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PRIMARY QUERY ANALYSIS ON SQL DATABASE RESTRUCTURING IN GEOGRAPHIC INFORMATION SYSTEMS Ridwan Ilyas; Wina Witanti; Fildzah Syarafina
JIKO (Jurnal Informatika dan Komputer) Vol 7 No 2 (2024)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8565

Abstract

Database restructuring is a crucial process aimed at enhancing data management and access efficiency by modifying the existing data structure. This research focuses on improving a Geographic Information System (GIS) for taxation by migrating and restructuring an inefficient and redundant database. The study conducts a comparative performance evaluation of the old and restructured databases using benchmarking tests with varying numbers of threads and ramp-ups. The results reveal a significant increase in average throughput (24.60%) following the restructuring, indicating a substantial improvement in the database's data processing capacity. However, there is also an average increase in response time (21.65%), suggesting a trade-off between enhanced throughput and slower response times. This increase in response time indicates that while the system can handle more data, it requires more time to process each query. Overall, the restructured database demonstrates enhanced performance and efficiency, though further optimization is necessary to achieve consistent throughput across different workloads and to mitigate the increased response times
Klasifikasi Emosi pada Kalimat Bahasa Indonesia Menggunakan Transformer Rey Aji Darusalam; Ridwan Ilyas; Fatan Kasyidi
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.2457

Abstract

Text-based emotion classification is a challenging task in natural language processing, particularly for Indonesian, which has flexible sentence structures and varied informal language usage. This study aims to develop an emotion classification model for Indonesian sentences using a Transformer-based approach, specifically leveraging the IndoBERT model. The dataset employed is an adaptation of the SemEval 2025 benchmark, translated into Indonesian, and includes five emotion categories: anger, fear, joy, sadness, and surprise. The research process involves data preprocessing through IndoBERT tokenization, padding, label encoding, and the implementation of three data balancing strategies: Synthetic Minority Oversampling Technique (SMOTE), class weighting, and random oversampling. Fine-tuning of IndoBERT is conducted using the [CLS] token representation as the main feature for classification. Evaluation is performed for all balancing approaches using accuracy, precision, recall, and F1-score metrics. Results indicate that SMOTE achieves the highest accuracy at 58.31%, while the class weight approach yields the highest recall at 48.22%. Random oversampling demonstrates relatively stable performance across all metrics. The surprise emotion category is the most challenging class to recognize across all three approaches, highlighting the need for improvements in data and model design. Additionally, all models exhibit mild overfitting, as evidenced by performance differences between training and validation datasets. These findings demonstrate that IndoBERT can be effectively used for emotion classification in Indonesian sentences, with performance significantly influenced by the data balancing strategy employed. This study provides an initial insight valuable for the development of emotion classification systems that account for the context and characteristics of the Indonesian language.
Co-Authors Achmad Aziz Adriana, Reyhan Agung Besti Akbar, Tzazkia Febriyana Aminuddin Ihsan, Aminuddin Ari Sri Windyaswari Ari Sri Windyaswari, Ari Sri Ariq Irawan, Muhamad Asendra, Irfan Asep Saepul Ridwan Ashaury, Herdy Aziz, Achmad Azmira Mifti Harjana Besti, Agung Chandani Nurul Hafizah Destri Wulansari Dhimas Ariya Wibiksana Djamal, Esmeralda Contesa Dwi Hendratmo Widyantoro Dwifani, Bella Melati Wiranur Eddie Khrisna Putra Eriyadi, Maulidina Norick Esmeralda C Djamal Esmeralda C Djamal Esmeralda C. Djamal Esmeralda C. Djamal Esmeralda Contessa Djamal Fadhilahsyah Ramadhan, Muhammad Diky Fahrauk Faramayuda, Fahrauk Fajri Rakhmat Umbara Fajri Umbara Fatimah Indrianti, Nisa Fildzah Syarafina Fitri Nur Suciani Gunawan Abdillah Gunawan Abdillah, Gunawan Hadiana, Asep Id Hidayat, Ferdian Afza Iqbal Prayoga Willyana Ismail, Nursafira Khairunnisa Iyan Taufik Hidayat Janjan Nurjaman Kania Ningsih, Ade Kasyidi, Fatan Komarudin, Agus Luthfi Ahmad Fadhil Masayu Leylia Khodra Maulidina Norick Eriyadi Melina Melina Muhamad Ramdan, Muhamad Muhamad Rizal Firmansyah Muhammad Ramdhani, Muhammad Muhammad, Azri Naufal Akhfasy, Muhammad Neneng Nurhamidah NIDA MUTHI ANNISA Nur Shabrina, Nariswari Nurhamidah, Neneng Nursafira Khairunnisa Ismail Nurul S, Puspita Nurul Sabrina, Puspita Paramita, Veronika Santi Purnama Ginandjar, Ichas Putra, Dion Revaldy Putri, Dhiffa Namira Alifia Ramdani, Maullidan Alfa Rizki Fikri Ramdhan, Edvin Resa Abdilah Rey Aji Darusalam Reyhan Adriana Deris Reza Dwi Putra Reza Indrawan Rezki Yuniarti Rezky Yuniarti ridwan fauzi Rifaz Muhammad Sukma Rizka Khoirunnisa Guntina Rizki Kurniawan, Moch. Sopian, Annisa Mufidah Susilowati, Merliana Tri Syarafina, Fildzah Tzazkia Febriyana Akbar Wildan Pratama Wina Witanti Wina Witanti Yamina Azmi Yoga Esa Mahendra Yulison Herry Chrisnanto Yustiana Fauziyah