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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Keperawatan Jiwa (JKJ): Persatuan Perawat Nasional Indonesia Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) MULTINETICS Jurnal Keperawatan Widya Gantari Indonesia Indonesian Journal of Electrical Engineering and Computer Science Khatulistiwa Nursing Journal Jurnal Locus Penelitian dan Pengabdian Majalah Cendekia Mengabdi Journal Of Engineering Sciences (Improsci) The Indonesian Journal of Computer Science Jurnal Gawat Darurat
Budi, Indra
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Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary

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Indonesian sentiment analysis in natural environment topics Octovianto, Christofer; Ibrohim, Muhammad Okky; Budi, Indra
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1353-1366

Abstract

Indonesia is one of the countries that is rich in biodiversity and has a high population growth. This condition can cause Indonesia to have problems related to the natural environment that are more complex than other countries. Hence, this has created a lot of discussions regarding natural environmental issues in Indonesia on social media platforms. In this case, stakeholders like the government in general can utilize sentiment analysis (SA) to comprehend the public’s views to allow them to better fit the public’s expectations when formulating a particular policy that related to the environmental sustainability (ES) issues. This paper built the first open dataset of Indonesian SA dataset in ES topics collected from Instagram. As the benchmark of our dataset, we used IndoBERT model variant for constructing the model and the experiment result shows that model based on IndoBERT-large-p2 obtained the best performance with 72.44% of F1-score.
Utilizing Translation to Enhance NLP Models in Offensive Language and Hate Speech Identification Kurniawan, Sandy; Budi, Indra
Jurnal Improsci Vol 1 No 4 (2024): Vol 1 No 4 February 2024
Publisher : Ann Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/improsci.v1i4.187

Abstract

The number of social media users in Indonesia has increased in recent years. The surge in social media users leads to more offensive language on these platforms. The use of offensive language can trigger conflicts between users. Therefore, it is necessary to identify the use of offensive language on social media. This study focused on identifying offensive language, hate speech, and hate speech targets on Twitter. The data used were obtained from previous research on identifying offensive language and hate speech. The amount of data is very influential on the performance of the classification. Therefore, data was added using translation in this study. Classical machine learning (SVM et al.) and deep learning (BiLSTM, CNN, and LSTM) algorithms are used as classification algorithms with word n-gram and word embedding as the features. Three scenarios were done based on the training data used in the classification model development. The result shows that scenario 3, which uses translation for data augmentation, can improve the classification model’s performance by 5%.
Uncovering the Reasons Behind Abstain Voters' Stances in the 2024 Indonesian Presidential Election: Social Media X Study Cases Putri, Irzanes; Insani, Faiz Nur Fitrah; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4126

Abstract

The Indonesian Government expects the participation of all Indonesian people in holding General Elections. However, according to the 2019 Political Statistics by BPS, there were 34.75 million people who did not exercise their right to vote or were abstain voters (golput) in the 2019 Election. This research aims to analyze individual attitudes towards abstaining voters using stance analysis and topic modelling. From 9,045 collected tweets, subsequent manual annotation revealed 2,566 pro stances, 5,264 neutral stances, and 1,215 contra stances. The classification models utilized are Random Forest, Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Gradient Boosting. The classification outcomes will be analyzed by comparing the accuracy, precision, recall, and F1-score results based on their algorithms and n-grams. The results obtained from the stance analysis show that Random Forest achieved the highest accuracy and precision scores, with values of 84% and 83%, respectively. The discussion topic among those supporting golput due to low trust in the presidential and vice-presidential candidates. Other topics mentioned public feels dissatisfied with the pairs of candidates.
Perbandingan Random Search dan Algoritma Genetika dalam Penyetelan Hyperparameter XGBoost pada Retail Sales Forecasting Tiastama, Sheren Afryan; Budi, Indra
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4285

Abstract

Sales is part of the important factor that influences a company in determining two things, namely profits and losses on the company. The right strategy to determine the amount of sales can be done through forecasting. Therefore, sales forecasting requires the right technique to produce accurate results. Machine learning has been proven to help overcome sales forecasting, one of which is XGBoost. However, XGBoost has many hyperparameters that affect its performance, it requires a hyperparameter setting method to produce an optimal hyperparameter. Random searches and genetic algorithms are optimized methods to find the optimal hyperparameter on XGBoost. The two methods of optimization were compared in this study with the measurement of RMSE performance in doing retail sales forecasting on the sales data of the retail company Rossmann Store which comes from the Kaggle site. The research obtained random search results superior to the genetic algorithm with RMSE values on the training process and the testing process are 0.123 and 0.122. Meanwhile, the RMSE values generated by genetic algorithms in the training and testing process are 0.333 and 0.332.
Dukungan Pasangan Terhadap Kepatuhan Diet Penderita Diabetes Melitus Tipe 2 Muthmainnah, Miftahul; Tjomiadi, Cynthia Eka Fayuning; Budi, Indra; Rakhmadhani, Irzal
Khatulistiwa Nursing Journal Vol. 4 No. 2 (2022): July 2022
Publisher : STIKes YARSI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53399/knj.v4i0.183

Abstract

Latar Belakang: Perubahan yang terjadi selama proses kehamilan menimbulkan kecemasan pada ibu hamil. Apabila tidak ditangani, maka akan berdampak terhadap kondisi ibu dan janin. Kecemasan dapat diatasi apabila ibu hamil memiliki mekanisme koping yang baik dengan cara meningkatkan spiritual self-care. Tujuan: Tujuan penelitian ini adalah untuk mengidentifikasi hubungan spiritual self-care dengan kecemasan ibu hamil trimester III. Metode: Desain penelitian menggunakan studi cross-sectional. Penelitian dilakukan di UPT Puskesmas Kampung Dalam. Sebanyak 40 sampel ibu hamil trimester III dipilih secara purposive dengan kriteria inklusi penelitian ini yaitu ibu hamil trimester III yang berkunjung ke UPT Puskesmas Kampung Dalam Pontianak Timur, ibu hamil trimester III yang mengalami kecemasan. Pengumpulan data menggunakan instrumen penelitian yang terdiri dari kuesioner spiritual self-care practice dan kuesioner Zung self-rating anxiety scale yang telah dialih bahasa oleh peneliti sebelumnya. Hasil: Hasil uji statistik dengan korelasi Kendall’s tau-b menunjukkan bahwa terdapat hubungan yang bermakna antara spiritual self-care dengan kecemasan ibu hamil trimester III dengan nilai p = 0,038 (p Kurang dari 0,05). Kesimpulan: Terdapat hubungan yang bermakna antara spiritual self-care dengan kecemasan ibu hamil trimester III.
Analisis Sentimen Berbasis Aspek dan Pemodelan Topik pada Candi Borobudur dan Candi Prambanan Arianto, Dian; Budi, Indra
MULTINETICS Vol. 8 No. 2 (2022): MULTINETICS Nopember (2022)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v8i2.5056

Abstract

This study focuses on conducting aspect-based sentiment analysis and topic modelling of tourism destinations in Indonesia, which are Borobudur Temple and Prambanan Temple using Google Maps and Tripadvisor user reviews. Aspect-based sentiment analysis was done using five classical machine learning algorithms, which are NaïveBayes (NB), Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and Extra Trees (ET) using the unigram+bigram+trigram feature and the application of combination of the use of training and test data, stopwords removal, stemming, emoji processing, and over-sampled training data. The performance of models was evaluated by comparing F1-scores on each experimental result. Topic modelling was carried out using Latent Dirichlet Allocation (LDA) method which evaluated by its coherence score. The results show that LR is a model that can predict data well in almost all scenarios in this study with the highest score on the Attraction aspect with a score of 84.4%, Amenity 84.2%, Accessibility 89.1%, Image 70%, and HR 92.8%. Meanwhile, DT can predict data well on the Price aspect with a score of 91.3%. From the results of topic modelling, we recommend some approaches for the development of tourism in Borobudur Temple and Prambanan Temple, one of which is the government can lower the price of admission to Prambanan Temple and Borobudur Temple for foreign tourists so that they can compete with tourist attractions in neighboring Indonesia because many reviews state that the price of entrance tickets to Prambanan Temple and Borobudur Temple is too expensive for foreigners.
User Review Analysis of the BNI Wondr Mobile Banking Application: Systematic Literature Review Mubina, Basma Fathan; Halim, Dicky; Budi, Indra; Ramadiah, Amanah; Putra, Prabu Kresna; santoso, Aris budi
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 8 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i8.4541

Abstract

In the digital age, mobile banking has become essential for facilitating efficient financial transactions, with the Wondr mobile banking application from Bank Negara Indonesia (BNI) emerging as a significant innovation in this sector. Designed to provide a secure and user-friendly experience, Wondr aims to meet the diverse needs of its customers. However, to enhance its service and ensure user satisfaction, BNI must actively engage with customer feedback. This study leverages user reviews from platforms like Google Play Store to gain insights into the strengths and weaknesses of the Wondr application. Employing text analysis techniques, we utilise topic modeling through Latent Dirichlet Allocation (LDA) to extract relevant themes from these reviews to identify key areas for improvement and generate targeted recommendations. The findings of this research are intended to inform the ongoing development of the Wondr application, ultimately enhancing user experience and reinforcing BNI’s position within the digital banking landscape.
Sentiment Analysis of Air Pollution on Social Media: Systematic Literature Review Permana, Yandi Dwi; Gofur, Abdul; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.3679

Abstract

The need for a healthy and pollution-free environment is the basis of the problem that this study examines. Social media has become an integral aspect of daily existence for the majority engaged in the digital realm. It enables individuals from various backgrounds to utilize these platforms to stay updated on the latest information, such as the current state of pollution in Jakarta. This research explores the attitudes of social media users regarding their perspectives on air pollution in Jakarta. The method used includes conducting a Systematic Literature Review of academic papers released from 2020 to 2023. The results of this research can unveil the types of social media platforms utilized, the quantity of datasets, the procedures for data collection, data preprocessing techniques, and the commonly employed methods in sentiment analysis studies concerning the subject of air pollution.
PENGALAMAN PASIEN GAGAL JANTUNG DI RSJPD HARAPAN KITA TERHADAP PERAWATAN DIRINYA DI RUMAH: STUDI FENOMENOLOGI Widiastuti, Ani; Nurachmah, Elly; Sekarsari, Rita; Budi, Indra
Jurnal Keperawatan Widya Gantari Indonesia Vol 7 No 2 (2023): JURNAL KEPERAWATAN WIDYA GANTARI INDONESIA (JKWGI)
Publisher : Nursing Department, Faculty of Health, Universitas Pembangunan Nasional "Veteran" Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52020/jkwgi.v7i2.5789

Abstract

Gagal jantung menjadi masalah kesehatan yang progresif dengan angka mortalitas dan morbiditas yang tinggi di negara maju maupun negara berkembang. Tingginya angka readmission juga menyebabkan tingginya biaya perawatan yang harus dikeluarkan, oleh karena itu diperlukan pendekatan penanganan yang baik dengan meningkatkan efektifitas perawatan diri di rumah. Penelitian ini bertujuan untuk mengeksplorasi pemahaman yang mendalam tentang pengalaman, kebutuhan dan harapan pasien gagal jantung dalam melaksanakan perawatan dirinya (self care) di rumah. Penelitian ini menggunakan desain penelitian deskriptif kualitatif dengan pendekatan fenomenologi. Pemilihan partisipan diambil dengan cara purposive sampling sebanyak delapan orang. Pengumpulan data dilakukan dengan wawancara mendalam dengan membuat pertanyaan berdasarkan tujuan yang ingin dicapai. Data yang diperoleh dianalisis dengan menggunakan langkah-langkah Colaizzi sehingga dapat disimpulkan tema-tema sesuai pengalaman partisipan. Dari hasil analisa data ditemukan dua belas tema utama yaitu : (1) pengetahuan gagal jantung (2) Tanda dan gejala yang dialami (3) respon terhadap penyakit (4) mengatur pola makan (5) mengkonsumsi obat (6) olah raga dan aktifitas (7) kontrol ke dokter (8) hambatan yang dihadapi (9) dukungan keluarga (10) dukungan informasi (11) sumber informasi (12) harapan pasien. Melalui penelitian ini, kebutuhan pasien, kesulitan yang dihadapi serta harapan terhadap perawatan dirinya dapat teridentifikasi dengan jelas. Pasien gagal jantung yang melakukan perawatan diri di rumah membutuhkan dukungan keluarga serta dukungan informasi untuk dapat menjalankan program pengobatan dengan baik. Melalui penelitian ini dapat direkomendasikan untuk disusun media edukasi dan informasi yang dapat memudahkan pasien gagal jantung dalam melakukan perawatan dirinya di rumah sehingga harapan pasien untuk dapat ditangani dengan baik dapat terlaksana.
Query keyword extraction in discriminative marginalized probabilistic neural method for multi-document summarization Subeno, Bambang; Budi, Indra; Yulianti, Evi
Indonesian Journal of Electrical Engineering and Computer Science Vol 40, No 2: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v40.i2.pp907-915

Abstract

The large number of textual documents in the medical field makes it very difficult for readers to obtain comprehensive information. Users usually use a query approach to get the desired information. Using the correct query will produce relevant information. In the existing discriminative marginalized probabilistic neural method, referred to as DAMEN, used for multi-document summarization, a background sentence query is used to retrieve the top-K relevant documents and then generate a summary of these documents. However, the background sentence query used to retrieve the top-K documents did not provide accurate summary results. The author improved the DAMEN model by adding a keyword extraction process to the query background sentence. We call this model Q-DAMEN. Our model shows significant improvement over the original DAMEN method, with the best results achieved by the variation of using a keyword query entered into the discriminator component and a background sentence query entered into the generator component. The multipartieRank keyword extraction method shows the best results with a Rouge-1 value of 29.12, Rouge-2 of 0.79, and Rouge-L of 15.53. The results demonstrate that the more accurate the keywords extracted from the sentence background query, the more accurate the multi-document summaries generated.
Co-Authors Abdul Gofur Adila Alfa Krisnadhi Agustina, Mely Angelo, Michael David Anggraini, Veny Ani Widiastuti, Ani Ardin Arianto, Dian Asmadiannor, Asmadiannor Azarya, Yosia Bagus Rahmat Santoso, Bagus Rahmat Bambang Subeno Budi Santoso, Aris Cloudia, Lorenza Dewi, Ni Gusti Agung Ayu Sri Elly Nurachmah Evi Yulianti Habibi, Nur Hakidah Halim, Dicky Harwenda, Reyhan Widyatna Heryadi, Abdi Taofan Ibrohim, Muhammad Okky Insani, Faiz Nur Fitrah Irmawan, Oky Ade Istiqomah, Relaci Aprilia Izzuddin, Muhammad Sulthan Kresna Putra, Prabu Kurniawan, Sandy M. Sobirin Mohtar Melda, Melda Mohammad Basit, Mohammad Mubina, Basma Fathan Munawarah Munawarah, Munawarah Muthmainnah, Miftahul Nataly, Onevia Berlian Octovianto, Christofer Permana, Yandi Dwi Prabu Kresna Putra, Prabu Kresna Prastowo, Rahardito Dio Putri, Irzanes Rakhmadhani, Irzal Ramadiah, Amanah Rizka Windiastuti, Rizka Rosalina, Nadya Sahid, Irfanda Husni Santoso, Aris Budi Sekarsari, Rita Subhannur Rahman, Subhannur Tiastama, Sheren Afryan Tjomiadi, Cynthia Eka Fayuning Umi hanik Fetriyah, Umi hanik Virdasari, Sweetryani Wati, Eka Setya Wijaksono, M. Arief