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All Journal International Journal of Electrical and Computer Engineering E-Dimas: Jurnal Pengabdian kepada Masyarakat JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal ICT : Information Communication & Technology JATI (Jurnal Mahasiswa Teknik Informatika) E-Link: Jurnal Teknik Elektro dan Informatika SKANIKA: Sistem Komputer dan Teknik Informatika Djtechno: Jurnal Teknologi Informasi International Journal Software Engineering and Computer Science (IJSECS) Jurnal Sains Terapan : Wahana Informasi dan Alih Teknologi Pertanian PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Teknologi dan Manajemen Industri Terapan JUSIFOR : Jurnal Sistem Informasi dan Informatika Informasi interaktif : jurnal informatika dan teknologi informasi
Gema Parasti Mindara
Program Studi Teknologi Rekayasa Komputer, Sekolah Vokasi IPB
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Veterinary

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Pengujian Black Box pada Website Lums Creative dengan Teknik Boundary Value Analysis Athala Fazli Maula; Muhammad Mahardicka Alfattah Zelda; Rafi Muhammad Rusydan; Maulana Zulfan Azka; Aditya Wicaksono; Gema Parasti Mindara
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 5 No 1 (2026): JUSIFOR - Juni 2026
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v5i1.8523

Abstract

Lums Creative merupakan sebuah website yang menyediakan layanan kreatif digital dengan berbagai fitur untuk mengelola layanan, portofolio, klien, ulasan, hingga proyek. Untuk memastikan kualitas fungsionalitas serta konsistensi respons pada setiap fitur, dilakukan pengujian menggunakan metode Black Box Testing dengan teknik Boundary Value Analysis (BVA). Teknik ini digunakan untuk mengevaluasi perilaku sistem pada nilai batas minimum, maksimum, serta nilai di luar batas pada setiap field input. Pengujian dilakukan pada enam fitur utama, yaitu Service, Portofolio, Client, Review, Create New Project, dan Edit Profile. Setiap fitur diuji berdasarkan validasi teks, pemilihan opsi, format input, serta batas ukuran file. Hasil pengujian menunjukkan bahwa seluruh fitur telah memproses input sesuai aturan yang ditetapkan, di mana sistem mampu menerima data pada nilai batas valid dan menolak input yang melampaui batas atau tidak memenuhi syarat. Penerapan teknik BVA pada seluruh fitur terbukti efektif dalam mengidentifikasi potensi kesalahan fungsional, sehingga memastikan bahwa website bekerja secara konsisten sesuai kebutuhan pengguna.
Implementation of the Waterfall Method in the Lalungguh Ecoprint Website Dini Nurul Azizah; Raisa Mutia Thahir; Luthfi Dika Chandra; Muhammad Naufal Ardhani; Aditya Wicaksono; Gema Parasti Mindara
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 1 (2025): Jurnal Teknologi dan Open Source, June 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i1.4412

Abstract

The rapid development of the digital era has encouraged MSME (Micro, Small, and Medium Enterprises) owners to adopt technology to enhance business efficiency and effectiveness. Lalungguh Ecoprint, an MSME engaged in sustainable fashion through the use of natural-based ecoprint techniques, still encountered obstacles in product promotion and manual financial record-keeping. This study aimed to develop a website that integrates product catalog management with financial recording into a unified, more efficient system. The development process employed the Waterfall method to ensure a structured and systematic workflow. Laravel was chosen as the primary framework due to its support for the Model-View-Controller (MVC) architecture, which simplifies code organization and modular feature development. MySQL was utilized as the database management system for its reliability in managing complex data storage. The resulting website enables real-time, centralized management of product and financial data and is accessible across multiple devices. This system is expected to enhance operational efficiency, streamline business activities, and broaden Lalungguh Ecoprint’s marketing reach through a digital platform.
Design and Development of an E-Commerce Website Using the Waterfall Method with the Laravel Framework Gema Parasti Mindara; Aisya Tyanafisya; Siti Farah Fakhirah; Azhar Nadhif Annaufal; Ibnu Aqil Mahendar; Aditya Wicaksono
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4570

Abstract

The e-commerce sector has experienced significant growth in Indonesia in recent years. However, many small business owners still rely on manual operations through social media platforms. This study focuses on the design and implementation of an e-commerce website for Comot Langsung, a local thrifting business, using the Waterfall methodology and the Laravel framework. The sequential nature of the Waterfall method is applied through six phases: requirement analysis, system design, development, testing, deployment, and ongoing maintenance. In the analysis phase, several key features were identified, including user registration, product catalog, shopping cart, ordering system, and QRIS payment integration. The design process utilized UML diagrams to clearly and structurally visualize the system architecture and user flow. The results show that all features were successfully implemented, offering high responsiveness and ease of navigation. This website is expected to expand market reach for thrifting entrepreneurs while enhancing the online shopping experience for consumers in selecting and purchasing vintage fashion products efficiently and conveniently.
PENGUJIAN PADA WEBSITE SMARTPETSCARE UNTUK LAYANAN GROOMING HEWAN MENGGUNAKAN METODE BLACK BOX TESTING Nur Rahma Ditta Zahra; Anatasya Wenita Putri; Kanaya Sabila Azzahra; David Reza Widhiwipati; Muhammad Ilham Nurfajri; Gema Parasti Mindara; Aditya Wicaksono
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12299

Abstract

Penelitian ini bertujuan untuk menguji fungsionalitas sistem berbasis web SmartPetsCare, yang dirancang untuk mendukung layanan grooming hewan peliharaan secara online. Website ini menyediakan berbagai fitur, seperti pendaftaran hewan peliharaan, pengaturan jadwal layanan, pelacakan riwayat grooming, serta akses informasi melalui artikel, tips perawatan, dan showcase produk. Pendekatan Black Box Testing digunakan untuk menguji fungsi-fungsi utama sistem berdasarkan spesifikasi kebutuhan pengguna, tanpa mengevaluasi struktur internal atau kode programnya. Pengujian dilakukan pada fitur login, registrasi, serta operasi CRUD (Create, Read, Update, Delete) untuk memastikan setiap fungsi berjalan sesuai harapan. Hasil pengujian menunjukkan bahwa fitur-fitur utama website beroperasi sesuai spesifikasi yang ditentukan. Semua skenario pengujian berhasil memberikan hasil yang diharapkan, meskipun terdapat beberapa peluang perbaikan, seperti optimalisasi antarmuka pengguna dan pengayaan fitur tambahan untuk meningkatkan kualitas pengalaman pengguna. Penelitian ini diharapkan dapat menjadi referensi dalam pengujian dan pengembangan perangkat lunak berbasis web, khususnya dengan penerapan metode Black Box Testing untuk memastikan keandalan sistem.
People Counting in Sample Video Footage Using CNN Integrated with YOLOv5 Ahmad Hasan Faqih Aulia; Carissa Fathinah Balti; Keisyah Zahra Anatasya; Gema Parasti Mindara; Endang Purnama Giri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1933

Abstract

Accurate people counting in dynamic environments remains challenging due to variations in lighting, complex backgrounds, and occlusion. This study proposes a video-based people counting system leveraging a Convolutional Neural Network (CNN) integrated with the YOLOv5 object detection model. The system applies a structured preprocessing pipeline, including frame extraction, normalization, and noise reduction, to enhance data consistency before detection. The model was evaluated using ten real-world campus video sequences to assess detection reliability and counting accuracy. Experimental results demonstrate that the proposed method achieves high precision and recall for real-time detection across diverse scenarios. Performance degradation was observed in frames containing dense crowds or low illumination, indicating limitations under extreme conditions. These findings validate the feasibility of lightweight CNN-based detectors for surveillance and monitoring applications, while highlighting the need for larger datasets and optimized training strategies to improve robustness in more complex environments.
PEMBUATAN PLATFORM DIGITAL UNTUK EDUKASI DAN E-COMMERCE HIDROPONIK BERBASIS BUSINESS INTELLIGENCE: STUDI KASUS HYDROSPACE Nurrizkyta Aulia Hanifah; Muhammad Aqil Musthafa Arrachman Musthafa Arrachman; Muhammad Fillah Al Fatih; Nasywa Shafa Salsabila; Gema Parasti Mindara; Aditya Wicaksono
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.6501

Abstract

Urban farming has become one of the solutions to address limited land availability in cities, with hydroponics being an effective method. However, the low literacy level of the public regarding hydroponics hinders the adoption of this technology. This research aims to develop a digital platform, HydroSpace, which integrates hydroponic education and e-commerce services to facilitate the public's access to information and hydroponic supplies. The Waterfall method was used in the platform's development, focusing on educational features in the form of video tutorials, a hydroponic product marketplace, and a Business Intelligence (BI) system for user data analysis. Data was collected through platform testing with various users, and the results show that HydroSpace effectively improved users' understanding of hydroponics and facilitated the purchase of hydroponic supplies. The conclusion of this research is that HydroSpace can be an efficient solution to enhance hydroponic literacy and support sustainable urban farming.
PERBANDINGAN GAUSSIAN BLUR, MEDIAN, DAN BILATERAL FILTER UNTUK REDUKSI NOISE CITRA DIGITAL Vellisya Afifa Qonita; Keisha Ramadhani; Dwi Febriyanti; Muthiah Hamidah; Achmad Fauzal Khobir; Endang Purnama Giri; Gema Parasti Mindara
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 13 No. 1 (2026): Prosisko Vol. 13 No. 1 Maret 2026
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/prosisko.v13i1.11556

Abstract

Reduksi noise merupakan tahapan krusial dalam pengolahan citra digital. Hal ini karena reduksi noise dapat menurunkan kualitas visual dan akurasi analisis citra. Permasalahan utama dalam reduksi noise adalah memilih metode filtering paling efektif untuk jenis noise tertentu dengan tetap mempertahankan detail dan tepi objek. Penelitian ini bertujuan untuk membandingkan efektivitas Gaussian Blur, Median Filter, dan Bilateral Filter dalam mereduksi Gaussian noise dan salt and pepper noise, serta mengevaluasi kualitas visual citra hasil filter melalui penilaian subjektif. Metode pada penelitian ini adalah eksperimen kuantitatif dan kualitatif, dimana citra uji (grayscale) diolah dengan ketiga filter dan diukur menggunakan tiga metrik objektif yaitu Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), dan Structural Similarity Index (SSIM). Kemudian penelitian dilengkapi dengan survei penilaian visual oleh responden.
PERBANDINGAN KINERJA ALGORITMA KNN DAN SVM DALAM KLASIFIKASI KEMATANGAN BUAH JERUK MEDAN BERDASARKAN CITRA DIGITAL Fadilla Julianifa Putri; Siti Laila Nurjannah; Dwi Febrina Wati; Silvia Ariani Daulay; Indira Sistamarien; Endang Purnama Giri; Gema Parasti Mindara
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 9 No 1 (2026): Jurnal SKANIKA Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v9i1.3661

Abstract

As a regional flagship commodity with a promising selling value, the process of grouping the maturity level of Medan Orange is still dominated by manual visual techniques. This often triggers data inconsistency and requires a long duration of processing due to personnel subjectivity factors. This research aims to compare the performance of two machine learning algorithms, namely KNN and SVM, in classifying the maturity level of Medan Orange fruit based on digital images. The dataset used is a primary dataset collected directly from Medan Orange farmers in field conditions. The research stages include image acquisition, pre-processing, extraction of HSV-based color features and GLCM-based textures, as well as classification of maturity levels into three classes, namely raw, semi-cooked, and mature. The performance of both algorithms is evaluated using accuracy, precision, and recall metrics. The research results show that the KNN algorithm has a superior performance compared to SVM, with an accuracy rate of 96,25%, while SVM produces an accuracy of 91,25%. This result shows that KNN is effective and more suitable to be applied to the automation system of classification of the maturity of Medan Orange fruit based on digital images.
IMPLEMENTASI HOUGH CIRCLE TRANSFORM DAN ORB UNTUK DETEKSI KLASIFIKASI NOMINAL KOIN RUPIAH Maulana Zulfan Azka; Hanin Putri Sholiha; Syahna Aulia Putri; Muhammad Mahardicka Alfattah Zelda; Endang Purnama Giri; Gema Parasti Mindara
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 11 No 2 (2026): Jurnal Informasi Interaktif
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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

Abstract

Manual coin counting and classification in high-volume transactions are often inefficient and prone to human error. In computer vision implementations, the primary challenges in coin detection are lighting variations and changes in image scale, rendering conventional area-based methods inaccurate. This study aims to develop a coin detection system robust to changes in camera distance and lighting conditions. The proposed method combines the Hough Circle Transform algorithm for detecting geometric coin locations and ORB (Oriented FAST and Rotated BRIEF) for classifying denominations based on surface texture feature matching. The system is equipped with an adaptive learning mechanism (Human-in-the-Loop), allowing users to interactively train the system upon encountering new coin variants or unrecognized coins. Test results indicate that the combination of CLAHE (Contrast-Limited Adaptive Histogram Equalization) pre-processing and Hough detection successfully isolates overlapping circular objects, while the feature matching method effectively distinguishes coin denominations with similar diameters but distinct textures. It is concluded that integrating texture analysis with user manual correction features significantly enhances system accuracy and flexibility compared to static contour-based detection methods.
Co-Authors Achmad Fauzal Khobir Aditya Wicaksono Ahmad Hasan Faqih Aulia Aisya Tyanafisya Anatasya Wenita Putri Andy Pramurjadi Anggito Rangkuti Bagas Muzaqi Anifatul Faricha Anka Luffi Ramdani Athala Fazli Maula Azhar Nadhif Annaufal Capriandika Putra Susanto Carissa Fathinah Balti Citra Lestari Mindara David Reza Widhiwipati Dini Nurul Azizah Dwi Febrina Wati Dwi Febriyanti Endang Purnama Giri Fachri Aldin Fansuri Fadilla Julianifa Putri Fami, Amata Fauzi Adi Saputra Fifi Novianti Gany Andisa Geni Rahmah Putri Hanin Putri Sholiha Harvini Al Meitavia Husna Alfiani Ibnu Aqil Mahendar Indira Sistamarien Inna Novianty Inna Novianty Jonathan Cristiano Rabika Jonser Steven Rajali Manik Kanaya Sabila Azzahra Keisha Ramadhani Keisyah Zahra Anatasya Luthfi Dika Chandra Marsya Halya Alfrida Maulana Zulfan Azka Maulana Zulfan Azka Mia Putri Yeza Muhamad Rafif Fadhillah Muhammad Achirul Nanda Muhammad Aqil Musthafa Arrachman Musthafa Arrachman Muhammad Fillah Al Fatih Muhammad Ilham Nurfajri Muhammad Mahardicka Alfattah Zelda Muhammad Mahardicka Alfattah Zelda Muhammad Naufal Ardhani Muthiah Hamidah Nasywa Shafa Salsabila Nur Iman Nugraha Nur Indah Chasanah Nur Rahma Ditta Zahra Nurrizkyta Aulia Hanifah Nurulhaq, Muhammad Iqbal Pradeka Brilyan Purwandoko Rafi Muhammad Rusydan Raisa Mutia Thahir Rajhaga Jevanya Meliala Rismen Sinambela Rivanka Marsha Adzani Sholihah, Walidatush Silvia Ariani Daulay Siti Farah Fakhirah Siti Laila Nurjannah Sofiyanti Indriasari Syahna Aulia Putri Thoriq Muhammad Pasya Tuti Hartati Vellisya Afifa Qonita