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All Journal Semesta Teknika Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL ILMIAH INFORMATIKA JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika Kaputama (JIK) Jurnal Mantik JIKA (Jurnal Informatika) Jurnal Abdimas Komunikasi dan Bahasa J-Intech (Journal of Information and Technology) Jurnal Ilmu Komputer JURNAL KESEHATAN, SAINS, DAN TEKNOLOGI (JAKASAKTI) Jurnal Pengabdian Masyarakat Bangsa Jurnal Manuhara: Pusat Penelitian Ilmu Manajemen Dan Bisnis
Antonius Yadi Kuntoro
Universitas Bina Sarana Informatika
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ANALISA SENTIMEN VAKSINASI COVID-19 DENGAN METODE SUPPORT VECTOR MACHINE DAN NAÏVE BAYES BERBASIS TEKNIK SMOTE Riza Fahlapi; Hermanto Hermanto; Taufik Asra; Antonius Yadi Kuntoro; Ridatu Ocanitra; Lasman Effendi; Ferry Syukmana
Jurnal Informatika Kaputama (JIK) Vol 6 No 1 (2022): Volume 6, Nomor 1, Januari 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v6i1.136

Abstract

Keadaan dan tantangan pandemi pada awal tahun 2021 dengan telah ditemukannya vaksin atas virus Covid-19 tentunya diperlukan percepatan dalam pemberian vaksin kepada seluruh umat manusia di seluruh dunia. Di Indonesia, Pemerintah menggalakan program vaksinasi masal kepada seluruh Warga Negara Indonesia dengan melakukan percepatan vaksinasi di seluruh wilayah Indonesia sampai dengan saat ini. Berdasarkan hal tersebut diatas dipandang perlu melakukan analisa sentimen. Media sosial twitter dipilih sebagai salah satu sarana dalam analisas sentiman ini. Terdapat 1013 komentar positif dan negatif para pengguna twitter dengan kata kunci “vaksin” yang didapatkan untuk diproses terkait tanggapan masyarakat atas pelaksanaan vaksinasi masal yang dilaksanakan di Indonesia. Dengan menggunakan Algoritma Support Vector Machine (SVM) dan Naïve Bayes berbasis SMOTE dilakukan perbandingan pengujian atas komentar positif dan negatif tersebut. Dari proses pengujian tersebut didapatkan hasil akurasi dari algoritma SVM menggunakan teknik SMOTE didapatkan nilai akurasi =70.51% dan nilai AUC =0.827, sedangkan proses pengujian menggunakan algoritma Naïve Bayes dengan teknik SMOTE didapatkan nilai akurasi = 64.36% dan nilai AUC = 0.423. dari proses diatas, penggunaan Support Vector Machine berbasis teknik SMOTE memiliki akurasi yang lebih tinggi sehingga dapat digunakan untuk memberikan solusi terhadap analisis sentimen vaksinasi Covid-19.
SENTIMENT ANALYSIS ON GOJEK AND GRAB USER REVIEWS USING SVM ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION Hermanto, Hermanto; Kuntoro, Antonius Yadi; Asra, Taufik; Nurajijah, Nurajijah; Effendi, Lasman; Ocanitra, Ridatu
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1068.985 KB) | DOI: 10.33480/pilar.v16i1.1304

Abstract

Users of the Gojek and Grab application can provide reviews or comments about the application on Google Play. Reviews in the form of giving opinions about their satisfaction or dissatisfaction with the services provided. So with the many opinions provided, making people selective in choosing an online motorcycle taxi service provider. The application with the best review will be chosen by the community. In previous studies regarding the classification of online ojek service review using the Naïve Bayes algorithm, C.45 and Random Forest produced an unsatisfactory accuracy of 69.18% at the highest value. This study aims to determine the extent of the analysis of Gojek and Grab application user reviews based on user comments by classifying negative and positive reviews with a higher level of accuracy than previous studies so that applications with the best reviews can be known for public consideration in using the application's services. The method used for data review classification is using the Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO). The test results on the Grab application review get the highest accuracy results in the amount of 73.09% with AUC value = 0.804, while for the test results on the application review Gojek get an accuracy value of 65.59% and AUC value = 0.680
Pelatihan Artificial Intelligence Dalam Membuat Power Point Pada Remaja Masjid Baitul Halim Hasanah, Riyan Latifahul; Kuntoro, Antonius Yadi; Saelan, M. Rangga Ramadhan; Anasanti, Mila Desi
Jurnal Pengabdian Masyarakat Bangsa Vol. 2 No. 8 (2024): Oktober
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v2i8.1475

Abstract

Pengembangan ilmu pengetahuan dan teknologi (IPTEK) memberikan peran dalam meningkatkan kesejahteraan dan perekonomian masyarakat. Salah satu bidang yang dapat merasakan kehadiran teknologi yaitu bidang pendidikan organisasi kemasyarakatan, termasuk pada organisasi Remaja Masjid Baitul Halim Jakarta Selatan. Untuk mengelola data organisasi diperlukan kemampuan administrasi yang baik, sehingga data bisa tertata dengan baik dan keberlanjutan bagi kegiatan organisasi. Dalam rangka menunaikan salah satu Tri Dharma Perguruan Tinggi, maka Universitas Nusa Mandiri melaksanakan Pengabdian Masyarakat berupa Pelatihan Artificial Intelligence Dalam Membuat Power Point untuk memudahkan proses pemaparan program kerja dan juga sebagai media promosi dan publikasi organisasi. Metode pengabdian masyarakat terdiri dari 4 tahapan, yaitu persiapan, pelaksanaan, evaluasi dan pelaporan. Adapun peserta kegiatan ini adalah para anggota Remaja Masjid Baitul Halim yang mengikuti pelatihan komputer secara offline. Dengan pelatihan ini, peserta merasakan manfaat kehadiran teknologi dimana dapat membantu kegiatan sosial, pendidikan dan keagamaan bagi organisasi. Pemanfaatan AI dalam pembuatan Power Point dapat digunakan untuk membuat presentasi yang menarik dalam slide yang bisa dimodifikasi sesuai kebutuhan.
Implementasi Sistem Aplikasi Agent Anywhere Pada PT. Bank Syariah Indonesia Terintegrasi Whatsapp Menggunakan Metode Agile Scrum Sugiarto, Hady; Kuntoro, Antonius Yadi
Jurnal Ilmu Komputer (JUIK) Vol 4, No 3 (2024): October 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i3.3346

Abstract

In recent years, information and communication systems have experienced rapid growth. The impact is not only felt by those working in technology, but also affects the lifestyles of people from all walks of life. The emergence of online marketing is one of the impacts of these technological advances. As time goes by, many companies are forced to lay off their employees for reasons of age, especially those who are married and have children, even though basically these employees are still very productive in their fields. Agent Anywhere is a strategy of using online platforms to communicate messages about business image, as well as promote products or services to potential consumers. The online platforms used are very diverse, ranging from websites, search engine optimization (SEO) techniques, pay per click (PPC) advertising, marketing via email (email marketing), to social networks, in designing applications as promotional and information media. Online Marketing consists of two pages, the admin page and the Agent page. Agents can access and log in first. In this application, agents can send promotional messages directly by creating a campaign/activity first and preparing Leads data as a Whatsapp telephone number database. This application is designed using the programming languages PHP, CodeLignter, XAMPP, Node.js, and MySql as the database.
Perbandingan Algoritma Klasifikasi Analisis Sentimen Pengguna Aplikasi Getcontact Dalam Pencegahan Penipuan Online Hermanto, Hermanto; Fahlapi, Riza; Kuntoro, Antonius Yadi; Asra, Taufik
J-INTECH (Journal of Information and Technology) Vol 12 No 1 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i1.1262

Abstract

Online fraud refers to various fraudulent acts carried out over the internet with the aim of fraudulently obtaining financial gain or personal information. We need to continue to spread awareness about the importance of security for ourselves and the people we know, where currently there are many different modes of online fraud. One application that is well known to the public is the GetContact application, which is an application designed to provide information about incoming calls, identify spam or fraudulent calls, and provide services related to a list of telephone contacts that have been registered by fellow users of the application. In this research, researchers will analyze the sentiment of comments from users of the Getcontact application by comparing the test results of classification algorithms, namely Naïve Bayes Classifier and SVM. This research process will begin with data sampling using the scrapping technique on Google Playstore and processing data from users of the Getcontact application using RapidMiner. After the preprocessing process and model testing with two textmining methods using algorithms, namely SVM and Naive Bayes, the evaluation and validation results show that Naïve Bayes has a higher level of accuracy than SVM. For Naïve Bayes, the accuracy value reached 82.97% with an AUC value of 0.500, while for SVM, the accuracy value was 78.00% with an AUC value of 0.926. These results show that Naïve Bayes is superior in classifying user comments on the Getcontact application on Google Play as positive and negative comments.
Analisis Sentimen Analisis Sentimen Terhadap Twitter Direktorat Jenderal Bea dan Cukai Menggunakan komparasi Algoritma Naïve Bayes dan Support Vector Machine Saputra, Dedi Dwi; Fahlapi, Riza; Kuntoro, Antonius Yadi; Hermanto, Hermanto; Asra, Taufik
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1274

Abstract

Direktorat Jenderal Bea & Cukai (DJBC) is a government agency in charge of guarding and serving export and import activities in Indonesia since its establishment in 1946 which is expected by the community as the front guard in protecting the community in this field, but in recent times there have been many cases involving the institution of the Directorate General of Customs & Excise which make this institution can affect the view of the performance of this institution. With the description of the problem above, it is very interesting to conduct research on public views using tweets from twitter @bravobeacukai and @beacukaiRI which are owned and processed by Direktorat Jenderal Bea & Cukai as a place to channel public opinions and views on this institution. This research uses the Smote method with Naïve Bayes and compared with Support vector machine methods for these results to compare the level of accuracy. The results of this study found that using the Smote method with Naïve Bayes obtained an Accuracy value of 78.95%, Precision 74.01%, Recall 89.41%, and AUC 0.650 while for the Smote method with Support vector machine is worth 73.35% Accuracy, Precision 67.88%, Recall 88.95%, and AUC 0.853. Based on the research results, the smote method with Naïve Bayes has the greatest results and is effective with the dataset studied.
Studi Pengaruh Kemudahan Akses Aplikasi dan Kualitas Layanan terhadap Kepuasan Pelanggan Shopee Food Ani Nuriska Safitri; Mawalda Azharah; Khiyarana Fayziyah; Nadia Septia Aisyah; Antonius Yadi kuntoro; Riza Fahlapi; Dedi Dwi Saputra; Hermanto Hermanto; Taufik Asra
Jurnal Manuhara : Pusat Penelitian Ilmu Manajemen dan Bisnis Vol. 3 No. 3 (2025): Jurnal Manuhara: Pusat Penelitian Ilmu Manajemen dan Bisnis
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/manuhara.v3i3.1926

Abstract

The development of information and communication technology in Indonesia has driven the rapid growth of app-based food delivery services, such as ShopeeFood. The ease of using the application and the quality of service are key factors influencing user satisfaction in utilizing this service. This study aims to analyze the influence of application ease of use and service quality on ShopeeFood user satisfaction in Depok. A quantitative approach was used, with primary data collected through questionnaires distributed to 100 respondents. The data was processed using SPSS by conducting data quality tests, classical assumption tests, t-tests, and F-tests. Based on the research findings, it was concluded that both application ease of use and service quality have a significant influence on user satisfaction, both individually (partially) and jointly (simultaneously). The t-value for ease of use was 6.576 and for service quality was 4.929, both exceeding the t-table value of 1.984 with a significance level of 0.000. Simultaneously, the F-value of 37.967 also indicates a significant influence.
Perancangan UI/UX Design Warung Pintar Berbasis Android Menggunakan Metode Design Thinking (Studi Kasus: Warung 16) Kuntoro, Antonius Yadi; Fahlapi, Riza; Saputra, Dedi Dwi; Hermanto, Hermanto; Sukmawati, Alfiani; Asra, Taufik
Jurnal Ilmu Komputer (JUIK) Vol 5, No 2 (2025): JUNE 2025
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v5i2.4168

Abstract

Perkembangan teknologi informasi yang pesat telah menjangkau berbagai kalangan, termasuk instansi swasta, negeri, wirausahawan, pebisnis, sekolah, hingga perguruan tinggi. Teknologi informasi tidak hanya mempermudah pencarian informasi, tetapi juga mendukung kelancaran bisnis, termasuk aktivitas penjualan. Peran User Interface (UI) dan User Experience (UX) menjadi krusial dalam pengembangan aplikasi untuk memastikan kenyamanan dan kemudahan pengguna. Aplikasi mobile memungkinkan pengguna mengakses informasi, media sosial, dan marketplace online dengan mudah. Warung 16, toko retail di Bogor, melayani pembelian langsung dan delivery via WhatsApp. Namun, metode WhatsApp memiliki kendala seperti ketiadaan informasi stok real-time dan proses pemesanan manual. Penelitian ini merancang UI/UX aplikasi untuk mempermudah pembeli dalam proses pembelian dan akses informasi produk di Warung 16. Desain ini bertujuan meningkatkan efisiensi, mengurangi kesalahan manual, dan menawarkan pengalaman pengguna yang optimal. Melalui pendekatan Design Thinking pada aplikasi warung 16 yang diuji dengan motede System Usability Scale (SUS) terhadap 112 responden menggunakan kuesioner mendapatkan hasil sebesar 91,2 yang menunjukkan bahwa desain memenuhi persyaratan dengan baik dalam uji kegunaan.
ANALISIS KEPUASAN PENGGUNA APLIKASI GOPAY MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN K-FOLD CROSS VALIDATION Usnah, Asmaul; Hasan , Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10276

Abstract

The rapid advancement of digital technology has significantly increased the adoption of digital wallet services in Indonesia, one of which is the GoPay application. This study aims to analyze user satisfaction with GoPay based on user reviews from the Google Play Store. The classification method used is the Naïve Bayes algorithm, with model validation performed using the K-Fold Cross Validation technique. A total of 3,000 reviews were collected through web scraping and then preprocessed using several text preprocessing steps including cleansing, case folding, tokenizing, stopword removal, and stemming. The data was automatically labeled using the IndoBERT model and classified into two satisfaction categories. The classification results show that the Naïve Bayes algorithm achieved an accuracy of 92.46%, with a precision of 92.25%, recall of 94.70%, and an f1-score of 93.46%. Validation using 10-fold cross-validation resulted in an average accuracy of 92.23%. These results indicate that the model demonstrates strong classification performance and stable generalization on unseen data. This research is expected to contribute to improving GoPay's service quality and serve as a reference for the implementation of machine learning techniques in user satisfaction analysis.
KLASIFIKASI CITRA WADAH MINUMAN REUSABLE DAN NON-REUSABLE MENGGUNAKAN MOBILENETV2 Ramanda, Dea; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10349

Abstract

Single-use plastic waste, particularly from beverage bottles, remains a significant contributor to the increasing volume of waste in Indonesia. The limited use of reusable beverage containers underscores the urgent need for technological innovations that can support efficient waste segregation. Addressing this issue, the present study proposes a computer vision-based image classification system designed to automatically distinguish between reusable and non-reusable drinking containers. This research adopts a quantitative experimental approach, employing the MobileNetV2 architecture through transfer learning techniques. The model was trained with augmented and normalized datasets to enhance its generalization across diverse image inputs. Evaluation results demonstrate strong classification performance, achieving 96% accuracy, 99% precision (for tumblers), 95% recall, and a 97% F1-score. These outcomes indicate the effectiveness of MobileNetV2 in identifying visual patterns between container types and its potential for deployment in image-driven waste management systems.
Co-Authors Ali Mustopa, Ali Anasanti, Mila Desi Ani Nuriska Safitri Budiarto, Gunawan Christian, Yoel Dedi Dwi Saputra Dedi Dwi Saputra Dwiza Riana Fahlapi, Riza Febrian, Dio Ferry Syukmana Hasan , Fuad Nur Hasan, Fuad Nur Hasanah, Riyan Latifahul Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Wahono Hermawan, Muhamad Taufik Khiyarana Fayziyah Laia , Metodius Modianus Lasman Effendi M. Rangga Ramadhan Saelan Mahmud Syarif Mawalda Azharah Moh. Arie Hasan Muhammad Syukur Nabilatul Adzra, Salsa Nadia Septia Aisyah Nitra, Ridatu Oca Novianti, Deny Nurajijah, Nurajijah Ramadhan, Xena Hadi Ramanda, Dea Rianto, Yan Ridatu Oca Nitra Ridatu Oca Nitra Ridatu Ocanitra RIZA FAHLAPI Riza Fahlapi Riza Fahlapi Saputra, Dedi Dwi Siti Nurlela siti nurlela Sugiarto, Hady Sukmawati, Alfiani Sutisna, Alifan Widad Taufik Asra Usnah, Asmaul Wahono, Hermanto