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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar JURNAL PENDIDIKAN TAMBUSAI Jurnal Teknologi Informasi dan Pendidikan Community Empowerment Afeksi: Jurnal Penelitian dan Evaluasi Pendidikan Tsaqofah: Jurnal Penelitian Guru Indonesia Journal of Artificial Intelligence and Digital Business JPNM : Jurnal Pustaka Nusantara Multidisiplin Jurnal Teknik Komputer dan Informatika (JTeKI) Journal of Authentic Research Jurnal Publikasi Manajemen Informatika
Asmara, Delvi
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Religion Arts Humanities Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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RANCANG BANGUN MEDIA PEMBELAJARAN AUGMENTED REALITY PADA MATERI HARDWARE KOMPUTER DI SMK MUHAMMADIYAH 1 PADANG Prastanti, Cinta Bening; Asmara, Delvi; Irfan, Dedy; Samala, Agariadne Dwinggo
Jurnal Publikasi Manajemen Informatika Vol. 5 No. 3 (2026): JURNAL PUBLIKASI MANAJEMEN INFORMATIKA
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupumi.v5i3.7819

Abstract

Computer hardware learning in vocational high schools is often constrained by limited practicum equipment, restricting students' access to hardware components, while conventional media further limit independent study. This study aimed to develop an Augmented Reality (AR)-based learning medium for computer hardware material, integrating three-dimensional visualization, a gamified assessment, and an anti-tab-switching mechanism to support assessment integrity. The study employed the Research and Development (R&D) method using the 4D model (Define, Design, Develop, Disseminate), with the Disseminate stage limited to a small-scale practicality trial. The AR application was developed using Unity 3D, Blender, and Vuforia SDK with marker-based tracking to visualize the motherboard, processor, RAM, hard disk, power supply, and VGA card. Product validity was assessed by three media experts and three material experts using Likert-scale instruments, while practicality was evaluated through a questionnaire administered to 10 students from a population of 20 Grade X Computer and Network Engineering students at SMK Muhammadiyah 1 Padang. The results showed media validity of 91.25%, material validity of 93.81%, and practicality of 94%, each categorized as very valid or very practical. These findings indicate that the developed AR-based media is feasible and practical for interactive, independent hardware learning while maintaining assessment integrity.
Rancang Bangun Aplikasi Reservasi Wisata Air Terjun Lubuk Hitam Bungus dengan Penerapan Algoritma Neural Networks dan Fitur Barcode Digital Mahendra, Jimmy; Hendriyani, Yeka; Asmara, Delvi; Fatmi, Yulia
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/2ap08p90

Abstract

Penelitian ini bertujuan untuk merancang dan membangun aplikasi reservasi wisata pada objek wisata Air Terjun Lubuk Hitam Bungus berbasis Android dengan memanfaatkan teknologi WebView sebagai solusi atas masih digunakannya sistem reservasi manual yang menyebabkan antrean panjang, kesalahan pencatatan data, dan keterbatasan pengelolaan informasi pengunjung. Aplikasi yang dikembangkan mengintegrasikan algoritma Neural Network sebagai modul analitik untuk memprediksi jumlah kunjungan wisatawan berdasarkan data historis serta fitur barcode digital sebagai media validasi tiket elektronik. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan model pengembangan Waterfall yang meliputi analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan pemeliharaan. Data prediksi menggunakan 36 data historis kunjungan periode Januari 2022–Desember 2024 yang diproses melalui tahap pembersihan data, normalisasi, pelatihan model, dan pengujian. Hasil penelitian menunjukkan bahwa aplikasi berhasil menyediakan fitur registrasi pengguna, pemesanan tiket daring, pembayaran, penerbitan e-ticket berbasis QR Code, dashboard admin, serta modul prediksi kunjungan. Pengujian Black Box Testing pada 9 fitur utama menunjukkan seluruh fungsi berjalan sesuai skenario uji dengan tingkat keberhasilan 100%. Evaluasi model prediksi menghasilkan Mean Absolute Error (MAE) sebesar 12,4 pengunjung, Mean Squared Error (MSE) sebesar 245,6, dan akurasi prediksi sebesar 87,3%. Uji usability terhadap 10 responden memperoleh nilai rata-rata 4,4 dari skala 5 yang menunjukkan aplikasi mudah digunakan dan diterima dengan baik. Implementasi sistem ini mengindikasikan bahwa digitalisasi layanan wisata berpotensi meningkatkan efisiensi reservasi, mempercepat validasi tiket, serta mendukung pengelolaan data kunjungan secara lebih terstruktur. Dengan demikian, aplikasi yang dikembangkan dapat menjadi alternatif solusi dalam mendukung transformasi digital sektor pariwisata menuju konsep smart tourism yang lebih efektif, adaptif, dan berbasis data. This study aims to design and develop a tourism reservation application for the Lubuk Hitam Bungus Waterfall tourist attraction based on Android by utilizing WebView technology as a solution to the continued use of manual reservation systems that cause long queues, data recording errors, and limitations in managing visitor information. The developed application integrates a Neural Network algorithm as an analytical module to predict tourist visit numbers based on historical data, as well as a digital barcode feature as an electronic ticket validation medium. The research method used was Research and Development (R&D) with the Waterfall development model, which includes requirements analysis, system design, implementation, testing, and maintenance. Prediction data used 36 historical visitation records from January 2022 to December 2024, processed through data cleaning, normalization, model training, and testing stages. The results show that the application successfully provides user registration, online ticket booking, payment, QR Code-based e-ticket issuance, admin dashboard, and visit prediction modules. Black Box Testing on 9 main features showed that all functions operated according to test scenarios with a 100% success rate. Evaluation of the prediction model produced a Mean Absolute Error (MAE) of 12.4 visitors, a Mean Squared Error (MSE) of 245.6, and a prediction accuracy of 87.3%. Usability testing involving 10 respondents obtained an average score of 4.4 out of 5, indicating that the application is easy to use and well accepted by users. The implementation of this system indicates that the digitalization of tourism services has the potential to improve reservation efficiency, accelerate ticket validation, and support more structured visitor data management. Therefore, the developed application can serve as an alternative solution to support the digital transformation of the tourism sector toward a smarter, more adaptive, and data-driven smart tourism concept.
Perancangan Sistem Rekomendasi Pemilihan Mobil Bekas Kategori MPV dan City Car Menggunakan K-Nearest Neighbor (K-NN) dengan Hybrid Filtering Amin, Rudi Kurnia Al; Hendriyani, Yeka; Asmara, Delvi; Fatmi, Yulia
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/qrfc5h79

Abstract

Perkembangan kebutuhan transportasi pribadi di Indonesia menunjukkan tren yang terus meningkat, terutama di wilayah perkotaan. Di Kota Padang, meningkatnya kebutuhan tersebut diikuti oleh semakin banyaknya pilihan mobil bekas kategori MPV dan City Car, namun banyaknya alternatif pilihan ini justru menimbulkan information overload bagi calon pembeli. Penelitian ini bertujuan merancang dan mengimplementasikan sistem rekomendasi berbasis website menggunakan metode K-Nearest Neighbor (K-NN) dengan pendekatan Hybrid Filtering. Metode pengembangan sistem yang diterapkan adalah model Waterfall. Pendekatan Hybrid Filtering menggabungkan Content-Based Filtering dan Collaborative Filtering, sementara algoritma K-NN digunakan untuk menghitung tingkat kemiripan antar data kendaraan berdasarkan atribut seperti harga, tahun produksi, dan spesifikasi teknis menggunakan Euclidean Distance. Sistem juga menerapkan mekanisme pre-filtering berdasarkan kategori kendaraan untuk mengurangi kompleksitas perhitungan KNN agar sistem tetap responsif. Hasil pengujian fungsional menggunakan Black Box Testing menunjukkan seluruh fitur sistem berjalan dengan baik. Pengujian akurasi menghasilkan nilai Precision rata-rata sebesar 0,78, Recall 0,83, dan Mean Absolute Error (MAE) sebesar 0,15. Simpulannya, sistem ini mampu memberikan rekomendasi yang akurat, relevan, serta membantu mempercepat proses pengambilan keputusan calon pembeli mobil bekas. The development of private transportation needs in Indonesia shows a continuously increasing trend, especially in urban areas. In Padang City, this growth is followed by various used car options in the MPV and City Car categories, yet these alternatives cause information overload for potential buyers. This research aims to design and implement a web-based recommendation system using the K-Nearest Neighbor (K-NN) method with a Hybrid Filtering approach. The system development method applied is the Waterfall model. The Hybrid Filtering approach combines Content-Based Filtering and Collaborative Filtering, while the K-NN algorithm calculates similarity levels between vehicle data based on attributes such as price, production year, and technical specifications using Euclidean Distance. The system also applies a pre-filtering mechanism based on vehicle categories to reduce K-NN computational complexity and maintain responsiveness. Functional testing results using Black Box Testing indicate that all system features operate correctly. Accuracy testing produced an average Precision value of 0.78, a Recall of 0.83, and a Mean Absolute Error (MAE) of 0.15. In conclusion, this system provides accurate and relevant recommendations, helping potential used car buyers accelerate their decision-making process.
Implementasi MobileNetV2 dengan Teknik Augmentasi Data untuk Klasifikasi Penyakit Daun Cabai Berbasis Website Ali, Muhammad Irzan; Asmara, Delvi; Hadi, Ahmaddul; Budayawan, Khairi
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/txr3y475

Abstract

Penelitian ini bertujuan mengembangkan model klasifikasi penyakit daun cabai berbasis MobileNetV2 yang diintegrasikan ke dalam prototipe website sebagai alat bantu diagnosis awal. Permasalahan utama yang diangkat adalah kemiripan gejala visual antarpenyakit daun cabai, keterbatasan identifikasi manual, dan kebutuhan model yang ringan untuk implementasi praktis. Dataset terdiri atas 500 citra awal dari lima kelas, yaitu daun sehat, daun keriting, daun kuning, bercak daun, dan embun tepung. Data diperluas melalui augmentasi rotasi, shear, zoom, dan horizontal flip sehingga diperoleh 2.200 citra, kemudian dibagi menjadi data latih 80%, validasi 10%, dan uji 10%. Model dilatih menggunakan arsitektur MobileNetV2 dengan optimizer Adam, batch size 32, dan 20 epoch. Hasil menunjukkan bahwa augmentasi data meningkatkan akurasi model dari 74,00% menjadi 99,09%. Pada data uji, model mencapai akurasi 98,64% dengan loss 0,0363. Classification report memperlihatkan performa tinggi pada seluruh kelas, meskipun masih terdapat kesalahan minor pada kelas daun keriting dan embun tepung. Sistem berbasis website juga berhasil menjalankan fungsi registrasi, login, unggah citra, klasifikasi, konsultasi AI, dan profil pengguna melalui pengujian black-box. Secara kritis, hasil ini menunjukkan potensi MobileNetV2 sebagai model efisien untuk klasifikasi penyakit daun cabai, namun validasi eksternal pada kondisi lapangan yang lebih beragam tetap diperlukan sebelum sistem digunakan sebagai alat diagnosis pertanian berskala luas. This study aims to develop a MobileNetV2-based chili leaf disease classification model integrated into a website prototype as an early diagnostic support tool. The central problem concerns the visual similarity among chili leaf disease symptoms, the limitations of manual identification, and the need for a lightweight model suitable for practical deployment. The dataset consisted of 500 original images from five classes, namely healthy leaf, curly leaf, yellow leaf, leaf spot, and powdery mildew. Data augmentation using rotation, shear, zoom, and horizontal flipping expanded the dataset to 2,200 images, which were divided into 80% training, 10% validation, and 10% testing subsets. The model was trained using the MobileNetV2 architecture with the Adam optimizer, a batch size of 32, and 20 epochs. The results show that data augmentation improved model accuracy from 74.00% to 99.09%. On the test set, the model achieved 98.64% accuracy with a loss value of 0.0363. The classification report indicates strong performance across all classes, although minor misclassifications were found in curly leaf and powdery mildew classes. The web-based system also successfully supported registration, login, image upload, classification, AI consultation, and user profile functions through black-box testing. Critically, these findings demonstrate the potential of MobileNetV2 as an efficient model for chili leaf disease classification, but external validation under more diverse field conditions is still necessary before the system can be used as a large-scale agricultural diagnostic tool.
Pengaruh Artificial Intelligence (AI) terhadap Literasi Digital Belajar Peserta Didik di SMK Negeri 2 Padang Farizy, Muhammad Habbil Al; Asmara, Delvi; Huda, Yasdinul; Sriwahyuni, Titi
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/1t6zed54

Abstract

Perkembangan era digital dan Revolusi Industri 4.0 telah mendorong integrasi teknologi dalam pendidikan, namun tantangan literasi digital peserta didik masih menjadi masalah serius, seperti rendahnya kemampuan verifikasi informasi, kurangnya kesadaran keamanan digital, serta belum konsistennya capaian literasi digital di SMK Negeri 2 Padang. Penelitian ini bertujuan untuk menganalisis pengaruh Artificial Intelligence (AI) terhadap literasi digital belajar peserta didik di SMK Negeri 2 Padang. Metode yang digunakan adalah mixed methods dengan desain sekuensial eksploratori. Teknik pengumpulan data dilakukan melalui wawancara mendalam kepada 5 siswa dan 2 guru, observasi partisipatif selama 2 minggu, serta kuesioner skala Likert 1-5 yang disebarkan kepada 225 responden yang diambil menggunakan teknik simple random sampling dari populasi 522 siswa kelas XI. Teknik analisis data meliputi analisis regresi linier sederhana, uji asumsi klasik (normalitas, linearitas, heteroskedastisitas), serta uji hipotesis (uji t, uji F, dan koefisien determinasi) dengan bantuan SPSS versi 26. Hasil penelitian menunjukkan bahwa AI berpengaruh positif dan signifikan terhadap literasi digital (t-hitung 42,317 > t-tabel 1,970; Sig. 0,000 < 0,05), dengan koefisien determinasi (R Square) sebesar 0,889 dan nilai korelasi (R) 0,943 yang mengindikasikan hubungan sangat kuat. Pembahasan mengungkap bahwa kontribusi AI tertinggi pada aspek digital skill, namun aspek digital ethics dan digital safety masih memerlukan perhatian. Kesimpulannya, AI berpengaruh signifikan terhadap literasi digital peserta didik. Implikasi penelitian ini adalah bahwa pemanfaatan AI yang terintegrasi dalam pembelajaran dapat menjadi strategi efektif untuk mengembangkan literasi digital, namun perlu disertai penguatan etika dan keamanan digital serta pengawasan dari guru.
PERANCANGAN SISTEM STOCK OPNAME BERBASIS WEB PADA KAFE KOPKIT Zahelna Azzahra, Karisa; Irfan, Dedy; Dwinggo Samala, Agariadne; Asmara, Delvi
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 Nomor 03, September 2026 Publish
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.62500

Abstract

Stock opname activities at Kafe Kopkit, a food and beverage business operating eight outlets, are still recorded manually using paper-based logbooks, which causes discrepancies between physical and system stock, delays in reporting, and difficulty for management in monitoring the completion of stock opname across outlets, particularly because most outlets operate for twenty-four hours. This study aims to design and build an integrated web-based stock opname information system that supports real-time monitoring and provides an objective performance ranking of outlets to support managerial decision making. The system was developed using the Prototype method, which allows iterative refinement based on feedback from five user roles (Owner, Operational Management, Outlet Management, Kitchen, and Bar), and was verified functionally using Black Box Testing. To rank outlet performance, the system implements the Simple Additive Weighting method using four criteria: stock discrepancy rate, stock opname completion percentage, stock opname frequency, and completion timeliness. Black box testing on twelve functional scenarios produced a one hundred percent valid result, and the Simple Additive Weighting calculation successfully differentiated and ranked eight simulated outlets consistently with their input performance data. The system is expected to reduce recording errors, accelerate cross-outlet monitoring, and provide a transparent, data-driven basis for evaluating outlet performance.
RANCANG BANGUN SISTEM INVENTARIS ASET SEKOLAH BERBASIS WEB DI SMK N 6 PADANG TERINTEGRASI QR-CODE Sabrina, Mutiara; Asmara, Delvi; Dwinggo Samala, Agariadne; Irfan, Dedy
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 Nomer 03, September 2026 Publication
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.64038

Abstract

School asset inventory management at SMK Negeri 6 Padang is still carried out conventionally, so that data recording, searching, borrowing, and reporting require a relatively long time and are prone to recording errors. The absence of a physical asset-tracking mechanism and a systematic record of user activity has also made asset supervision less than optimal. This study aims to design and build a web-based school asset inventory system equipped with multi-access, QR Code, and digital audit features at SMK Negeri 6 Padang. The system was developed using the Software Development Life Cycle (SDLC) with the Waterfall model, covering requirement analysis, system design, implementation, testing, deployment, and maintenance, and was built using the Laravel framework with a MySQL database, while functional testing was carried out through Black Box Testing. The results show that the system simplifies asset data recording, location management, borrowing and return transactions, QR Code-based asset tracking, digital audit trails of user activity, and the preparation of inventory reports more quickly and accurately. Black Box Testing results indicate that all 53 functions across five user roles operate as expected without functional errors, achieving a 100% success rate, so that the system is considered feasible to be implemented as a medium for managing school asset inventory at SMK Negeri 6 Padang.
Co-Authors Adam, Al Agariadne Dwinggo Samala Ahmaddul Hadi, Ahmaddul Ali, Muhammad Irzan Amin, Rudi Kurnia Al Andini, Vina Fitri Arizqa, Tifani Putri Budayawan, Khairi Chintia Ningsih, Nur Dalifa, Mikola Dedy Irfan Dony Novaliendry Edidas , Edidas Elfi Tasrif Erdisna, Erdisna Farizy, Muhammad Habbil Al Fatmi, Yulia Geovanne Farell Gusra, Laura Febriani Hasibuan, Kholid Huda, Yasdinul Ika Parma Dewi Irma Delianti, Vera Irnanda, Muhammad Fakhri Kurniadi, Denny Mahendra, Jimmy Mahesi Agni Zaus Marta, Rizkayeni Miftahul Jannah Ningsih, Tiara Heliyan Nurainah, Titik Aipah Nurlatipah, Nurlatipah Nuzul Hidayat, Nuzul Prastanti, Cinta Bening Putra, Rido Ramadhani, Wahyuni Resmi Darni Resmidarni, Resmidarni Sabrina, Mutiara Saputra, Noris Dwi Saputri, Sindi Syafitra, Kurniawan Syukhri, Syukhri Syukri, Raihan Titin Sriwahyuni Vera Irma Delianti Wahyuni, Titi Sri Yeka Hendriyani Zahelna Azzahra, Karisa