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All Journal Elkom: Jurnal Elektronika dan Komputer Jurnal Algoritma Jurnal Informatika Jurnal Inspiration Paradigma JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Information System for Educators and Professionals : Journal of Information System Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JURNAL ILMIAH INFORMATIKA METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi DoubleClick : Journal of Computer and Information Technology INTECOMS: Journal of Information Technology and Computer Science STRING (Satuan Tulisan Riset dan Inovasi Teknologi) JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research METIK JURNAL Jurnal Mantik Technologia: Jurnal Ilmiah Buletin Ilmiah Sarjana Teknik Elektro Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Journal of Applied Engineering and Technological Science (JAETS) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Tekinkom (Teknik Informasi dan Komputer) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal AbdiMas Nusa Mandiri Yayasan Cita Cendikiawan Al Khwarizmi Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Sistem Komputer Triguna Dharma (JURSIK TGD) Jurnal Algoritma Journal Of Communication Education Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Jurnal Teknik Elektro dan Komputer Asian Journal of Management, Entrepreneurship and Social Science
Windu Gata
Universitas Nusa Mandiri
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Analisis Perbandingan Algoritma Machine Learning Terhadap Sentimen Analis Pemindahan Ibu Kota Negara Arif Rahman Hakim; Windu Gata; Alda Zevana Putri Widodo; Oky Kurniawan; Arief Rama Syarif
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 2 (2023): APRIL-JUNE 2023
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i2.701

Abstract

The Indonesian nation was enlivened with news about the relocation of the State Capital (IKN). The government's plan to move IKN is based on Indonesia's vision and mission in 2045, namely advanced Indonesia. Twitter is one of the microblogging communication tools used to express opinions. Various algorithms have been used to analyze sentiment towards an opinion such as Support Vector Machine, Naive Bayes and Random Forest. This study aims to compare the performance of three classification algorithms, namely Support Vector Machine, Naïve Bayes and Random Fores. The highest accuracy results are using the Support Vector Machine algorithm and added with the Synthetic Minority Oversampling Technique Method (SMOTE) feature of 82.82%, Precision 79.34%, Recall 88.75%, 87.78% and ROC AUC 82.82%. Naive Bayes accuracy is 81.18%, Precision 84.89%, Recall 75.86%, 80.13% and ROC AUC 81.18%. and Random Forest accuracy of 79.55, precision 84.48%, recall 72.39%, 77.97% and ROC AUC 77.55%.
Analisis Sentimen pada Komen Twitter Pawang Hujan Mandalika dengan Support Vector Machine (SVM) dan Naïve Bayes Rahmat Satria Buana; Windu Gata; Alda Zevana Putri Widodo; Hendra Setiawan; Khairunisa Hilyati
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 2 (2023): APRIL-JUNE 2023
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i2.705

Abstract

Indonesia is a country with a majority Muslim population, but Indonesia is also rich in culture influenced by previous religions such as Hinduism and Buddhism. The rain handler by Muslims is considered shirk, but on the other hand also considers this ancestral culture that has always existed. With the advancement of human technology, it is easier to express opinions or opinions regarding a topic that is currently being discussed, for example, regarding the rain handler who acted at the Mandalika Circuit some time ago through social media. Twitter is one of the social media that is used as a forum to accommodate these opinions. In this study, the CRISP-DM (Cross Industry Standard Process for Data Mining) data mining methodology was used with Rapid Miner Version 9.10 with the Support Vector Machine (SVM) classification method and nave Bayes with SMOTE to improve accuracy. The application of the SVM method is 97.71 % with AUC 0.997 Positive Comments, and Using Naïve Bayes, the accuracy obtained is 93.41% accuracy with AUC 0.973 Positive Comments.
SURVEI KEPUASAN KADER POSYANDU TULIP TERHADAP PENGGUNAAN APLIKASI SIPOS UNTUK PENDATAAN DAN PELAPORAN SECARA DIGITAL Linda Marlinda; Taranza Taranza; Windu Gata
Jurnal AbdiMas Nusa Mandiri Vol 5 No 1 (2023): Periode April 2023
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v5i1.4061

Abstract

Pemerintah Desa Cipenjo sangat aktif mengadakan kegiatan - kegiatan untuk warga dan masyarakat sekitar, tidak hanya itu para kader - kader ibu PKK dan Aktifis Posyandu juga turut berpartisipasi dalam kegiatan ini. Saat ini Pemerintah Desa berharap agar masyarakat dibekali dengan kemampuan mengoperasikan Microsoft, hal ini bermanfaat untuk membuat segala kegiatan yang berlangsung menjadi automation. Pengabdian ini bertujuan memberi kontribusi pada ibu kader PKK dan Posyandu agar dapat mengoperasikan komputer guna mendukung kegiatan - kegiatan dan pencatatan yang dibuat di Pemerintah Desa.Setelah mengikuti pelatihan, peserta pelatihan terbukti lebih percaya diri untuk berbicara di depan public karena mereka lebih memahami cara mengoperasikan Microsoft
Penerapan Finite State Automata pada Proses Peminjaman Ruang Laboratorium Komputer Universitas Bina Sarana Informatika Oky Kurniawan; Fikri Ismaya; Windu Gata; Jordy Lasmana Putra; Fitra Septia Nugraha
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 10, No 4 (2022)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v10i4.47879

Abstract

Dengan semakin berkembangnya teknologi dalam dunia pendidikan terutama perguruan tinggi, sistem informasi sangat dibutuhkan untuk menunjang segala aktivitas dalam proses kegiatan belajar mengajar. Universitas Bina Sarana Informatika sebagai perguruan tinggi yang tentunya harus mempunyai sarana kegiatan belajar mengajar seperti ruang kelas dan laboratorium. Laboratorium dibutuhkan dalam menunjang proses kegiatan belajar mengajar dengan metode praktikum. Laboratorium pada Universitas Bina Sarana Informatika tentu dalam penggunaannya dibawah tanggung jawab dari staf laboran. Dalam manajemennya sistem peminjaman laboratorium pada universitas Bina Sarana informasi masih menggunakan metode pembukuan manual. Selain Pembuatan laporan penggunaan laboratorium oleh staf laboran yang terkesan lama serta informasi mengenai pemakaian laboratorium yang tidak akurat dan realtime maka dibutuhkanlah sebuah sistem yang dapat memudahkan staf laboran di Universitas Bina Sarana Informatika dalam manajemen peminjaman dan pemakaian laboratorium. Pada Paper ini membahas Teori Finite State Automata (FSA) jenis Nondeterministic Finite Automata (NFA) yang diimplementasikan pada alur proses aplikasi sistem informasi peminjaman laboratorium. Dengan adanya aplikasi sistem peminjaman ini kemudahan dalam pendataan manajemen laboratorium oleh staf laboran ditampilkan dengan monitoring dan status yang akurat. Dimana ketika laboratorium sedang dipakai maka mahasiswa, dosen maupun ketua program studi mengetahui bahwa laboratorium itu sedang dipakai, ataupun jika ingin meminjam laboratorium maka tidak perlu mendatangi staf laboran cukup reservasi menggunakan media sistem informasi dari peminjaman laboratorium ini.
ALGORITMA REGRESI LINIER UNTUK MEMPREDIKSI PENGARUH PROMOSI TERHADAP PENJUALAN PRODUK K31 S-2 DENGAN FRAMEWORKS CRISP-DM Ipang Sasono; Ria Hartati; Gusli Chidir; Windu Gata
Journal Of Communication Education Vol 17, No 2 (2023): JOCE-IP Vol. 17 No. 2 Tahun 2023
Publisher : Universitas Insan Pembangunan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/joce-ip.v17i2.339

Abstract

Tujuan dari penelitian ini untuk mengetahui penggunaan budget promosi yang terukur dan menghasilkan penjualan pada produk K31 S-2 yang optimal dan apakah pengeluaran budget saat ini sudah sesuai atau belum. Penelitian ini menggunakan perusahaan dibidang manufaktur dengan tujuan untuk mendapatkan informasi yang akurat mengenai prediksi pengaruh promosi terhadap penjualan dengan menggunakan frameworks CRISP-DM. Hasil penelitian didapatkan nilai coefficients sebesar 9.61652512 dan intercept 123757.37057197 dengan nilai R2 adalah 0.93 yang sehingga model tersebut fit dengan data yang ada  yang menghasilkan budget promosi lebih besar dari yang seharusnya sehingga omset yang didapatkan tidak sesuai dengan budget yang dikeluarkan, sehingga budget yang dikeluarkan lebih besar 17% dari yang seharusnya.
The Implementation of Finite State Automata Concept in Data Integration Services Submission Heri Nurcahyo; Windu Gata; Eni Heni Hermaliani; Hafifah Bella Novitasari; Suwanda Aditya Saputra
Jurnal Teknik Elektro dan Komputer Vol. 11 No. 1 (2022): Jurnal Teknik Elektro dan Komputer
Publisher : Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35793/jtek.v11i1.37142

Abstract

The submission of Data Integration Services on regional apparatus in the DKI Jakarta Provincial Government is still processed manually. The data user proposes data integration services by attaching a data analysis requirement document addressed to the Data Producer and a copy to the data guardian. The Problems of manual submitting services are the difficulty of tracking the integration status, filling out the application data analysis form is inappropriate and incomplete, the data integration submission letter is not properly archived, and the results of the coordination betwen users and data producers are not properly documented.This study aims to design an application for submitting data integration services by applying the concept of Finite State Automata which is expected to provide convenience and benefits for data users in data integration submission, facilitate data producers in verifying data integration submission and facilitate the Department of Communication, Informatics, and Statistics of DKI Jakarta as data guardian in providing data integration services for Regional Apparatus in the DKI Jakarta Provincial Government.
Adversıty Quotıent: Perspectıves On Work Challenges For Mıllennıals And Beyond Nia Kusuma Wardhani; Windu Gata
Asian Journal of Management, Entrepreneurship and Social Science Vol. 4 No. 03 (2024): August Asian Journal of Management Entrepreneurship and Social Science ( AJMES
Publisher : Cita Konsultindo Research Center

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

Abstract

This study examines the Adversity Quotient (AQ) among millennial employees in Indonesia, focusing on the dimensions of Control, Ownership, Reach, and Endurance (CORE). Using a qualitative approach, the study integrates text mining methods to analyze responses from millennial and Generation Z employees. The findings indicate that AQ plays a crucial role in helping employees effectively handle work challenges through the development of critical thinking, resilience, and adaptability. Employees with high AQ tend to perform better and adapt to the dynamic changes in the workplace environment. This research provides insights for managers and stake holders to develop strategies that support AQ development in employees, particularly in today’s competitive and digital era
Pelatihan Membuat Desain Kemasan Produk UMKM Menggunakan Canva bagi Remaja RT 003 Green De Jalen Tambun Jawa Barat Sulistianto Sutrisno Wanda; Linda Marlinda2; Windu Gata
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1335

Abstract

Permasalahan utama yang dihadapi Remaja saat ini adalah orientasi atas statusnya sebagai remaja. Di wilayah RT.003 Green de Jalen, Tambun Utara, remaja dengan statusnya entu harus mendapatkan arahan ang positif agar memiliki potensi. Disisi lain rendahnya daya saing visual terhadap produk akibat desain kemasan kurang menarik bagi UMKM. Bagaimana, remaja di lingkungan RT. 003 RW. 11 Green de Jalen  memiliki potensi besar sebagai digital native. Karena remaja memiliki potensi dalam membuat dan merekayasa, namun belum terarahkan secara optimal untuk kegiatan produktif. Pelatihan ini bertujuan untuk memberikan keterampilan praktis kepada remaja RT.003 RW. 11 Green de Jalen, Tambun Utara, Kabupaten Bekasi, Jawa Barat 17510 dalam merancang desain kemasan produk UMKM yang profesional menggunakan aplikasi Canva. Metode pelaksanaan kegiatan meliputi sosialisasi pentingnya branding, pelatihan teknis penggunaan fitur-fitur Canva, serta praktik langsung membuat desain kemasan bagi produk lokal warga sekitar. Hasil yang diharapkan dari kegiatan ini adalah terciptanya identitas visual produk yang lebih modern dan mampu meningkatkan nilai jual UMKM di pasar digital maupun konvensional. Selain itu, program ini bertujuan untuk menumbuhkan jiwa kewirausahaan dan kepedulian sosial di kalangan remaja terhadap potensi ekonomi di lingkungan tempat tinggal mereka. Melalui kolaborasi ini, diharapkan terjadi transformasi digital pada UMKM lokal yang didorong oleh kreativitas generasi muda Green de Jalen.
EagleEyes: An Artificial Intelligence-Based Approach for Automatic Traffic Violation Detection Using Deep Learning Windu Gata; Muhammad Haris; Maria Irmina Prasetiyowati; Sony Harianto
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1097

Abstract

Rapid urbanization and the advancement of smart city programs in Indonesia necessitate intelligent, automated solutions for traffic monitoring and law enforcement. This study introduces EagleEyes, an artificial intelligence–based framework designed for automatic detection of multiple traffic violations by integrating the YOLOv8 deep learning architecture with Optical Character Recognition (OCR) for vehicle license plate identification. YOLOv8 was selected due to its anchor-free design, decoupled detection head, and enhanced feature fusion modules, which collectively improve detection accuracy, convergence speed, and small-object recognition compared to YOLOv5 and YOLOv7, while maintaining lightweight computational efficiency suitable for real-time applications. The proposed system was trained on a multi-class dataset representing common Indonesian violations, including seat belt non-compliance, helmet absence, motorcycle overcapacity, and unreadable license plates. Experimental results demonstrate robust performance, achieving a precision of 0.91, recall of 0.92, and mean average precision (mAP@0.5) of 0.96 at the optimal epoch, with an average inference speed of 25 frames per second and total training time of approximately 15 minutes on an NVIDIA RTX GPU. The OCR module attained an average recognition accuracy of 98.7%, although its performance decreased for vehicles captured beyond a five-meter distance due to reduced clarity and illumination inconsistencies. Implemented as a web-based application using the Flask framework, EagleEyes enables flexible browser-based visualization, and can be seamlessly integrated into Indonesia’s Electronic Traffic Law Enforcement (ETLE) infrastructure. Overall, the system demonstrates high potential to enhance smart city traffic management through scalable, AI-driven, and ethically responsible automation.
Perbandingan Kinerja Machine Learning dan Deep Learning untuk Analisis Sentimen Fufufafa Darusman Darusman; Windu Gata
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Vol 10 No 1 (2025): INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS (Juni 2025)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/isbi.v10i1.3333

Abstract

This study examines the performance comparison of various machine learning and deep learning models in sentiment analysis of the fufufafa phenomenon on Twitter. The models tested include Naive Bayes, Random Forest, Support Vector Machine, Logistic Regression, Decision Tree, and Long Short-Term Memory (LSTM). The study aims to evaluate the effectiveness of these models in classifying sentiment into positive, negative, and neutral categories. Experimental results show that the Decision Tree model achieved the highest accuracy of 96%, followed by LSTM with 95%. Other models, such as Random Forest, Support Vector Machine, and Logistic Regression, achieved an accuracy of 94%, while Naive Bayes recorded the lowest accuracy at 81%, primarily due to its limitations in handling more complex sentiments. The LSTM model proved to be superior in capturing temporal contexts and word relationships, delivering more accurate predictions despite requiring greater computational resources. The findings of this study affirm that deep learning models, particularly LSTM, are more effective in analyzing sentiment in dynamic and complex data, such as that found on Twitter, compared to machine learning models. These results provide valuable insights for developing more efficient and accurate sentiment analysis methodologies in the future.
Co-Authors Achmad Bayhaqy Achmad Fatkharrofiqi Ahmad Baihaqi Ahmad Bayhaqqi Ahmad Toha Alda Zevana Putri Widodo Ali Ahmad Andita Permata Rahmawati Anggun Yuli Asih Anisah Novitarani Annisa Elfina Augustia Annisa Novtariany Annisa Novtariany Arief Rama Syarif Arif Rahman Hakim Bagus Dwi Wicaksono Bryan Pratama Chairul Fikri Cicih Sri Rahayu Darusman Darusman Dedi Dwi Saputra Dedik Erwanto Dwi Andriyanto Dwin Indrawan Eni Heni Hermaliani Enie Heni Hermalani Erni Erni Fadillah Said Fahmi Ardiansyah Fakhrudin Fakhrudin Fakihotun Titiani Fariszal Nova Arviantino Faruq Aziz Febri Ainun Jariyah Febri Ainun Jariyah Fikri Ismaya Fitra Septia Nugraha Frieyadie Gusli Chidir Hafifah Bella Nofitasari Hafifah Bella Novitasari Hafifah Bella Novitasari Hafifah Bella Novitasari Hamdan Harianto Hendra Budi Kusnawan Hendra Setiawan Heri Nurcahyo Hernawati Hernawati I Gusti Bagus Arya Pradnja Paramitha Ihud Hafid Ilham Wahyudi Siadi Ipang Sasono Jordy Lasmana Putra Ketut Sakho Parthama Khabib Astoni Khairunisa Hilyati Kukuh Panggalih Kusnadi Kusnadi Lael Kurniawati Laela Kurniawati Lili Dwi Yulianto Linda Marlinda Linda Marlinda2 Mahdi Abdullah Maria Irmina Prasetiyowati Mohamad Noor Muhammad Haris Muhammad Romadhona Kusuma Muji Ernawati Nia Kusuma Wardhani Oky Kurniawan Purwono, Purwono Rahmat Satria Buana Resi Taufan Rhini Fatmasari Ria Hartati Rian Hidayat Rini Novi Ambarwati Risnandar Risnandar Ristyani Slamet Rosadi Rosadi Ruhul Amin Satria Budi Sena Ramadona Cakrawijaya Sendi Permana Sony Harianto Sri Rahayu Subagja Putra Pratama SUGIYANTO S.KOM. Sulistianto Sutrisno Wanda Supriadi Pangabean Susanto Lim Suwanda Aditya Saputra Syarif Hidayat Taransa Agasya Tutupol Taranza Taranza Trisiwi Indra Cahyani Tuti Haryanti Valianda Farradillah Hakim Venny Yulianty Virda Mega Ayu Wawan Kurniawan Yessica Fara Desvia Yuris Alkhalifi