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All Journal Jurnal Pseudocode Sinergi Jurnas Nasional Teknologi dan Sistem Informasi Journal of Information Technology and Computer Science JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal SOLMA Prosiding Seminar Nasional Teknoka JCES (Journal of Character Education Society) JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Innovation in Research of Informatics (INNOVATICS) KLIK: Kajian Ilmiah Informatika dan Komputer AMMA : Jurnal Pengabdian Masyarakat Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Abdi Reksa BACA: Jurnal Dokumentasi dan Informasi
Febriandirza, Arafat
Universitas Muhammadiyah Prof. Dr. Hamka, Indonesia
Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Nursing Social Sciences Other

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ANALISIS SENTIMEN KOMENTAR YOUTUBE TENTANG DEMAM BERDARAH DENGUE MENGGUNAKAN NAIVE BAYES Rasyidin, Andi; Febriandirza, Arafat
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 8 No 1 (2025)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v8i1.2239

Abstract

This study aims to analyze public sentiment towards Dengue Hemorrhagic Fever (DHF), a disease that is still a serious health problem in tropical countries such as Indonesia. This problem is explored through sentiment analysis of 1.058 user comments taken from four YouTube videos related to DHF, symptoms, treatment, and recovery. Text preprocessing is applied to the comments, followed by sentiment labeling using InSet Lexicon, and classification using the Multinomial Naive Bayes algorithm. To address class imbalance, the SMOTE (Synthetic Minority Oversampling Technique) method is applied. The dataset is divided into three ratios (70:30, 80:20, and 90:10) to evaluate model performance using Balanced Accuracy, AUC Score, and G-Mean. The result show that the application of SMOTE significantly improves the model’s ability to classify the minority class. The best performance was achieved with a train-test ratio of 70:30, resulting in a Balanced Accuracy of 0.7818, an AUC Score of 0.9357, and a G-Mean of 0.8396. These findings indicate that the combination of Naive Bayes and SMOTE is effective for sentiment classification of imbalanced social media data and can support public health communication strategies
Analisis Sentimen Menggunakan Metode Naive Bayes Pada Komentar Penonton YouTube Windah Basudara Berlin, Adam Putra; Febriandirza, Arafat
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.899

Abstract

The development of social media has provided users with a space to express their opinions through comments, including on the YouTube platform. One content creator who has a large fanbase and active comment section is Windah Basudara. This study aims to analyze the sentiment of viewer comments on one of Windah Basudara’s videos using the Naive Bayes algorithm. This method was chosen due to its effectiveness in text classification and sentiment analysis. The data used consists of comments from the video titled "Mencoba NAMATIN game Keju Joget", which were collected randomly and cleaned through text preprocessing steps such as case folding, tokenizing, stopword removal, and stemming. The comments were classified into two sentiment categories: positive and negative. The analysis results show that the majority of comments carry a positive sentiment, reflecting a favorable response from viewers toward the presented content. The model evaluation demonstrates satisfactory classification results. This study is expected to contribute to understanding audience perception of YouTube content and serve as a reference for further analysis on social media platforms.
Sentiment Analisis Opini Masyarakat Sistem Ganjil Genap di Twitter Menggunakan Algoritma Naive Bayes Classifier dan Algoritma K-NN Acep Setiawan; Arafat Febriandirza
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.1837

Abstract

This journal's abstract addresses sentiment analysis of public opinion in relation to the odd-even system's implementation on Twitter, utilizing the K-NN and Naïve Bayes Classifier algorithms. The odd-even system was discussed in tweets by Twitter users, which served as the source data. The tweets were categorized into three sentiment categories: positive, negative, and neutral. The analysis's findings indicate that, of the total number of tweets gathered, 391 were categorized as neutral, 50 as negative, and 59 as positive. In addition, it was found that the Naïve Bayes algorithm and the K-Nearest Neighbor algorithm both had an average accuracy rate of approximately 79.72%. This suggests that both algorithms do similarly well when it comes to classifying the sentiment of the tweets under discussion. With respect to sentiment analysis of public opinion on the Twitter platform, this conclusion clarifies the performance comparison between the Naïve Bayes and K-Nearest Neighbor algorithms.
Pemanfaatan dataset ukuran efek (effect size) untuk membangun alternatif model penelitian: Studi kasus minat konsumen membeli kendaraan listrik Putri, Rizkiya Anisyah; Yoganingrum, Ambar; Febriandirza, Arafat; Asmara, Indri Juwita; Rezaldi, Muhammad Yudhi; Tohari, Amin; Prasetyadi, Abdurrakhman; Indrawati, Ariani; Siagian, Al Hafiz Akbar Maulana
BACA: Jurnal Dokumentasi dan Informasi 2024: SPECIAL ISSUE - DATA IN BRIEF FOR REPOSITORI ILMIAH NASIONAL
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/baca.2024.7782

Abstract

This study presents survey data from primary research papers containing effect size data and the number of respondents for several variables influencing consumer interest in purchasing electric vehicles. The survey utilized the Meta-Analytic Structural Equation Modeling (MASEM) approach. Data were collected in June 2021 using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify 11 valid papers. This survey aimed to collect effect size values, such as path coefficients and standardized regression weights, from each of the eleven papers. The effect size values collected indicate the magnitude of the relationship between the variables: Attitude, Perceived Behavior Control, Subject Norm, Charging Infrastructure, Environmental Concern, Financial Benefit, External Environment, Marketing Mix, Willingness to Pay a Premium, Incentive Policy Measures, and Perceived Value, and their impact on interest in purchasing electric vehicles. The data set stored in this repository can serve as a reference for researchers and policymakers in developing models and examining the relationship between variables influencing electric vehicles adoption.
Analisis Sentimen Aplikasi Mobile Bangking Bca Pada Ulasan Pengguna di Google Play Store Menggunakan Metode Naive Bayes Tobing, Afinda Juliana; Febriandirza, Arafat
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5485

Abstract

An application is a program that is developed to meet user needs. M-banking is one application that makes it very easy for users to make transactions anytime and anywhere. The services contained in the M-banking application make users do not need to bother visiting ATMs or banks. The number of BCA Mobile application installations through Playstore reached more than 50 million users The development of technology is currently increasing rapidly, including applications in the field of banking which are now widely used for mobile transactions without the need to go to a bank or ATM Of course, this makes it very easy for users or customers to make transactions using the mobile banking application. User reviews are an important source of information for developers to find out complaints from users or customers. User comments and ratings in reviews are needed by developers to improve the quality and performance of M-Banking applications. However, this does not guarantee satisfaction for application users. To identify the sentiment of BCA Mobile application users, sentiment analysis will be carried out with the Naive Bayes algorithm. This aims to assess the accuracy of the Naive Bayes algorithm. This study aims to determine the results of sentiment through comments from application users and to determine the results of accuracy, precision and recall. Whether the results of this analysis will be greater than positive or negative values. At the same time to see how accurate it is if sentiment analysis is classified with the Naive Bayes method. The data used is obtained through web scraping from 1000 user reviews on the Google Play Store application. For after web scrapping, a preprocessing stage will be carried out, and the data is divided into 60% training data and 40% training data.
Analisis Sentimen Ulasan Pengguna Game Pubg Di Google Play Store Menggunakan Algoritma Naïve Bayes Wibowo, Fajar Iqbal; Febriandirza, Arafat
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7264

Abstract

In today's digital era, technological development is very rapid and sophisticated. The online gaming industry has also evolved. Online games are a variant of video games that are played online via the internet. When users connect with other users, users can interact and work together. Battle rolaye games, such as Player Unknown's Battlegrounds (PUBG) have become one of the most popular of the many online games available. PUBG games offer a large-scale gaming experience that creates a dynamic gaming experience. One of the advantages of the PUBG game is that it has an attractive visual design and high quality graphics so that the game feels more realistic. However, this cannot guarantee satisfaction for users. To find out user sentiment towards the PUBG game, sentiment analysis using the Naïve Bayes Algorithm is carried out which aims to find out how accurate the Naïve Bayes Algorithm is used in classification. Data is taken using web scrapping techniques as many as 1000 user reviews in the Google Play Store review column. After going through preprocessing, the data is divided into 50% training data and 50% testing data. Prediction results tend to be positive with 578 positive sentiments and 232 negative sentiments. Based on evaluation using confusion matrix, the results are 83.95% for accuracy, 88.10% for precision, and 89.62% for recall.
Performance and Effectiveness Evaluation of the National Digital Samsat as a Public E-Government Service Using the PIECES Framework Fitria, Rahma; Syakhila, Amanda; Yulisda, Desvina; Hussain, Azham; Febriandirza, Arafat
Innovation in Research of Informatics (Innovatics) Vol 7, No 2 (2025): September 2025
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v7i2.15672

Abstract

The SIGNAL application is a digital service from the Korlantas Polri that makes it easier for people to take care of STNK validation online. However, some users still experience problems such as the verification process that is not always successful, slow delivery of physical documents, less rapid customer service response, and slow verification or login process. Therefore, this study aims to evaluate the performance of the SIGNAL application with the PIECES framework approach which includes six aspects: Performance, Information, Economic, Control, Efficiency, and Service. The data collection method was carried out through distributing questionnaires to 300 respondents who use the SIGNAL application. In addition, technical performance testing was also carried out using Apptim tools to measure application technical metrics. The results showed that overall, users were satisfied with the system based on the six aspects of PIECES with an average score of 3.9 on a scale of 5.76% of respondents stated that they were satisfied to very satisfied, 15% were undecided/neutral, and 9% were dissatisfied. This finding indicates that the majority of users consider this application to be quite effective and worth using. Performance testing using Apptim resulted in an average response time of 2.4 seconds, CPU usage of 18%, memory usage of 170MB, and no errors (error rate 0%), indicating that the application is quite stable and runs well on user devices. It is hoped that this research can be the basis for further development of the SIGNAL application, especially in improving service aspects and overall system efficiency.
Aksesibilitas User Experience Web Conten Penyandang Disabilitas Kognitif dengan Metode Double Diamond Garno, Garno; Sarwosri, Sarwosri; Febriandirza, Arafat
Jurnal Nasional Teknologi dan Sistem Informasi Vol 11 No 3 (2025): Desember 2025
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v11i3.2025.282-293

Abstract

Aksesibilitas digital merupakan aspek krusial dalam pengembangan teknologi yang inklusif, terutama bagi penyandang disabilitas kognitif. Namun, masih banyak platform digital yang belum mempertimbangkan kebutuhan khusus kelompok ini, yang menyebabkan kesulitan dalam mengakses informasi dan menggunakan layanan secara mandiri. Penelitian ini bertujuan untuk mengidentifikasi tantangan yang dialami oleh penyandang disabilitas kognitif dalam menggunakan platform digital serta merancang user interface yang lebih ramah dan inklusif. Metode penelitian yang digunakan adalah double diamond, yang terdiri dari empat tahap: discover, define, develop, dan deliver. Sebanyak 15 partisipan penyandang disabilitas kognitif terlibat dalam proses pengumpulan data melalui wawancara dan observasi. Data dianalisis dan diolah ke dalam bentuk empathy map, user needs & pain points, hingga menghasilkan desain interface dalam bentuk low-fidelity wireframe dan User interface final visual. Desain ini diuji secara visual kepada partisipan untuk mendapatkan tanggapan awal dan validasi kelayakan. Hasil penelitian menunjukkan bahwa tantangan utama meliputi kesulitan membaca teks panjang, bingung saat tidak ada petunjuk langkah, sulit membedakan elemen visual, serta kebingungan akibat absennya pesan kesalahan. Desain akhir mengadopsi prinsip-prinsip Web Content Accessibility Guidelines (WCAG) dan praktik User experience (UX) inklusif yang berhasil menjawab kebutuhan tersebut. Partisipan memberikan respon positif terhadap tampilan yang lebih sederhana, visual, dan informatif, yang mampu meningkatkan kemandirian mereka dalam menggunakan aplikasi. Penelitian ini memberikan kontribusi praktis dalam pengembangan desain digital inklusif serta menegaskan pentingnya keterlibatan pengguna disabilitas dalam proses desain berbasis empati.
Co-Authors Abdiel Alpriyan Gempa Alamsyah Sahuri Abdurrakhman Prasetyadi, Abdurrakhman Acep Setiawan Ade Maya Saraswati Ahmad Afif Supianto Alim, Endy Sjaiful Ambar Yoganingrum Amin Tohari Anggraeni, Widia Azpiranda, Novira Berlin, Adam Putra E Erizal Elvianasti, Mega Endy Syaiful Alim Faldy Irwiensyah Faldy Irwiensyah, Faldy Firjatullah, Farhan Firman Noor Hasan garno, Garno Herdi Tri Nanda Hibatullah Faisal Hussain, Azham Indrawati, Ariani Indri Juwita Asmara Indriyanti, Prastika Irdalisa Kartikawati, Eka Maesaroh Maesaroh Muhamad Wahyu Sanjaya Muhammad Efrizal Febriyan Muhammad Hafizd Ibnu Hajar Muhammad Solehuddin Al-Khawarizmi Muhammad Yudhi Rezaldi, Muhammad Yudhi Nanang Yudi Setiawan Prastiyo, Isnan Wisnu Putri, Rizkiya Anisyah Rahady Puji Alfiansyah Rahma Fitria, Rahma Rahmi Imanda rasyidin, andi Sarwosri Sarwosri SIAGIAN, AL HAFIZ AKBAR MAULANA Suryawati, Endang Suwoyo, Heru Syakhila, Amanda Tobing, Afinda Juliana Wibowo, Fajar Iqbal Yulisda, Desvina Yuwana, R. Sandra