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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 Syntax Literate: Jurnal Ilmiah Indonesia 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 Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Nursing Social Sciences Other

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Perancangan Prototipe Sistem Informasi Pariwisata Berbasis Web di Kota Malang Muhammad Efrizal Febriyan; Herdi Tri Nanda; Arafat Febriandirza
Prosiding Seminar Nasional Teknoka Vol 8 (2023): Proceeding of TEKNOKA National Seminar - 8
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

One of the best tourism destinations in Indonesia is Malang. This city has a variety of uniqueness that can attract tourists to visit it. With the development of technology in this era, many make things easier, one of which is conveying information. This study aims to design a prototype of a web-based tourism information system in Malang City so that later tourists can more easily obtain information about this city. The method used is a descriptive method which will present and analyze facts systematically so that it will be easy to draw conclusions. Data collection was carried out by distributing questionnaires. In designing this prototype, Data Flow Diagrams, Flowcharts, Database Designs, and Output Designs will be designed. The results of this information system prototype will include various information about tourism in the city of Malang.
The use of Fuzzy Logic Controller and Artificial Bee Colony for optimizing adaptive SVSF in robot localization algorithm Suwoyo, Heru; Hajar, Muhammad Hafizd Ibnu; Indriyanti, Prastika; Febriandirza, Arafat
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.003

Abstract

The objective of solving feature-based localization problems is to estimate the path of the robot referring to a given map. Thus, it is not surprising that robust estimators such as Smooth Variable Structure Filter (SVSF) are often used to handle this problem. Basically, its use is highly dependent on an accurate system model and known statistical noise. Where neither of these are available by definition. Therefore, the conventional way is not recommended and the use of an adaptive filter approach can be involved. Based on this and although only partially, Innovation Adaptive Estimation (IAE) has been considered to have a positive influence on improving the performance of the estimator. But not infrequently the solutions offered by this approach also lead to divergences due to unmapped dynamic conditions. Moreover, in this proposal, IAE is enhanced by applying Artificial Bee Colony-Tuned Fuzzy Logic. The hope is that there is quality control for the process noise covariance Q and R measurements by updating them based on the output of this ABC-Tuned FLC.
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 : STMIK 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.
Analisis Perbandingan Prediksi Tingkat Kemiskinan Menggunakan Metode XGBoost dan Random Forest Regression Prastiyo, Isnan Wisnu; Febriandirza, Arafat
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7892

Abstract

This research aims to compare the performance of two prediction algorithms, XGBoost Regression and Random Forest Regression, in predicting poverty levels in the DKI Jakarta area. For this research, researchers obtained data from the DKI Jakarta Central Statistics Agency (BPS) covering the period 2010 to 2023. The testing method used involved measuring Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) to assess the accuracy of predictions from the two algorithms. . The findings show that the Random Forest Regression algorithm generally produces more accurate predictions compared to the XGBoost Regression algorithm as seen from the test results on (MSE) and (MAPE) for most of the areas analyzed. As with MAPE for the West Jakarta area, the test results for XGBoost Regression were 1.43, while Random Forest Regression produced 1.42, so Random Forest Regression is better than XGBosst Regression. However, in the Seribu Islands, the MAPE for XGBoost is better with a value of 4.49 than for Random Forest Regression which has a value of 4.56. Then MSE Random Forest is better than XGBoost in this prediction test. For example, in the Central Jakarta area with a value of 0.02 for XGBoost Regression, while Random Forest Regression has a smaller test result with a value of 0.01.
Sentiment Anlysis On Customer Reviews Using Support Vector Machine and Usability Scoring Using System Usability Scale Azpiranda, Novira; Supianto, Ahmad Afif; Setiawan, Nanang Yudi; Suryawati, Endang; Yuwana, R. Sandra; Febriandirza, Arafat
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202163330

Abstract

Al-Ghiff Steak is a restaurant located in Cirebon City that offers quality steaks at affordable prices. For maintaining a competitive Al-Ghiff Steak advantage and reputation, it is important to build a good relationship with customers and have a business strategy that considers customer opinions. However, in its implementation, Al-Ghiff Steak has difficulty when collecting and processing customer review data manually. Therefore, it is necessary to conduct sentiment analysis by utilizing Google Reviews to determine customer perspectives regarding Al-Ghiff Steak products and services. This analysis was conducted on 968 Google Review reviews from 2016 to 2020 using the Support Vector Machine (SVM) and Term Frequency-Inverse Document Frequency (TF-IDF) methods. Classification testing is done with a confusion matrix against four parameters: accuracy, precision, recall, and f1-score. SVM with TF-IDF gets accuracy value 83%, precision 64%, recall 60% and f1-score 59%. The sentiment classification result is then visualized in the form of a dashboard. We utilize the System Usability Scale (SUS) for usability testing, which produces a value of 77.5. This result achieve the Acceptable category and an Excellent rating.
PEMBERDAYAAN PELAKU USAHA PERIKANAN BERBASIS TEKNOLOGI DIGITAL Febriandirza, Arafat; Maesaroh, Maesaroh; Kartikawati, Eka; Irdalisa, Irdalisa; Elvianasti, Mega; Anggraeni, Widia
JCES (Journal of Character Education Society) Vol 5, No 4 (2022): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jces.v5i4.10768

Abstract

Abstrak: Kelompok usaha pindang bandeng di Kabupaten Bekasi memulai usaha dalam bidang perikanan sekitar 20 tahun. Selama perjalanan usahanya, produk pindang ikan bandeng diproduksi dan distribusikan secara konvensional. Sumber daya manusia merupakan salah satu keterbatasan dalam pengembangan usaha pindang bandeng. Kegiatan ini dilaksanakan untuk memberikan pemahaman dan keterampilan bagi pelaku usaha pindang bandeng terkait pemanfaatan teknologi digigal untu mendukung aktivitas usaha. Metode yang digunakan dalam kegiatan yaitu berupa seminar pemberian materi dan workshop keterampilan teknologi digital. Hasil evaluasi kegiatan menunjukkan bahwa terdapat perubahan pengetahuan dalam proses pengemasan produk dan pemasaran menggunakan digital marketing. Seluruh peserta kegiatan menyatakan bahwa pendampingan pelaku usaha perikanan ini bermanfaat untuk mereka. Melalui kegiatan ini para peserta memeroleh pengetahuan, dan keterampilan tentang proses produksi dan pemasaran usaha pindang menggunakan teknologi digital. Diperlukannya tindak lanjut dan waktu pendampingan yang lebih panjang dalam upaya membuat pelaku usaha lebih mudah beradaptasi dan mandiri.Abstract:  Pindang bandeng business group in Bekasi Regency started a business in the fishery sector for about 20 years. During the course of its business, milkfish pindang products were produced and distributed conventionally. Human resources are one of the limitations in the development of milkfish pindang business. This activity is carried out to provide understanding and skills for milkfish pindang business actors regarding the use of digital technology to support business activities. The method used in the activity is in the form of seminars on providing material and workshops on digital technology skills. The results of the activity evaluation show that there is a change in knowledge in the process of product packaging and marketing using digital marketing. All participants of the activity stated that the assistance of fishery business actors was beneficial for them. Through this activity, participants gain knowledge and skills about the production process and marketing of pindang businesses using digital technology. The need for follow-up and longer mentoring time in an effort to make business actors more adaptable and independent.
Rancangan Sistem Informasi Perpustakaan Ruang Publik Terpadu Ramah Anak Berbasis Web Firjatullah, Farhan; Febriandirza, Arafat
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.7089

Abstract

Child Friendly Integrated Public Space (RPTRA), is a facility built by the DKI provincial government to facilitate its citizens as well as a place that is friendly to children as well as a means of playground, one of the facilities provided is a library but the library still uses manual or conventional methods in the process so that many stages are still inefficient, therefore the implementation of this library system is a good suggestion for the creation of an efficient process in the library. This system was created using PHP and MySql with the waterfall method as a guideline, the use of this method is expected to simplify and speed up the design process on the Kalimati West Jakarta RPTRA library information system. The conclusion obtained from this research is the design of a web-based library system that is easy to use in terms of interface and usage experience and to build a library system that makes it easy to collect library inventory data in the Child Friendly Integrated Public Space (RPTRA).
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.
Co-Authors Abdiel Alpriyan Gempa Alamsyah Sahuri Abdurrakhman Prasetyadi, Abdurrakhman Acep Setiawan Ade Maya Saraswati Ahmad Afif Supianto Ambar Yoganingrum Amin Tohari Anggraeni, Widia Azpiranda, Novira Berlin, Adam Putra E Erizal Eleonora Agustine Elvianasti, Mega Endy Sjaiful Alim Endy Syaiful Alim Esa Prakasa, Esa Faldy Irwiensyah Faldy Irwiensyah 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 Novia Wulandari, Novia Prastika Indriyanti 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