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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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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.
Comparison of CNN’s Architecture GoogleNet, AlexNet, VGG-16, Lenet -5, Resnet-50 in Arabic Handwriting Pattern Recognition Nugraha, Gibran Satya; Darmawan, Muhammad Ilham; Dwiyansaputra, Ramaditia
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 2, May 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i2.1667

Abstract

The Arabic script is written from right to left and consists of 28 characters, with no capital or lowercase letters. The Arabic script has several orthographic and morphological properties that make handwriting recognition of the Arabic script challenging. In addition, one of the biggest challenges in recognizing Arabic script patterns is the different handwriting styles and characters of each person's writing. The authors propose a study to compare the accuracy of handwriting pattern recognition in Arabic script which has been done previously by comparing five CNN architectures, namely GoogleNet, AlexNet, VGG-16, LeNet-5, and ResNet-50. Considering that previous research has not obtained excellent accuracy. The number of datasets used is 8400 image data and the most optimal comparison of testing and training data is 80:20. Based on the research that has been done, there are several things that the author can conclude. The model is made using 64 filters for each convolution layer because the optimal size is used for 5 architectures, kernel size is 3x3, neurons is 128, dropout weight is 50% to reduce overfitting, learning rate is 0.001, image size is 64x64, the normalization method with the ReLU activation function, and 1-dimensional input image (grayscale), and with a comparison of testing and training data of 80:20. The VGG-16 architectural model is the architecture that gets the highest score, namely 83.99%. This can have good potential to be developed as a medium for learning Arabic script.
IMPLEMENTASI LENET-5 DAN MOBILENET-V2 UNTUK KLASIFIKASI KEMATANGAN BUAH CABAI BERBASIS COMPUTER VISION Hadi, Risman; Dwiyansaputra, Ramaditia; Irfan, Pahrul
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12725

Abstract

Tingginya konsumsi cabai rawit menjadikannya komoditas dengan permintaan yang selalu tinggi, sehingga memiliki nilai ekonomi yang signifikan bagi para petani . Terlebih lagi, makanan khas Pulau Lombok seperti pelecing kangkung, ayam taliwang, dan bebalung sangat ditentukan cita rasanya oleh cabai sebagai salah satu bahan utama untuk bumbu. Permintaan cabai yang cenderung tinggi sepanjang tahun tanpa mengenal musim menciptakan tantangan dalam pengelolaan kualitas cabai di pasaran. Identifikasi kualitas buah cabai yang masih dilakukan secara visual oleh petani sering kali menghasilkan kesalahan dalam proses sortir yang dapat merugikan konsumen. Oleh karena itu, diperlukan penerapan teknologi computer vision untuk mengatasi masalah ini. Penelitian ini mengimplementasikan arsitektur CNN yaitu Lenet-5 dan MobileNet-V2. Lenet-5 memiliki kelebihan dalam kesederhanaan struktur dan kebutuhan komputasi yang rendah, sehingga cocok digunakan pada perangkat dengan sumber daya terbatas. MobileNet-V2 memiliki unggul dalam efisiensi parameter dan kinerja yang optimal untuk perangkat mobile atau aplikasi real-time. Hasil penelitian menunjukkan bahwa model arsitektur Lenet-5 menunjukkan performa lebih baik dengan accuracy 99%, precission 1.00, recall 1.00 dan F-1 Score 1.00, sedangkan model arsitektur MobileNet-V2 memiliki accuracy 100%, precission 1.00, recall 1.00 dan F-1 Score 0,95. Hal tersebut menunjukkan potensi computer vision berbasis CNN untuk meningkatkan akurasi dan efisiensi dalam klasifikasi tingkat kematangan buah cabai.
Implementation of Digital Marketing Strategy for UMKM in Keroya Village, East Lombok through Optimization of Promotional Design Using Canva: IMPLEMENTASI STRATEGI DIGITALISASI MARKETING DI UMKM DESA KEROYA LOMBOK TIMUR MELALUI OPTIMALISASI DESAIN PROMOSI MENGGUNAKAN CANVA Akhyar, Halil; Bimantoro, Fitri; Dwiyansaputra, Ramaditia; Hamidi, Mohammad Zaenuddin; Maulana, Sutan Fajri; Rahayu, Susi
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 6 No. 1 (2025): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v6i1.1362

Abstract

Desa Keroya memiliki potensi pengembangan ekonomi karena memiliki banyak pelaku usaha mikro di sektor pertanian dan perkebunan. Upaya yang dilakukan untuk mendukung daya saing pelaku usaha mikro dengan mengadakan kegiatan pelatihan digitalisasi marketing. Kegiatan bertujuan untuk meningkatkan pemahaman dan keterampilan dalam strategi promosi menggunakan canva. Kegiatan ini mencakup pelatihan penggunaan aplikasi canva sebagai alat desain promosi serta pengenalan teknis pemasaran berbasis digital. Metode yang diterapkan dalam pelatihan meliputi pendekatan Participatory Rural Apprasial (PRA), Economic Empowerment Model, Technological Empowerment Model, dan edukatif. Hasil evaluasi menunjukkan bahwa pelatihan ini meningkatkan kesadaran peserta terhadap pentingnya digitalisasi marketing serta kemampuan peserta dalam merancang materi promosi secara mandiri. Namun, tantangan seperti keterbatasan perangkat teknologi dan tingkat literasi digital yang beragam menjadi hambatan. Banyak pelaku usaha yang masih kesulitan memanfaatkan platform digital secara optimal karena masih kurangnya pemahaman. Tanpa dukungan yang tepat, kesenjangan digital ini dapat mempengaruhi daya saing pasar yang semakin kompetitif. Oleh karena itu, diperlukan pendampingan berkelanjutan serta peningkatan akses teknologi guna memastikan keberlanjutan program ini. Kolaborasi antara akademisi, pemerintah desa, dan masyarakat menjadi factor kunci dalam mendukung pemberdayaan UMKM melalui digitalisasi marketing.
PERBAIKAN KESALAHAN KATA MENGGUNAKAN KOMBINASI JARO-WINKLER & JACCARD SIMILARITY Tresna, I Made Agus; Dwiyansaputra, Ramaditia; Akhyar, Halil
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 1 (2025): Maret 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i1.435

Abstract

Word error correction is challenging due to the variety of errors. This research proposes a combination of two similarity algorithms to improve accuracy. The objective is to evaluate how each algorithm responds to different types of spelling errors and to assess the effectiveness of their combined performance. Jaro-Winkler determines initial similarity by assigning more weight to word prefixes, effectively addressing errors due to transposition and character omission. This algorithm excels in scenarios where the beginning of the word is critical to identifying the correct candidate. In contrast, Jaccard similarity filters candidates based on character set similarity, which helps assess the overall composition similarity of the word but does not consider character order. The test results show that Jaro-Winkler is more dominant in providing relevant correction candidates, with higher accuracy in the 1-best (68.94%) and 5-best (90.78%) scenarios compared to Jaccard (55.25% and 78.42%). This performance difference suggests that Jaro-Winkler is more suitable for the initial screening of candidates. The combination of the two algorithms proved to be more effective in handling different types of word errors than when used separately, resulting in a more robust overall correction mechanism.
KLUSTERING TOPIK PADA KOLOM KOMENTAR INSTAGRAM TENTANG KABINET MERAH PUTIH MENGGUNAKAN METODE K-MEANS Rahayu, Sefani Cahyo Auliya; Dwiyansaputra, Ramaditia; Husodo, Ario Yudo
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 1 (2025): Maret 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i1.455

Abstract

This research attempts to determine the primary themes that Indonesians talked on President Prabowo Subianto's "Merah Putih" cabinet by using clustering analysis of Instagram comments. Using crawling data from the Instagram platform with the hashtag #KabinetMerahPutih, comments were gathered using the K-Means Clustering approach. Prior to the data being analyzed to create five clusters, the cleaning and pre-processing procedure, which included tokenization with IndoBERT and dimensionality reduction using Principal Component Analysis (PCA), was able to greatly improve the clustering quality, with the Silhouette Coefficient value rising from 0.010 to 0.200. Out of 23.780 initial data, 9.320 clean data were processed for this investigation. The findings demonstrate that the K-Means algorithm can group comments according to pertinent themes and offer profound understanding of support more responsive public policy analysis.
OPTIMALISASI LAYANAN SISTEM INFORMASI MAHASISWA DENGAN INTEGRASI TELEGRAM : CHATBOT RETRIEVAL-AUGMENTED-GENERATION BERBASIS LARGE LANGUAGE MODEL Hidayat, Lalu Ramdoni; Wijaya, I Gede Pasek Suta; Dwiyansaputra, Ramaditia
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 1 (2025): Maret 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i1.459

Abstract

Kemajuan teknologi telah memberikan dampak yang cukup signifikan dalam berbagai bidang, termasuk salah satunya Pendidikan. Dalam aspek Pendidikan permasalahan yang dihadapi adalah keterbatasan akses mahasiswa terhadap informasi akademik secara cepat dan efisien. Untuk mengatasi hal ini, penelitian ini bertujuan mengembangkan chatbot berbasis Telegram yang mampu memberikan respons informatif, akurat, dan ringkas terhadap pertanyaan pengguna terkait akademik di program studi Teknik Informatika. Chatbot ini memanfaatkan metode Retrieval-Augmented-Generation (RAG) untuk memproses informasi dari dokumen teks secara efisien. Metode RAG digunakan untuk menemukan jawaban yang relevan dari dokumen berdasarkan pertanyaan pengguna, sementara Large Language Model memahami konteks pertanyaan dan menghasilkan jawaban yang sesuai. Penelitian ini menggunakan pendekatan Research and Development (R&D) dengan tahapan meliputi survei questioner kebutuhan mahasiswa, preprocessing data, Pembangunan indeks pencarian berbasis vektor, konfigurasi model LLM, serta integrasi chatbot dengan Telegram. Hasil pengujian menunjukkan bahwa chatbot mampu memberikan jawaban dengan akurasi tinggi dan waktu respons rata-rata 60 detik untuk pertanyaan sederhana hingga kompleks, sehingga chatbot berbasis RAG cukup efektif meningkatkan aksesibilitas informasi secara real-time. Pengembangan lebih lanjut dapat difokuskan pada peningkatan pemahaman terhadap beragam pertanyaan dan personalisasi respons.
PENDEKATAN SENTIMEN BERBASIS ASPEK PADA ULASAN SIRKUIT MANDALIKA MENGGUNAKAN CNN DAN REPRESENTASI FASTTEXT Manuaba, Ida Bagus Ryand Wirayana; Dwiyansaputra, Ramaditia; Hamidi, Mohammad Zaenuddin
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 1 (2025): Maret 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i1.460

Abstract

Reviews are texts that contain an assessment or comment on something and can be used to provide more in-depth information. This research aims to analyze community reviews of the Mandalika Circuit using the aspect-based sentiment analysis technique CNN method. The CNN model is trained using two types of word embedding, namely Keras and FastText, and supported by the Multilabel Stratified K-Fold Cross Validation method to ensure an even distribution of data on each label and produce a stable accuracy evaluation. The results show that CNN with FastText word embedding has a higher average accuracy than CNN with Keras word embedding for both aspect and sentiment classification tasks. However, the model had difficulty in classifying the positive class in the sentiment label, which was due to the smaller amount of review data with positive sentiment than neutral and negative. Therefore, for future research, it is recommended to use data augmentation techniques on the imbalanced classes to improve the accuracy of the model.
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.
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