menjadi solusi yang efektif untuk mendokumentasikan dan menyebarluaskan informasi keanekaragaman hayati di Universitas Mataram.
Co-Authors A.A.Sg. Mas Karunia Maharani Ade Ragil Purwandani Adi Sugita Pandey Afwani, Royana Agitha, Nadiyasari Agus Eko Minarno Agustini, Latifa Zahra Ahmad Dia’ul Haqqi Ahmad Zafrullah Mardiansyah Aisyah, Yunda Aldian Wahyu Septiadi Ali Albar, Moh Alif Sabrani Aliyah Fajriyani Alwi Pratama Anita Rosana MZ Anjarwani, Sri Endang Annisa Mujahidah Robbani Anugrah, Febrian Rizky Aohana, Mizanul Ridho Aprilla, Diah Mitha Aranta, Arik Arik Aranta Arik Aranta Ario Yudo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo, Ario Yudo Arrie Kurniawardhani arrie kurniawardhany, arrie Ayu Septya Maulani B. Nurwahyu Hairani Bagaskara, Andhika Dwija Baiq Rizki Putri Utami Budi Irmawati Chaerus Sulton Cokro Mandiri, Mochammad Hazmi Daniel Swanjaya Darmawan, Riski dina hastari Dina Juliani U M, Eka Ditha Nurcahya Avianty Dwiyansaputra, Ramaditia Effendy, Michael Ellysabeth Usmiatiningsih Fachry Abda El Rahman Fadilah . Fahmi Syuhada Faqih Hamami fathin zulian tsany Fernanda Dicky Ivansyah Fiena Efliana Alfian Fuad Fadlila Surenggana Fuad Fadlila Surenggana Gerald Dennaya HD, Muh. Gibran Satria Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Grendis, Nuraqilla Waidha Bintang Haidar Rahman Haidra Rahman Halil Akhyar Hamidi, M. Zaenuddin Hamidi, Mohammad Zaenuddin Hanung Adi Nugroho Hendrawan Heri Wijayanto Hidhayah, Ratu Nisful Laily husnul khotimah I B K Widiartha I Gede Andika I Gede Pasek Suta Wijaya I Gede Putu Wirarama Wadashwara Wirawan I Gede Putu Wirarama Wedashwara W I Gede Wirarama Wedashwara W. I Putu Teguh Putrawan I Putu Teguh Putrawan I Wayan Agus Arimbawa I Wayan Agus Arimbawa, I Wayan Agus Ibrahim, Zaidah Ida Bagus Ketut Widiartha Ida Bagus Ketut Widiartha Imam Tantowi Isye Arieshanti Jatmika, Andy Hidayat Kansha, Lyudza Aprilia Lalu Zulfikar Muslim Lidia Ardhia Wardani Liza Yuliana Khairani Marcellino, Hendy Maulana Surya Negara Maulana, Sutan Fajri Mizanul Ridho Aohana Moh. Ali Albar Moh. Azzam Al Husaini Muhamad Irzan Muhammad Afif Ma'ruf Muhammad Daden Kasandi Putra Wesa Muhammad Edy Kurniawan Basri Muhammad Giri Restu Adjie Muhammad Hadi Muhammad Hadiasri Muhammad Khaidar Rahman Muhammad Sholihul Hamdi Muhammad, David Arizaldi Muntari Muntari Murpratiwi, Santi Ika Nanik Suciati Nazibullah Nazibullah Ni Nyoman Citariani Sumartha Nindya Alita Rosalia Noor Alamsyah Novanita Laylatul Husna Novita Nurul Fakhriyah Nugraha, Gibran Satya Nuraqilla Waidha Bintang Grendis Nurhaini Rahmawati Nurhalimah Nurhalimah Obenu, Juanri Priskila Patriaji Ibrahim Maulana Prasetyo, Andrie Ridzki Prof. I Gede Pasek Suta Wijaya Putu Wahyu Pratama Rabbani, Budiman Raihan, Muhammad Dzulhi Ramadhani, Rizky Insania Ramadian Ridho Illahi Ramaditia Dwiyansaputra Ramaditia Dwiyansaputra Ramdhani, Ghina Kamilah Ramlah Nurlaeli Rani Farinda Regania Pasca Rassy Rijalul Imam Rina Lestari Riska Yulianti Rival Biasrori rizka amalia Rizki Rahmadi Rizqullah, Muhammad Naufal Robert Silas Kabanga Rosalina Rosalina Salma Nabilla Ulpa Salsabila Putri Rajani Said Satya Nugraha, Gibran Setiawan, Lalu Rudi Sitti Latifah Susi Rahayu Suwardiman Suwardiman Tazkiya Aulia Rachman Teguh Ardian Samudra Ulandari, Alisyia Kornelia Umbara Diki Pratama Wahyu Alfandi Wildan Suharso Yogi Permana Yudhis, Putu Yudhis Yudo Husodo, Ario Yufis Azhar Yunia Puspita Wulandari Zafrullah M., Ahmad Zubaidi, Ariyan Zuhraini, Marlia Zul Rijan Firmansyah