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Journal : journal of computer science and informatics engineering j-cosine

Pengenalan Pola Tulisan Tangan Aksara Bima menggunakan Ciri Tekstur dan KNN: Handwriting Recognition of Bima Script using Texture Features and KNN Fitri Bimantoro; Arik Aranta; Gibran Satya Nugraha; Ramaditia Dwiyansaputra; Ario Yudo Husodo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 1 (2021): June 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i1.387

Abstract

As the fact, that is Bima script did not familiar to bimanese, Bima script as a cultural heritage needs to be preserved. Pattern recognition has been used to recognize several of ancient script. Gray Level Co-occurence Matrix (GLCM) as features exctraction and K Nearest Neighbour (KNN) as a classifier show the good performance to recognize of an ancient script. so, in this research we use GLCM and KNN to recognize Bima script. we use 2640 images of handwritting bima Script that is collected from 10 volunter. Each volunter write 22 of Bima script twelve times each script. The experimental result show that the performance of our model is good enough, with 60.86% of accuracy that is obtained by manhattan distances.
Pengelompokan Provinsi di Indonesia Berdasarkan Indikator Pendidikan Menggunakan Metode K-Means Clustering: Grouping Provinces in Indonesia Based on Education Indicators Using the K-Means Clustering Method Mindi Richia Putri; Gibran Satya Nugraha; Ramaditia Dwiyansaputra
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 7 No 1 (2023): June 2023
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v7i1.509

Abstract

The education level of the Indonesian people has improved, but has not yet reached the entire population. The educational disparity that occurs between economic groups is still a problem and widens as the level of education increases. The education gap is also still high when compared between regions. Quality learning also has not run optimally and evenly between regions. Accurate and complete information is needed as a reference in planning and determining the right strategy in facing development challenges in the education sector. This information is expected to explain the current condition and situation of education development in Indonesia. This study aims to group provinces in Indonesia based on educationalindicators using the K-Means method. The data and parameters used are based on a portrait of education statistics in Indonesia in 2020. This study shows that clustering produces the best cluster quality at K=3 based on the Silhouette Coefficient
Perancangan Mesin Klasifikasi Menggunakan Particle Swarm Optimization: Designing A Classification Machine Using Particle Swarm Optimization Made Agus Dwiputra; I Gede Pasek Suta Wijaya; Ramaditia Dwiyansaputra
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 2 (2024): Desember 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i2.614

Abstract

Designing an effective classification engine is very important in various pattern recognition and machine learning applications. In this research, the Particle Swarm Optimization (PSO) algorithm is applied for the development of classification engines on various datasets. PSO is a population-based optimization method inspired by the behavior of flocks of birds or fish, which is effectively used to find optimal solutions in large search spaces. This research aims to develop a classification model by using Particle Swarm Optimization (PSO) as a training element to determine weights and biases. To test the performance on several different datasets, namely on a dummy multi-class dataset, Sasak Aksara image dataset, and the well-known Iris dataset. In the Sasak Aksara data, Discrete Cosine Trasnform (DCT) is used as feature extraction with the aim of reducing computation time. The results show that PSO can be used in the implementation of several datasets used, in the classification of dummy data, iris data, and Sasak Aksara image data. The model achieved 100% accuracy, precision, recall, and F1-Score on dummy data and iris data. However, on the Sasak Aksara image dataset, the performance of the model decreased with accuracy only reaching 65%, precision 50%, recall 32%, and F1-Score 39%. This research contributes in demonstrating the effectiveness of PSO in optimizing Perceptron models on simpler datasets and highlights the need for further development to handle more complex datasets.
Prototyping Interface for a Website-Based Visitor Management System of Gili Tramena: A Design Thinking Approach: Prototipe Antarmuka Visitor Management System Gili Tramena Berbasis Website: Sebuah Pendekatan Design Thinking Amara, Nadya; Noor Alamsyah; Ramaditia Dwiyansaputra
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 9 No 1 (2025): Juni 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.v8i1.632

Abstract

Gili Tramena which stands for Gili Trawangan, Gili Air and Gili Meno. The three Gili Islands are one of the tourist destinations that are visited by many tourists, both local and foreign tourists because of their underwater power. The high flow of tourists has both positive and negative impacts from an economic, social and environmental perspective. The positive impacts of increased tourism include economic improvement in Gili Tramena, globalization of Indonesian tourism, and improvement of public infrastructure. The negative impacts of increased tourism include cultural change, economic dependency, degraded water quality, and damage to coral reefs. These negative impacts will continue if the number of tourists continues to increase. One way to prevent this is to limit the number of visitors to Gili Tramena each day. Tourist data collection, which is still done manually, is also the reason for the difficulty in controlling tourists entering Gili Tramena. One way to streamline visitor data collection is through a Visitor Management System (VMS). This VMS will help to collect data systematically. Therefore, it is necessary to design a UI/UX VMS information system to limit and control visitors entering Gili Tramena. The UI/UX design of the Tramena VMS was carried out using the Design Thinking approach with 5 stages, namely Emphatize, Define, Ideate, Prototype, and Test. Based on the results of testing using the SUS (System Usability Score) method, a score of 85.92 was obtained, which indicates that this system is included in the "Excellent" category, with the UI/UX design meeting high standards in terms of usability, efficiency, and overall user experience. It is expected that this system can be further developed with the actual implementation of the designed design.
Rancang Bangun Algoritma Konversi Bahasa Indonesia Latin Menjadi Bahasa Sasak Latin Menggunakan Metode Sequence-To-Sequence Transformers Muhammad Giri Restu Adjie; Ramaditia Dwiyansaputra; Fitri Bimantoro; Arik Aranta
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 9 No 1 (2025): Juni 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.v9i1.619

Abstract

Bahasa Sasak adalah bahasa daerah yang digunakan di Nusa Tenggara Barat, yang menghadapi tantangan dalam mempertahankan penggunaannya, terutama di kalangan generasi muda, karena dominasi bahasa Indonesia di lingkungan formal. Penelitian ini mengeksplorasi tantangan-tantangan tersebut dan menyoroti pentingnya melestarikan bahasa Sasak sebagai identitas sosial dan budaya yang penting bagi masyarakat Sasak. Penelitian ini bertujuan untuk mengembangkan sistem penerjemah mesin untuk menerjemahkan bahasa Indonesia ke bahasa Sasak dengan menggunakan metode Sequence-to-Sequence Transformer. Dengan menggunakan model Transformer dengan arsitektur berbasis encoder-decoder, penelitian ini menerjemahkan teks bahasa Indonesia ke bahasa Sasak, dengan memanfaatkan metode Rule-Based untuk preprocessing dataset. Dataset yang digunakan terdiri dari lebih dari 85.290 baris pasangan teks bahasa Indonesia-Sasak, yang dibagi menjadi set training, validasi dan testing. Pelatihan yang dilakukan oleh model ini mencapai hasil akhir akurasi setelah 30 epoch sebesar 0.99 dan akurasi validasi sebesar 0.98 serta dengan skor 6.075 dalam evaluasi Bilingual Evaluation Understudy (BLEU). Hal ini menunjukkan kemampuan model yang kuat untuk menghasilkan terjemahan yang akurat, meskipun bahasa Sasak adalah bahasa yang kompleks. Penelitian ini tidak hanya untuk melestarikan bahasa Sasak tetapi juga membuka jalan baru bagi para peneliti di masa depan dalam pemrosesan dan pelestarian bahasa, terutama untuk bahasa yang memiliki sumber daya yang lebih sedikit seperti bahasa Sasak.
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.
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