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All Journal Jurnal Edukasi Universitas Jember Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Ilmiah Universitas Batanghari Jambi Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Bisma: Jurnal Bisnis dan Manajemen Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL AKUNTANSI KEUANGAN DAN MANAJEMEN Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Soft Computing Exploration Studi Ilmu Manajemen dan Organisasi Jurnal Abdimas Ekonomi dan Bisnis Transekonomika : Akuntansi, Bisnis dan Keuangan Jurnal Relevansi : Ekonomi, Manajemen dan Bisnis Perwira Journal of Science and Engineering (PJSE) Reviu Akuntansi, Manajemen, dan Bisnis PENA ABDIMAS : Jurnal Pengabdian Masyarakat Journal of Advances in Information Systems and Technology Indonesian Journal of Informatic Research and Software Engineering Jurnal Pemberdayaan Ekonomi eProceedings of Management Journal of Student Research Exploration Journal of Information System Exploration and Research Recursive Journal of Informatics IJEB JPM JER Jurnal Akuntansi dan Governance Andalas Media Penelitian dan Pengembangan Kesehatan Jurnal Ekonomi, Manajemen, Akuntansi INOVTEK Polbeng - Seri Informatika Jurnal Abdi Negeri Recursive Journal of Informatics
Budi Prasetiyo, Budi
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Sentiment Analysis on Twitter Social Media Regarding Covid-19 Vaccination with Naive Bayes Classifier (NBC) and Bidirectional Encoder Representations from Transformers (BERT) Saputra, Angga Riski Dwi; Prasetiyo, Budi
Recursive Journal of Informatics Vol. 2 No. 2 (2024): September 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/7h63ma50

Abstract

Abstract. The Covid-19 vaccine is an important tool to stop the Covid-19 pandemic, however, there are pros and cons from the public regarding this Covid-19 vaccine. Purpose: These responses were conveyed by the public in many ways, one of which is through social media such as Twitter. Responses given by the public regarding the Covid-19 vaccination can be analyzed and categorized into responses with positive, neutral or negative sentiments. Methods: In this study, sentiment analysis was carried out regarding Covid-19 vaccination originating from Twitter using the Naïve Bayes Classifier (NBC) and Bidirectional Encoder Representations from Transformers (BERT) algorithms. The data used in this study is public tweet data regarding the Covid-19 vaccination with a total of 29,447 tweet data in English. Result: Sentiment analysis begins with data preprocessing on the dataset used for data normalization and data cleaning before classification. Then word vectorization was performed with TF-IDF and data classification was performed using the Naïve Bayes Classifier (NBC) and Bidirectional Encoder Representations from Transformers (BERT) algorithms. From the classification results, an accuracy value of 73% was obtained for the Naïve Bayes Classifier (NBC) algorithm and 83% for the Bidirectional Encoder Representations from Transformers (BERT) algorithm. Novelty: A direct comparison between classical models such as NBC and modern deep learning models such as BERT offers new insights into the advantages and disadvantages of both approaches in processing Twitter data. Additionally, this study proposes temporal sentiment analysis, which allows evaluating changes in public sentiment regarding vaccination over time. Another innovation is the implementation of a hybrid approach to data cleansing that combines traditional methods with the natural language processing capabilities of BERT, which more effectively addresses typical Twitter data issues such as slang and spelling errors. Finally, this research also expands sentiment classification to be multi-label, identifying more specific sentiment categories such as trust, fear, or doubt, which provides a deeper understanding of public opinion.
Hyperparameter Tuning of Long Short-Term Memory Model for Clickbait Classification in News Headlines Satriawan, Grace Yudha; Prasetiyo, Budi
Recursive Journal of Informatics Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/19mypm04

Abstract

Abstract. The information available on the internet nowadays is diverse and moves very quickly. Information is becoming easier to obtain by the general public with the numerous online media outlets, including news portals that provide up-to-date information insights. Various news portals earn revenue from advertising using pay-per-click methods that encourage article writers to use clickbait techniques to attract visitors. However, the negative effects of clickbait include a decrease in journalism quality and the spread of hoaxes. This problem can be prevented by using text classification to classify clickbait in news titles. One method that can be used for text classification is a neural network. Artificial neural networks use algorithms that can independently adjust input coefficient weights. This makes this algorithm highly effective for modeling non-linear statistical data. The artificial neural network algorithm, especially the Long Short-Term Memory (LSTM), has been widely used in various natural language processing fields with satisfying results, including text classification. To improve the performance of the neural network model, adjustments can be made to the model's hyperparameters. Hyperparameters are parameters that cannot be obtained through data and must be defined before the training process. In this research, the Long Short-Term Memory (LSTM) model was used in clickbait classification in news titles. Sixteen neural network models were trained with different hyperparameter configurations for each model. Hyperparameter tuning was carried out using the random search algorithm. The dataset used was the CLICK-ID dataset published by William & Sari, 2020[1], with a total of 15,000 annotated data. The research results show that the developed LSTM model has a validation accuracy of 0.8030, higher than William & Sari's research, and a validation loss of 0.4876. Using this model, researchers were able to classify clickbait in news titles with fairly good accuracy. Purpose: The study was to develop and evaluate a LSTM model with hyperparameter tuning for clickbait classification on news headlines. The thesis also aims to compare the performance of simple LSTM and bidirectional LSTM for this task. Methods: This study uses CLICK-ID dataset and applies different text preprocessing techniques. The dataset later was used to build and train 16 LSTM models with different hyperparameters and evaluates them using validation accuracy and loss. This study uses random search for hyperparameter tuning. Result: The results of the study show that the best model for clickbait classification on news headlines is a bidirectional LSTM model with one layer, 64 units, 0.2 dropout rate, and 0.001 learning rate. This model achieves a validation accuracy of 0.8030 and a validation loss of 0.4876. The results also show that hyperparameter tuning using random search can improve the performance of the LSTM models by avoiding zero probabilities and finding the optimal values for the hyperparameters. Novelty: This study compares and analyzes the different preprocessing methods on text and the different configurations of the models to find the best model for clickbait classification on news headlines. The study also uses hyperparameter tuning to tune the model into the best model and finding the optimal values for the hyperparameters.
Sentiment Analysist of the TPKS Law on Twitter Using InSet Lexicon with Multinomial Naïve Bayes and Support Vector Machine Based on Soft Voting Aisy, Salsabila Rahadatul; Prasetiyo, Budi
Recursive Journal of Informatics Vol. 1 No. 2 (2023): September 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/zbxqcc36

Abstract

Abstract. The Indonesian Sexual Violence Law (TPKS Law) is a law that regulates forms of sexual violence. The TPKS Law reaped pros and cons in the drafting process and was officially ratified on April 12th, 2022. However, after being ratified, pros and cons can still be found and supervision is needed over the implementation of the law. Purpose: This study was conducted to identify the application and accuracy of soft voting on multinomial naïve Bayes and support vector machine algorithm, also to find out public opinion on the TPKS Law as a support tool in evaluating the law. Methods/Study design/approach: The method used is InSet lexicon for labeling with the soft voting classification method on the multinomial naive Bayes and support vector machine algorithm. Result/Findings: The accuracy obtained by applying 10 k-fold cross validation in soft voting is 84.31%, which uses a weight of 1:3 for multinomial naive Bayes and support vector machines. Soft voting obtains better accuracy than its standalone predictor, and also works well for sentiment analysis of the TPKS Law. Novelty/Originality/Value: This study using two combined lexicons (Colloquial Indonesian lexicon and the InaNLP formalization dictionary) in normalization process and using InSet lexicon as automatic labeling for sentiment analysis on TPKS Law.
Optimalisasi Podcast BISIK dalam Memperkuat Citra dan Preferensi Masyarakat Jawa Barat terhadap RSUD Welas Asih Marshanda, Ghea; Prasetiyo, Budi
Jurnal Relevansi : Ekonomi, Manajemen dan Bisnis Vol 9 No 2 (2025): Jurnal Relevansi : Ekonomi, Manajemen dan Bisnis
Publisher : LPPM STIE KRAKATAU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61401/relevansi.v9i2.361

Abstract

The transformation of digital media has driven a shift in communication strategies within the healthcare service sector, including public hospitals that continue to face challenges in shaping public preferences. RSUD Welas Asih, as one of the public hospitals in West Java, has adopted digital promotion through the live streaming podcast program BISIK (Bincang Sehat Asik) as a medium for health education and the dissemination of health-related information to the public. This study aims to examine the effect of digital promotion through the BISIK program on public preferences toward RSUD Welas Asih, as well as to examine the role of brand image as an intervening variable. This research employs a quantitative approach with a causal research design. Data were collected through the distribution of questionnaires to members of the public who had been exposed to the BISIK program. Data analysis was conducted using the Partial Least Squares–Structural Equation Modeling (PLS-SEM) method to test both direct and indirect relationships among the research variables. The results indicate that digital promotion through the BISIK live streaming podcast has a positive and significant effect on public preferences toward RSUD Welas Asih. Furthermore, brand image is proven to function as a mediating variable that strengthens the influence of digital promotion on public preferences. These findings suggest that digital promotion not only exerts a direct impact but also contributes to the formation of a positive image of public hospitals. This study concludes that well-planned and consistently managed digital promotion can serve as an effective strategy for enhancing public preferences and trust in public healthcare services.
PENGARUH KUALITAS PELAYANAN ROOM SERVICE DAN FASILITAS HOTEL TERHADAP KEPUASAN PELANGGAN DI V HOTEL & RESIDENCE BANDUNG Prasetiyo, Budi; Ristiawati, Monika
TRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN Vol. 2 No. 5 (2022): September 2022
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/transekonomika.v2i5.233

Abstract

Hospitality is an aspect of a very large field of business and includes many access fields of work. Therefore, the hotel does not only function to provide services, but also emphasizes the service aspect. Aspects of supporting hotel services and facilities are important points in creating customer satisfaction in a hotel business, for example the completeness of hotel facilities and the friendliness of room service will be of added value in the eyes of customers. This study aims to determine the effect of the quality of room service and hotel facilities on customer satisfaction at V Hotel & Residence Bandung. This study uses a descriptive research method with a quantitative approach. In this study, the variables used are Room Service Quality (X1), Hotel Facilities (X2) and Customer Satisfaction (Y). This research carried out in V Hotel & Residence Bandung, with a total of 100 respondents. Based on the results of the research above, it can be concluded that, the quality of room service (X1) and hotel facilities (X2) partially has a significant effect on customer satisfaction (Y). This indicates that the quality of room service and hotel facilities can affect customer satisfaction V Hotel & Residence Bandung.
PENGARUH KUALITAS PRODUK DAN PERSEPSI HARGA TERHADAP KEPUTUSAN PEMBELIAN SEPEDA MOTOR HONDA BEAT PADA DEALER CV. SUPRA JAYA MOTOR CIANJUR Nardo, Leo; Prasetiyo, Budi
TRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN Vol. 2 No. 5 (2022): September 2022
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/transekonomika.v2i5.234

Abstract

Motorcycles are a favorite means of transportation that are chosen by the community, especially because the current level of congestion is very high, so that one alternative is to make it easier and smoother to reach destinations in the city. The growth of motorcycle consumers that continues to fluctuate resulting in many new entrants in various categories. This study aims to obtain data and information regarding product quality and price perceptions, and to determine the extent of their influence on purchasing decisions for Honda BEAT Motorcycles in Cianjur. This study uses quantitative methods and uses the Non-Probability Sampling technique with an incidental sampling technique approach of 72 people. The research findings found that the variable quality of the product on the Honda BEAT motorcycle can be seen that the score is 305.8. Variable price perception on the Honda BEAT motorcycle can be seen that the results are very good because it reaches a score of 304.25. Variable purchasing decisions for Honda BEAT motorcycles at CV. Supra Jaya Motor Cianjur Dealers can be seen the results are good because they reach a score of 296.4.
PENGARUH LOKASI DAN PROMOSI TERHADAP KEPUTUSAN PEMBELIAN RUMAH DI PD RAHARJA CIMAHI Sulastri, Ai; Prasetiyo, Budi
TRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN Vol. 2 No. 6 (2022): November 2022
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/transekonomika.v2i6.301

Abstract

This research is a quantitative study on PD Raharja Cimahi that seeks to analyze how location and promotion influence judgments regarding the purchase of a home, as well as the extent to which these factors have an impact. The sample for this investigation consisted of 68 participants who were selected through the process of probability sampling using the technique of multiple linear regression analysis. Based on the study findings that the value of R2 is 0.535, which is equivalent to 53.5%, suggests that the findings of this study reveal the influence of location on consumer purchasing decisions. A simultaneous influence on customer purchasing decisions of 0.463%, or 46.3%, is exerted through promotion. The results of the tests on the hypotheses suggest that the elements of location and promotion have a positive impact on the decisions on which products to purchase. The value of R^2, which is 0.535%, reflects this point of view accurately. With a value of R = 20.535, it is possible to deduce that the independent elements in this investigation, namely location and promotion, have an influence on consumer spending decisions that is equivalent to 53.5%. The factors of location and promotion have a large influence on purchase decisions, with an effect size of 53.5%. Meanwhile, the remaining influence comes from factors that were not investigated in this study.
PENGARUH KUALITAS PELAYANAN DAN FASILITAS TERHADAP KEPUASAN PASIEN RAWAT INAP DI RUMAH SAKIT UMUM KASIH BUNDA KOTA CIMAHI Saparina, Iska Ayu; Prasetiyo, Budi
TRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN Vol. 3 No. 1 (2023): January 2023
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/transekonomika.v3i1.367

Abstract

This research was conducted on inpatients at Kasih Bunda Cimahi General Hospital. This study aims to determine how much influence quality and facilities had on inpatient satisfaction either partially or simultaneously in inpatients at Kasih Bunda Cimahi General Hospital. This study uses a descriptive and associative methodology with a quantitative approach. Inpatients in the Arjuna, Nakula, Shinta, and Bima rooms became the unit of analysis for this study. The sample for this study consisted of ninety respondents. By using stratified random sampling, this study used a systematic random sampling method. In addition to verifying the validity and reliability of research tools, the analytical approach uses multiple linear regression analysis. According to research findings, service quality has a partial effect of 12.01% on inpatient satisfaction, while facilities have a partial effect of 19.01%. Nevertheless, the total effect is only 31%. To further increase customer satisfaction, the hospital will provide outreach to all divisions related to hospital services.
Co-Authors Aditya Wardhana Afrizal Rizqi Pranata, Afrizal Rizqi Ahmad Roziqin, Ahmad Aisy, Salsabila Rahadatul Aji Purwinarko, Aji Alamsyah - Amidi Amidi, Amidi Anggraini, Tasya Fitria Anggyi Trisnawan Putra Ardila Rahma, Rana Aziz, Alif Abdul Azura, Amberia Narfi Bachtiar, Muhammad Irgi Bambang Widjajanta, Bambang Bayuaji, Hibatullah Zamzam Tegar Beta Noranita Biyantoro, Arell Saverro D.W, Made Bagus Paramartha Deske W. Mandagi Didimus Tanah Boleng Dinova, Dony Benaya Endang Sugiharti, Endang Fachrezi, Farhan Rifa Fadhilah, Muhammad Syafiq Fadlil, Affan Fajriati, Nafa Fata, Muhamad Nasrul Fata, Muhamad Nasrul Ferninda, Varin Fikri Mohamad Rizaldi Fitria, Yunita Fitriana, Jevita Dwi Hakim, Ade Anggian Hakim, M Faris Al Hakim, M. Faris Al Hani Fitria Rahmani Ilham Maulana Jhonatan, Edward Julianto, Richy Jumanto Jumanto , Jumanto Jumanto Jumanto, Jumanto Jumanto Unjung KA, Cecep Bagus Suryadinata Korina, Nanda Putri Leo nardo Lestari , Apri Dwi Lestari, Apri Dwi Lestari, Fitri Duwi Lintang, Irendra M. Faris Al Hakim Makrina Tindangen Marshanda, Ghea Maulidia Rahmah Hidayah, Maulidia Rahmah Much Aziz Muslim Muhammad Sugiharto Mukhlisin, Ahmad Munahefi, Detalia Noriza Mustaqim, Amirul Muzayanah, Rini Naufal Zuhdi, Hamzah Ndruru, Toni Krisman Nelly, Fredy Kusuma Nendya, Bima Nicko, Robertus Nikmah, Tiara Lailatul Nina Fitriani, Nina Ningsih, Maylinna Rahayu Nisa, Intan Khairun Niswah Baroroh Partini, Emilia Paundra, Fajar Pertiwi, Dwika Ananda Agustina Pradana, Fadli Dony PRASETYO, ERWIN Pratama, Muhammad Hasbi Puspo Dewi Dirgantari Rachmawati, Eka Yuni Rachmawati, Eka Yuni Rahmat Gernowo Ramadhian, M. Arief Rahman Ratih Hurriyati Riesnandar, Edi Ristiawati, Monika Riza Arifudin Robianty, Nenden Sondari Rofik Rofik, Rofik S.Pd. M Kes I Ketut Sudiana . Sadid, Moh Naufal Salsabila, Malika Putri Saparina, Iska Ayu Saputra, Angga Riski Dwi Satriawan, Grace Yudha Satrio Ardiansyah, Adi Seivany, Ravenia Septian, M Rivaldi Ali Subhan Subhan Sulastri, Ai Syaharani, Reisya Triyadi, Indra Ulhaq, Moch Daffa Dhiya Vember, Hilda Wahyu, Aufa Azfa Walean, Ronny H. Yahya Nur Ifriza Yosza Dasril Yulia Nur Hasanah