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All Journal Jurnal Teknologi Lingkungan Universitas Trisakti AJIE (Asian Journal of Innovation and Entrepreneurship) Jurnal Sains Dan Teknologi Lingkungan Jurnal Sains & Teknologi Lingkungan Jurnal Ilmiah KOMPUTASI INTEGER: Journal of Information Technology Jurnal Sains dan Informatika JSiI (Jurnal Sistem Informasi) Al-Ard: Jurnal Teknik Lingkungan JUSIM (Jurnal Sistem Informasi Musirawas) Journal of Information Systems and Informatics JUKANTI (Jurnal Pendidikan Teknologi Informasi) Prosiding National Conference for Community Service Project Jurnal Pena Indonesia JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) INSERT: Information System and Emerging Technology Journal Telcomatics Journal of Information System and Technology (JOINT) Khazanah: Jurnal Mahasiswa INDONESIAN JOURNAL OF URBAN AND ENVIRONMENTAL TECHNOLOGY Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Social Engagement: Jurnal Pengabdian Kepada Masyarakat Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan
Andik Yulianto
Universitas Islam Indonesia, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Menentukan Harga Kain Katun Menggunakan Fuzzy Inference System Metode Mamdani Lim, Louis; Rinaldo, Rinaldo; Lee, Lesley Peterson; Sherly, Sherly; Yulianto, Andik
Telcomatics Vol. 9 No. 1 (2024)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v9i1.9365

Abstract

Entrepreneurs must keep up with technological developments to compete in an increasingly competitive business environment. This competition causes price fluctuations that affect sales, requiring the right decisions for business survival. Cotton fabric is highly favored by consumers in the textile industry. The success and failure of this business depends on pricing. Setting a selling price too high may cause customer dissatisfaction, while setting a price too low may cause business losses. Therefore, determining an optimal selling price is crucial. Adopting fuzzy logic is proposed as a solution for this problem. Fuzzy logic can be applied to predict the selling price of cotton fabrics. This test aims to determine the selling price of cotton cloth by making a Fuzzy Inference System (FIS) using the Mamdani method with variables of material quality, production method, design, and coloring method as considerations. The results of this test show that the comparison of the system made by manual calculation and simulation with Python has an error rate of 0,00019% calculated by MAPE. Based on the results, this system is useful as an auxiliary tool in making decisions because it is able to overcome uncertainty in determining the selling price of cotton fabric.
Pengembangan Sistem Penentuan Durasi Lampu Hijau Pada Lampu Lalu Lintas Menggunakan Fuzzy Logic Yeo, Stefan; Tiffano Miracle Gaghana, Dave; Jason; Chandra Wijaya, Kevin; Stephen; Yulianto, Andik
Telcomatics Vol. 9 No. 1 (2024)
Publisher : Universitas Internasional Batam

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

Abstract

Pavement is one of the most important aspects of the economy and everyday life in a city, as it is always used by people in their activities. The appearance of obstacles on the road can cause losses to both the economy and the quality of life of local residents. One form of obstacle that often appears on roads is traffic jams. This traffic jam can be caused by many things, ranging from the road condition, the number of vehicles, to a less than optimal red light system. This is where the application of fuzzy logic in a dynamic traffic light system can help to solve the problem.
Sistem Kendali dan Monitoring Irigasi pada Rumah Kaca Berbasis Bluetooth dengan Metode Fuzzy Logic Sak, Erwin; Yulianto, Andik; Sabariman, Sabariman
Telcomatics Vol. 9 No. 1 (2024)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v9i1.9489

Abstract

In general, plantations using greenhouses or Green Houses are faced with various obstacles. Changes in temperature and humidity in the room are unpredictable and you have to determine the right time to water and determine which plants to plant by seeing whether the plants can tolerate the temperature and humidity levels in the greenhouse room and estimating how much watering should be done.From these problems, the author created a Green House Prototype and an irrigation system using the Fuzzy Method which is capable of monitoring and watering plants automatically.Based on the results of the analysis by applying the Fuzzy method in the irrigation system, the author can control the watering of Strawberry plants and adjust the Temperature, Humidity and moisture levels to a good ecosystem for the growth of Strawberry plants in the Prototype Green House.
Pengembangan Sistem Pengenalan Plat Nomor Indonesia Menggunakan YOLOv8 dan EasyOCR Anthony; Herman; Yulianto, Andik
Jurnal Ilmiah Komputasi Vol. 23 No. 4 (2024): Jurnal Ilmiah Komputasi : Vol. 23 No 4, Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.23.4.3659

Abstract

Sistem gerbang di Indonesia saat ini masih mengandalkan metode tradisional seperti gerbang manual atau teknologi RFID, yang memiliki keterbatasan dalam hal efisiensi dan keamanan. Penelitian ini bertujuan untuk mengembangkan solusi alternatif dengan menggabungkan teknologi text recognition berbasis machine learning dan kerangka kerja CRISP-DM. Metode yang digunakan melibatkan pendekatan multi-metode, yaitu metode terapan dan eksperimental. Metode terapan menggunakan kerangka kerja CRISP-DM untuk mengelola proyek, sementara metode eksperimental melibatkan pengujian model pada data yang dikumpulkan secara manual di lingkungan luar. Dataset yang digunakan adalah berjumlah 448 gambar yang dibagi kedalam tiga bagian berbeda yaitu train, validation, dan testing. Data plat nomor dikumpulkan secara manual dari lingkungan luar untuk mencerminkan kondisi kehidupan nyata, Algoritma yang diimplementasikan untuk mendeteksi plat nomor pada gambar kendaraan adalah algoritma YOLO V8. Sedangkan algoritma yang digunakan untuk text recognition adalah algoritma EasyOCR. Flask akan digunakan untuk mendistribusikan model secara berbasis web. Kerangka kerja CRISP-DM akan digunakan untuk memastikan proyek dapat selesai dilaksanakan. Pada bagian eksperimen, 100 gambar diuji untuk dapat mendapatkan perkiraan akurasi dari hasil sistem deteksi. Hasil pengujian menunjukkan bahwa model deteksi memiliki akurasi sekitar 99%, sementara text recognition mencapai akurasi sekitar 81%. Dengan memanfaatkan kerangka kerja CRISP-DM, kami berhasil mengembangkan sistem pendeteksi plat nomor berbasis web yang dapat memudahkan akses pengguna. Penelitian ini merupakan upaya untuk mengembangkan solusi alternatif untuk Sistem Gerbang Indonesia dengan mengembangkan machine-learning text recognition yang dikombinasikan dengan kerangka kerja CRISP-DM.
Development of an Integrated Chatbot on the Website Using IBM Watson Assistant Yulianto, Andik; Lau, Eric; Sabariman, Sabariman
INTEGER: Journal of Information Technology Vol 9, No 2: September 2024
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2024.v9i2.6525

Abstract

This research develops an integrated chatbot using IBM Watson Assistant to improve customer interaction on the Martindo Fine Foods website. The main problem addressed is the inefficiency and inconsistency of customer service responses. Using the Waterfall method, the study followed five systematic stages: requirements analysis, design, implementation, verification, and maintenance. The chatbot, featuring a hybrid navigation system, was evaluated using comprehensive Blackbox testing across 12 scenarios. With an accuracy of 91.67%, 11 scenarios succeeded, while 1 scenario failed due to typographical errors. Over one week, the chatbot successfully handled 50 out of 51 interactions, the results show that the chatbot significantly enhances response speed and reduces unanswered messages.
Evaluating YOLOv5 and YOLOv8: Advancements in Human Detection Ma Muriyah, Nimatul; Sim, Joel Hamim; Yulianto, Andik
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.944

Abstract

The YOLO (You Only Look Once) method is a state-of-the-art approach in real- time object detection, known for its high-speed image processing capabilities. Recently YOLO versions have differed in performance, particularly in terms of detection accuracy and computational efficiency. The objective of this study is to assess the effectiveness and performance of YOLOv5 and YOLOv8 in real-time human detection applications using the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology also. The dataset was processed through the Roboflow platform, which facilitated both the dataset management and the labeling process. Roboflow's tools streamlined the annotation of images, ensuring consistent labeling for deep learning model training and evaluation. F1 score, recall score, and precision score are compared both YOLOv5 and YOLOv8 to evaluate the performance of these architectures. The result of the evaluations shows that the performance of the YOLOv8 is better than the YOLOv5 which, YOLOv5 achieved F1-score equal 0.5865 (58%), recall score equal 0.83 (83%), and precision score of 0.4535 (45%). Meanwhile, YOLOv8 demonstrated better performance, with F1-score of 0.7921 (79%), recall score of 0.8289 (82%), and precision score of 0.7585 (75%). Base on the evaluations, we concluded that the performance of the YOLOv8 model is greater than the YOLOv5 model for Precision, and F1-Score, while YOLOv5 has slightly better score on recall. The contribution of this study is going to implemented into Audio guidance for the blind’s prototype that have been developing in previous study.
Penerapan Fuzzy Logic dalam Sistem Rekomendasi Film: Studi Kasus Justice League (2017) Leonardo, Kevin; Saputra, M. Abdilah; Ikhlas, Junior; Marbun, Ricky Yohannes; Anaztasya, Azra Putri; Yulianto, Andik; Deli, Deli
Telcomatics Vol. 9 No. 2 (2024)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v9i2.9517

Abstract

Currently, the development of technology encourages service provider sites in selling and renting to streaming movies, such as: IMDb, NetFlix, and Flixster to develop more accurate recommendation systems. This study uses fuzzy logic to provide movie recommendation information. Two similarity measurement methods are used to improve the accuracy of recommendations: first, by considering similar user choices, and second, by matching similar movie genres that have been rated by users. The fuzzy sets and membership functions used in this study are Critic Score, Audience Score, Audience Count, Year. The test results show that the application created can provide movie recommendations that match the dataset used.
Menyatukan Kreativitas dan Teknologi Proyek Pembuatan Website PT Berlian Batam Perkasa Tjua, Selina; Haeruddin, Haeruddin; Yulianto, Andik
Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Vol. 3 No. 1 (2024): Oktober 2024
Publisher : LPPM Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/madani.v3i1.9847

Abstract

Pembuatan website company profile untuk PT Berlian Batam Perkasa bertujuan untuk meningkatkan visibilitas dan kredibilitas perusahaan di era digital. Proyek ini menggunakan Content Management System (CMS) WordPress dan plugin Elementor, yang dipilih karena kemudahan penggunaannya dan kemampuannya untuk menghasilkan website yang responsif dan mudah dikelola. Metode yang diterapkan meliputi pengumpulan kebutuhan, desain, implementasi, pengujian, serta pemeliharaan. Hasil dari proyek ini adalah website yang memenuhi visi dan misi perusahaan serta memudahkan akses pelanggan terhadap informasi yang sebelumnya hanya tersedia melalui media fisik. Website ini juga meningkatkan brand awareness dan memperkuat posisi PT Berlian Batam Perkasa di pasar.
Perancangan dan Pengembangan Automatic Fish Feeder Menggunakan Aplikasi Mobile Blynk dan ESP32 Jeffrey, Jeffrey; Elvis, Elvis; Lau, Wilsen; Tham, Vincent; Yulianto, Andik
Telcomatics Vol. 9 No. 2 (2024)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v9i2.10077

Abstract

This research presents the design and development of an Internet of Things (IoT)-based Automatic Fish Feeder system using the Blynk platform to address common challenges in fish feeding management. The primary goal is to ensure consistent feeding schedules, minimize manual intervention, and provide remote control and monitoring capabilities. The system utilizes the ESP32 microcontroller integrated with ultrasonic sensors and servo motors to dispense feed accurately. Real-time data transmission is enabled via the Blynk Cloud, allowing users to schedule feeding times, monitor feed levels, and receive notifications when the feed stock is low. The methodology involves a multi-layer communication architecture: perception, data processing, communication, and application layers. Ultrasonic sensors calculate the remaining feed stock, while servo motors execute precise feeding commands. Users can interact through a user-friendly Blynk interface that visualizes feed levels, logs feeding history, and supports customizable schedules. The system also sends real-time alerts to ensure proactive management. The implementation successfully reduces manual feeding tasks, mitigates overfeeding risks, and enhances feed efficiency. This innovative approach supports sustainable aquaculture practices, promoting healthier fish growth for hobbyists and commercial breeders alike. Results demonstrate high reliability and user satisfaction, paving the way for future smart aquaculture solutions.
PERFORMANCE EVALUATION OF LIGHTWEIGHT OBJECT DETECTION MODELS FOR REAL-TIME PERSONAL PROTECTIVE EQUIPMENT DETECTION IN THE CONSTRUCTION SITES Herman; Dion, Sandy Alferro; Yulianto, Andik
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9896

Abstract

The environment of construction industry was known to have a high risk and high number of occupational accidents and injuries. One of the main causes of the occurrences was the construction workers' negligence in wearing personal protection equipment. Computer vision-based approaches were developed to assist in personal protective equipment adherence to address this issue. Using lightweight machine learning algorithms, object recognition can help to detect if the PPEs are worn correctly. We evaluated performance of YOLOv8-Nano and YOLOv9-Tiny (state of the art lightweight object detection models). Custom dataset was used for training the models and then metrics like F1 score, precision, recall mAP50 and mAP50-95 were used to evaluate both models’ performance. Results found that both models were able to show promising real time detections, but the YOLOv9-Tiny model was able to outperform the YOLOv8-Nano model on many evaluation metrics. Specifically, in terms of mAP, YOLOv8-Nano achieved an mAP50 of 81.48, while YOLOv9-Tiny attained a slightly higher mAP50 of 82.70. Higher efficiency in these parameters will help small industry to enforce PPE adherence monitoring using edge device at a relatively low cost. Lastly, enhanced enforcement of PPE regulations through automated detection system can contribute to improve workplace safety which in turns will lead to less injuries.   Keywords: Object Recognition, Computer Vision, Machine Learning, Lightweight, Personal Protective Equipment, YOLO
Co-Authors A.A. Ketut Agung Cahyawan W Abay, Margita Rahayu Adelia Anju Asmara Adelia Anju Asmara Agung Nugroho Adi, Agung Nugroho Aji Wilaksono, Aji Aldri Frinaldi Amilia Amilia Anaztasya, Azra Putri Andi Andi Andreas, Willy Anisah Hasna Jauharoh Anthony Any Juliani, Any Aripradono, Heru Wijayanto Arlina, Dilla Awaluddin Nurmiyanto, Awaluddin Billy Ardi, Billy Chandra Wijaya, Kevin Christian, Yefta Danang Wahyu Widodo Darojat, Irfa Davis Willyam, Davis Deli, Deli Delvira Jayatri Prasasti, Delvira Jayatri Dewi Wulandari Dhandhun Wacano Dilla Arlina Dion, Sandy Alferro Elvis, Elvis Hadi Hadi Haeruddin Haeruddin Herlica, Inne Herman Herto Dwi Arisyady, Herto Hervian Lanang Priyambodo, Hervian Lanang Hu dori, Hu Hudori Hudori Ikhlas, Junior Indah Purwaningsih Irawan, Ferdy Jason Jeffrey ., Jeffrey Jesson, Jesson Kevin kevin Khomali, Carlos Justin Lau, Eric Lau, Wilsen Lee, Lesley Peterson Leonardo, Kevin Lie, Melvin Lie, Steven Lim, Louis Lim, Stephani Lius, Kevin Marbun, Ricky Yohannes Mardya Ning Tyas Margita Rahayu Abay Marisa Handayani Maulana, Azhar Melvin, Melvin Meriana, Angelina Mistoro, Niesa Hanum Muriyah, Nimatul Ma Nimatul Mamuriyah Paerin, Paerin Pelawi, Jan Putra Bahtra Agung S Pratama, Adi Nuzul Pravitasari, Vidya Ayu Prayatni Soewondo Prihat maji, Prihat Rahman, M Abdur Rahmawati, Suphia Rinaldo, Rinaldo Sabariman Sabariman Sabariman Sak, Erwin Sama, Hendi Saputra, M. Abdilah Selina, Selina Setijawan, Wawan sherly sherly Siahaan, Mangapul Sim, Joel Hamim Simanjuntak, Fredian Simanjuntak, Noe Prihartoyo Sopiyan, Sopiyan Stelyven, Stelyven Stephen Suphia Rahmawati Taai, Derwin Tham, Vincent Tiffano Miracle Gaghana, Dave Tjua, Selina Trianes, Agustian Utomo, Kevin Saputra Wacano, Dhandhun Wantoputri, Noviani Ima Wenky, Wenky Wilson Wilson Yeo, Stefan Yulianto P., Yulianto