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All Journal DEDIKASI JURNAL MAHASISWA Jurnal Online Mahasiswa (JOM) Bidang Perikanan dan Ilmu Kelautan Journal of Industrial Engineering Management Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Riset Informatika JURNAL MANAJEMEN PENDIDIKAN ISLAM AL-IDARAH Jurnal Rupa Jurnal ICT : Information Communication & Technology Grouper: Jurnal Ilmiah Perikanan Jurnal Visual JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Lex Suprema Jurnal Nasional Teknologi Komputer Jurnal Ilmiah Dan Karya Mahasiswa Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat APPA : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat dan Riset Pendidikan International Journal of Applied Mathematics and Computing. International Journal of Computer Technology and Science International Journal of Information Engineering and Science Public Health And Medicine Journal (PAMA) Aktivitas Jurnal Ilmiah Akuntansi
Tri Wahyudi
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Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Veterinary Other

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Analisis Dampak Sistem Pembayaran Non Tunai Terhadap Efisiensi Operasional dan Keamanan di Arini Dental Care Cikarang Yuyun Putri Lestari; Tri Wahyudi
AKTIVITAS Jurnal Ilmiah Akuntansi Vol. 3 No. 1 (2025): AKTIVITAS
Publisher : Prodi Akuntansi Universitas Pamulang PSDKU Serang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/aktivitas.v3i1.45737

Abstract

Di era digitalisasi sekarang, metode pembayaran dapat dilakukan dengan menggunakan metode non tunai (cashless). Dengan semakin berkembangnya teknologi, pembayaran dapat dilakukan menggunakan kartu debit, qris, maupun transfer bank. Berdasarkan Perbup Nomor 64 Tahun 2018 Kabupaten Bekasi, sistem pembayaran non tunai sudah berlaku dan dilaksanakan berdasarkan efisiensi, keamanan, dan manfaat. Dalam peraturan tersebut, diharapkan dapat menjadi pedoman dan panduan implementasi transaksi non tunai pada pihak-pihak terkait.Penelitian ini bertujuan untuk mengetahui bagaimana dampak yang  diberikan dari adanya sistem pembayaran non tunai yang mencakup efisiensi operasional dan juga keamanan transaksi serta kepuasan pelanggan di Arini Dental Care sebagai lokasi dari penelitian ini. Metode penelitian yang digunakan adalah kualitatif deskriptif dengan teknik pengambilan data melalui survei serta wawancara terhadap pelanggan dan staff klinik.  
Perancangan Sistem Presensi Karyawan Berbasis Web Dengan Integrasi GPS Menggunakan Laravel dan Metode RAD (Rapid Application Development) pada PT. Kolling Advertising Muhammad Ashori Fahmi; Muhammad Bintang Pamungkas; Tri Wahyudi; Joko Priambodo
BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia Vol. 3 No. 4 (2025): BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia
Publisher : CV. Shofanah Media Berkah

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

Abstract

This research aims to design and develop a web-based employee attendance system integrated with GPS using the Laravel framework and the Rapid Application Development (RAD) method for PT. Kolling Advertising. The system is created to address several issues found in manual attendance processes, such as data loss, slow recap processing, and potential fraud, including proxy attendance. The development process includes requirements analysis, interface design, implementation of core features (attendance, leave request, recapitulation, and leaderboard), GPS-based location validation, and Black Box testing. The results indicate that the system is capable of processing attendance data in real time, reducing data manipulation, and improving administrative efficiency. Therefore, the proposed system successfully enhances attendance monitoring and supports effective employee management within the company.
Tren NLP dalam Analisis Sentimen Media Sosial: Tinjauan Sistematis dan Bibliometrik Tri Wahyudi; Purwati, Nani; Hasan, Noor; Budi Sulistyo, Gunawan
Jurnal ICT: Information Communication & Technology Vol. 25 No. 2 (2025): JICT-IKMI, December , 2025
Publisher : LPPM STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v25i2.341

Abstract

Penelitian ini menyajikan Systematic Literature Review (SLR) mengenai penerapan Natural Language Processing (NLP) untuk analisis sentimen pada media sosial dalam periode 2020 hingga 2025. Sebanyak 400 artikel awal diperoleh dari berbagai database bereputasi, termasuk IEEE Xplore, Scopus, SpringerLink, ACM Digital Library, ScienceDirect, dan Google Scholar. Setelah dilakukan filtrasi berdasarkan kriteria inklusi, eksklusi, serta quality assessment, sebanyak 201 artikel dinyatakan relevan untuk dianalisis lebih lanjut. Proses SLR mengikuti pedoman Kitchenham yang terdiri atas tiga fase, yaitu planning, conducting, dan reporting. Hasil penelitian menunjukkan bahwa tren publikasi meningkat signifikan dari tahun 2020 hingga 2024, kemudian menurun pada 2025 karena data hanya dihimpun sebagian. Twitter muncul sebagai platform yang paling sering diteliti, diikuti oleh Facebook, Instagram, dan ulasan e-commerce. Metode klasik seperti Naïve Bayes dan SVM masih digunakan untuk kasus sederhana, namun penelitian terkini menunjukkan dominasi metode deep learning dan transformer-based seperti CNN, LSTM, dan BERT yang secara konsisten mencapai tingkat akurasi di atas 90%. Tantangan utama yang diidentifikasi meliputi pemrosesan multibahasa, slang, sarkasme, code-mixing, serta keterbatasan dataset berlabel. Penelitian ini menyimpulkan bahwa arah penelitian ke depan perlu difokuskan pada pengembangan NLP multibahasa, analisis sentimen berbasis domain tertentu, serta pemanfaatan pre-trained transformer models untuk meningkatkan akurasi dan pemahaman kontekstual dalam analisis sentimen media sosial.
Implementation of Social Media Network Block Access Using Fortinet Case Study at PT Estrada Rasiban Rasiban; Tri Wahyudi; Elviwani Elviwani; Aditya Bagas Pramudhi
International Journal of Computer Technology and Science Vol. 1 No. 1 (2024): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i1.296

Abstract

Computers in one of the network companies at PT. Estrada uses the Fortinet operating system. The final result expected through this implementation is to comprehensively see the capabilities of the firewall on Fortinet in overcoming the problem of blocking social media applications and streaming platforms during working hours. Blocking the application in question is the ability to filter web processes such as Facebook, Instagram, YouTube, etc. In the tests carried out, web filtering was able to block applications on social media and streaming platforms, which proves that the performance of web filtering is quite good. In analyzing web filtering performance, use the office hour rule tool by carrying out the rule schedule in the Fortinet network and displaying all the information in detail. The final result obtained in the network application filtering simulation process using Fortinet is that every network sent cannot be entered (blocked) on both social media applications and streaming platforms.
Implementation of the A* (A STAR) Algorithm in Searching the Closest Route from Pisangan Lama Jakarta Timur to Kampus Stikom CKI Pusat Dadang Iskandar Mulyana; Tri Wahyudi; Muhammad Joko Umbaran; Rofik Rofik
International Journal of Computer Technology and Science Vol. 1 No. 1 (2024): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i1.303

Abstract

Jakarta, the capital of Indonesia, is known for its high congestion levels. Data from the TomTom Traffic Index shows that Jakarta ranked 30th in the world in 2023 as one of the most congested cities, with a congestion level reaching 53% during peak hours. Pisangan Lama in East Jakarta is one of the densely populated areas, adjacent to busy roads. The main campus of STIKOM CKI, also located in East Jakarta, is situated along a route prone to heavy traffic. Given the congestion issues and the lack of information on the nearest routes, this study aims to implement the A* algorithm to find the shortest route from Pisangan Lama, East Jakarta, to the main campus of STIKOM CKI. The A* algorithm is chosen for its optimal routing capabilities. Based on research on three routes (Jl. I Gusti Ngurah Rai, Jl. Basuki Rachmat, and Jl. Raya Kalimalang), the results show that the route via Jl. Basuki Rachmat is the shortest, with a distance of 7.7 km. The implementation of the A* algorithm is expected to provide an efficient solution for the community in finding the nearest route.
Sentiment Analysis of the Kabur Aja Dulu Trend on X as a Basis for Designing a Public Sentiment Monitoring System Using Naïve Bayes and SVM Sutisna Sutisna; Tri Wahyudi; Dwi Swasono Rachmad; Fachrur Rozi
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i3.79

Abstract

Social media X (Twitter) has become the main platform for the Indonesian public to express opinions, including on the trend of 'kabur aja dulu' (let's just run away for a bit). This research aims to classify the sentiments of the public using the Naïve Bayes and Support Vector Machine (SVM) methods, and to compare the accuracy of both in sentiment analysis. Data was collected via the Twitter API with the hashtag #kaburajadulu, resulting in 2,067 tweets, which, after the cleansing process and manual labeling, left 385 data points. The analysis process followed the CRISP-DM stages, which include business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Model evaluation was conducted using a confusion matrix with accuracy, precision, and recall metrics. The classification results show that 82% of tweets have a positive sentiment and 18% negative. The Naïve Bayes algorithm achieved an accuracy of 86.49%, slightly lower than SVM, which reached 88.05%. In conclusion, Support Vector Machine is more effective in sentiment classification on public opinion data. This research contributes to the digital mapping of public opinion and recommends the development of automatic labeling methods as well as the exploration of advanced algorithms in the future.
A HOLISTIC AI-DRIVEN ENERGY-EFFICIENT IOT FRAMEWORK FOR SMART AGRICULTURE USING MULTI-RESOURCE OPTIMIZATION Gunawan Budi Sulistyo; Nani Purwati; Tri Wahyudi; Noor Hasan
Jurnal Riset Informatika Vol. 8 No. 3 (2026): Juni 2026
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i3.525

Abstract

The rapid adoption of Internet of Things (IoT) technologies has accelerated the development of smart agriculture systems. However, existing studies predominantly focus on single-resource optimization and lack integrated artificial intelligence (AI) approaches within distributed architectures, resulting in suboptimal system-wide performance. This study proposes an AI-driven energy-efficient IoT framework that integrates the Random Forest algorithm with an edge–fog–cloud computing architecture to enable holistic multi-resource optimization. A quantitative simulation-based approach was employed using soil moisture data from the NASA SMAP dataset, with a case study in Magelang, Indonesia. The system was evaluated using key performance metrics, including energy consumption, network latency, packet delivery ratio (PDR), and water usage efficiency. The results demonstrate significant improvements, including a 28.65% reduction in energy consumption, a 31.43% decrease in latency, an increase in PDR to 96.8%, and a 20.3% improvement in water usage efficiency. Statistical validation confirms that these improvements are significant (p < 0.05). The main contribution of this study lies in the development of a holistic AI-driven IoT framework that simultaneously optimizes energy, water, computation, and communication without trade-offs. The proposed approach offers a scalable, adaptive, and efficient solution for real-world smart agriculture systems.
Stabilization of Distance Measurement Between Landmarks for Gesture Recognition Using Polynomial Regression Dadang Iskandar Mulyana; Tri Wahyudi; Dwi Swasono Rachmad; Muhammad Khalid
International Journal of Applied Mathematics and Computing Vol. 1 No. 3 (2024): July : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i3.120

Abstract

Gesture recognition technology enables computers and digital devices to detect, understand, and interpret human body movements through image processing techniques. This technology has significant potential to facilitate communication between individuals with hearing impairments and those without, thereby improving interaction and mutual understanding. However, the accuracy of gesture recognition systems is often influenced by variations in the distances between hand landmark points, which can introduce instability and reduce recognition performance. To address this issue, this study proposes a polynomial regression-based approach to stabilize distance measurements between hand landmarks in gesture recognition tasks. The proposed method calculates and normalizes landmark distances using polynomial regression to minimize measurement fluctuations and improve recognition accuracy. The system is implemented using the MediaPipe framework for real-time hand detection and tracking, while OpenCV is utilized for video processing and management. Experimental results demonstrate that the proposed approach significantly enhances the stability and accuracy of gesture detection. The developed system successfully recognizes hand gestures representing the letters A through F with an average accuracy exceeding 98.3%. Furthermore, the application of polynomial regression effectively reduces noise in landmark data, contributing to more reliable and accurate gesture recognition performance.
Data Mining Classification in The New Student Admission Process Using The K-Nearest Neighbors Method : Case Study: Yapmi Boarding School Veri Arinal; Tri Wahyudi; Mesra Betty Yel; Nurul Khoiriyah
International Journal of Applied Mathematics and Computing Vol. 1 No. 4 (2024): October: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i4.111

Abstract

The new student admission process is an important activity in educational institutions to ensure that prospective students meet the established admission criteria. However, the selection process is often conducted manually, making it less efficient and prone to subjective assessments. This study aims to implement a data mining classification approach using the K-Nearest Neighbors (K-NN) method to support decision-making in the new student admission process at Yapmi Boarding School. The research utilizes historical admission data consisting of academic scores, interview results, and other admission criteria as classification attributes. The K-NN algorithm was applied to classify prospective students into accepted and rejected categories based on the similarity of their characteristics to previously evaluated applicants. The research methodology includes data collection, preprocessing, classification modeling, and performance evaluation using accuracy metrics. The results demonstrate that the K-NN method is capable of classifying prospective students effectively and can assist admission committees in making more objective and accurate decisions. The implementation of this model contributes to improving the efficiency, consistency, and reliability of the student admission process at Yapmi Boarding School. Therefore, the K-NN algorithm can be considered a viable alternative for supporting educational admission decision systems.
Sentiment Analysis of the Trending Topic #Indonesiagelap on X Using a Naive Bayes Algorithm Based on Particle Swarm Optimization Untung Surapati; Veri Arinal; Tri Wahyudi; Ahmad Fauzan
International Journal of Applied Mathematics and Computing Vol. 2 No. 2 (2025): April: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i2.127

Abstract

The rise of social media has created a digital public sphere that enables users to express their opinions on social and political issues openly and in real-time. One of the most discussed topics on social media platform X is the trending hashtag #IndonesiaGelap, which reflects public concern and criticism regarding various governmental and societal conditions. This study aims to conduct sentiment analysis on tweets containing the hashtag to determine the overall sentiment trend among users. The method employed in this research is the Naive Bayes classification algorithm, known for its simplicity and effectiveness in text classification. To enhance the model’s performance, Particle Swarm Optimization (PSO) is applied to optimize feature selection and parameter tuning. The dataset consists of public tweets collected via the Twitter API, followed by preprocessing, feature extraction using TF-IDF, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that the integration of PSO significantly improves the classification accuracy of the Naive Bayes model compared to the baseline. The majority of tweets related to #IndonesiaGelap exhibit a negative sentiment, indicating widespread public dissatisfaction and criticism. This research is expected to contribute to a better understanding of public perception and serve as valuable input for stakeholders in addressing social issues in the digital age.
Co-Authors Achmad Farid Adia Lestari Aditya Bagas Pramudhi Ahmad Fauzan Ahmad Indra Harahap Aldo Amanullah Ali Jamaludin Any Sawheri Gading Arbansyah Arbansyah Arinal, Veri Asmika Harnalin Simarmata Aulia Khofifah Syamsuri Betty Yel, Mesra Dadang Iskandar Mulyana` Delicia Delicia, Delicia Della Anggun Yuniasari Deni Saeful Rizal Dian Ekawaty Dona Wahyuning Laily Dwi Swasono Rachmad Elviwani Elviwani Endah Sih Prihatini Fachrur Rozi Farid Wajdi Ferdi Iwanda Fitriani Fitri Gunawan Budi Sulistyo Hamada Zein Hj. Afriyana Amelia Nuryadin I Gusti Bagus Wiksuana Ilhan Firanda Iwan Giri Waluyo Joko Priambodo Joni Saputra Jordi Bernard Siburian Kharisma Idola Arga Khusnul Khotimah Muhamad Wahyu Tirta Muhammad Anshori Fahmi Muhammad Ashori Fahmi Muhammad Bintang Pamungkas Muhammad Galang Muhammad Joko Umbaran Muhammad Khalid Muhammad Khumaidi Nursyarif Muhammad Sukirlan Muntalim Muntalim Nandang Munandar Nani Purwati Noor Hasan Nurul Khoiriyah Pertiwi, Ratih Prisma Dwicahyo Putra Rizky PUTRI ANGGRAENI Rafa Nursyahela Rahmahwati, Ratih Ramlan Ginting Suka Rasiban Rasiban Ratih Rahmawati Renaldo Wijaya Reza Fadillah Rofik Rofik Silvia Uslianti Siti Muawwanah Siti Patimah Sutisna Sutisna Tengku Dahril, Tengku Tri Wahyuni Untung Surapati Uslianti, Silvia Yuyun Putri Lestari