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Journal of System and Technology
Published by Universitas Riau
ISSN : 31100171     EISSN : 31100171     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
Journal of System & Technology (SYSTEC) covers a broad range of research topics within Electrical Engineering, Informatics Engineering, and applied technologies, addressing both theoretical and practical aspects of design, development, and application. Specifically, the scope includes, but is not limited to, the following areas: 1. Computer Science and Engineering ✔ Development and implementation of algorithms and data structures in computing. ✔ Programming and software engineering for computer-based applications. ✔ Development of computer-based systems for industrial and technological applications. ✔ Parallel and distributed computing systems in big data and cloud computing. 2. Information Technology ✔ Development and management of IT infrastructure for industrial applications. ✔ Technologies in cloud computing, virtualization, and distributed computing. ✔ Cybersecurity, data privacy, and information systems protection. ✔ Application of technologies in IT infrastructure management and maintenance. 3. Information Systems ✔ Design and development of information systems for data management and decision-making. ✔ Enterprise Resource Planning (ERP) and organizational information management technologies. ✔ Web-based and mobile information systems for business and public services. ✔ Applied information systems in healthcare, education, government, and finance. 4. Electrical and Electronics Engineering ✔ Development and design of electronic devices and electrical systems for industry. ✔ Electronic control systems and automation in electrical engineering. ✔ Application of renewable energy and smart energy systems. ✔ Electronic devices for medical, communication, and control systems. 5. Electronics and Telecommunication ✔ Development of digital, wireless, and telecommunication networks. ✔ Satellite systems, 5G networks, and distributed data transmission technologies. ✔ Integrated electronic systems for telecom and data applications. ✔ Technologies for smart cities and infrastructure in electronic communication. 6. Applied Technologies ✔ Technologies in sectors like automotive, agriculture, and healthcare. ✔ Smart systems and smart grids for energy and urban infrastructure. ✔ Robotics, intelligent systems, and industrial automation. ✔ Big data and analytics in manufacturing, logistics, and finance.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 23 Documents
 1   2   3 
Automatic Sliding Gate System with IoT Capability Budhi Anto; Dahliyusmanto; Eddy Hamdani
Journal of System & Technology (SYSTEC) Vol. 1 No. 2 (2025): Journal of System & Technology (December Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

This paper presents a novel automatic sliding gate system with IoT capability enabling it to be controlled through the Internet using a smartphone. The system is built on three main parts: sliding gate opener (SGO) with its driving mechanism, electronic control unit (ECU), and an Android smartphone with application software to communicate with the ECU. The SGO is driven by a 12-pole permanent-split-capacitor (PSC) motor coupled with speed reducer gearbox and uses a rack-pinion power transmission. The ECU, which is based on two microcontroller modules working in  a cascade arrangement, controls the movement of the PSC motor in either forward or reverse rotation according to the information gained from a set of mechanical switches, inductive proximity sensors, and commands from the smartphone. The first microcontroller module is an Arduino UNO, functions to control the operation of PSC motor. The second is an ESP32 NodeMCU rolling as a communication controller between the ECU and smartphone. The SGO can also be controlled locally at the gate site by using a set of mechanical switches mounted on the control panel of the sliding gate system. The sliding gate system employs two inductive proximity sensors installed at the ends of the SGO movement to give information to the Arduino to stop the motor automatically as the SGO approaches the sensor position. The functional test has been conducted on the sliding gate system and the results show that the SGO movement can be controlled locally through pushbutton switches and remotely using an Android smartphone.
APLIKASI MOBILE BERBASIS ANDROID UNTUK REKOMENDASI RESEP MASAKAN DIET KETOGENIK YANG RENDAH KARBOHIDRAT Haidar, Ali; Gemala Jondya, Aisha; Tania, Erika; Arief, Remmy Joshua; Jondya, Aisha Gemala
Journal of System & Technology (SYSTEC) Vol. 1 No. 2 (2025): Journal of System & Technology (December Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

Beberapa faktor yang menjadikan diet keto populer adalah peningkatan kesadaran akan pentingnya pola makan yang sehat, dan meningkatnya jumlah orang yang mengalami obesitas, serta penyakit lain seperti diabetes. Terbatasnya pilihan makanan dan bahan yang diperbolehkan saat menjalani diet keto, menjadi salah satu tantangan yang dihadapi oleh para pejuang diet keto. Pada penelitian ini aplikasi "Diet Keto" dikembangkan sebagai alat yang dapat membantu pengguna berbagi resep dan menemukan variasi hidangan yang sesuai dengan diet ketogenik. Metode pengembangan yang digunakan dalam penelitian ini adalah metode Agile. Metode ini melibatkan perencanaan, perancangan, implementasi sistem, dan pengujian. Bahasa pemrograman yang digunakan adalah Typescript, PHP, Laravel, dan Android Studio sebagai lingkungan pengembangan. Hasil dan kesimpulan yang dicapai adalah melalui penggunaan aplikasi ini, pengguna dapat dengan lebih mudah mengikuti dan mencapai tujuan diet ketogenik mereka. Berdasarkan hasil evaluasi terhadap pengguna, 63,6% pengguna menganggap aplikasi membantu dan 18,8 % pengguna menganggap aplikasi sangat membantu proses diet keto yang dilakukan sementara hanya 17.6% pengguna merasa aplikasi kurang membantu proses diet keto.
PENERAPAN KEAMANAN Hashing password pada sistem penjualan bibbi shop berbasis web Dermawan, Rufaida; Rahman, Rakhmadi
Journal of System & Technology (SYSTEC) Vol. 1 No. 2 (2025): Journal of System & Technology (December Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

Keamanan penyimpanan password merupakan aspek krusial dalam sistem penjualan berbasis web, khususnya pada platform e-commerce yang mengelola data pengguna secara sensitif. Penelitian ini bertujuan untuk menganalisis penerapan algoritma hashing bcrypt dalam meningkatkan keamanan autentikasi pengguna pada sistem penjualan Bibbi Shop berbasis web. Metode penelitian yang digunakan adalah pendekatan rekayasa perangkat lunak dengan tahapan analisis kebutuhan, perancangan sistem keamanan, implementasi bcrypt pada proses registrasi dan login, serta pengujian keamanan penyimpanan password. Hasil penelitian menunjukkan bahwa penerapan bcrypt mampu meningkatkan tingkat keamanan penyimpanan password secara signifikan dibandingkan metode hashing konvensional, karena adanya mekanisme salt otomatis dan pengaturan cost factor yang dapat disesuaikan dengan kebutuhan sistem. Implementasi ini juga mampu meminimalkan risiko serangan seperti brute force dan rainbow table. Berdasarkan hasil analisis, dapat disimpulkan bahwa algoritma bcrypt efektif dan layak digunakan sebagai solusi keamanan autentikasi pada sistem penjualan berbasis web.
Pengembangan Sistem Informasi Peminjaman Dan Pengembalian Buku Menggunakan Pendekatan V-Model (Studi Kasus: Perpustakaan Sman 1 Batu Hampar Hanifah, Puja; Darmayanti Br Pasaribu, Rantika; Syaliman, Khairul Umam
Journal of System & Technology (SYSTEC) Vol. 1 No. 2 (2025): Journal of System & Technology (December Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

The library is an important facility in supporting the teaching and learning process in the school environment. At SMA Negeri 1 Batu Hampar, recording of borrowing and returning books is still done manually, which often causes delays and recording errors. To overcome this, a website-based library information system was developed using the Laravel framework and the V-Model method to ensure the development process is carried out in a structured manner and according to user needs. The test results showed that the system ran well, where Black Box Testing with 52 test cases was successful without significant obstacles, Integration Testing showed that all features were well connected, and User Acceptance Test (UAT) on 21 test cases by four user roles (principal, librarian, teacher, and student) was 100% successful. Usability Testing also showed an average value of 76%, with details of Learnability 79.5%, Efficiency 72%, Memorability 73.5%, Error 83%, and Satisfaction 72%. With these results, the system is proven to be able to improve the work efficiency of librarians and provide easy access for users, and is suitable for implementation in the school environment.
Analisis Pengalaman Pengguna dan Tingkat Kegunaan Aplikasi Mobile dan Website Shopee Menggunakan Pendekatan Human–Computer Interaction Chaizura, Natasya; Natasya Chaizura; Junaidi Salat; Nurhidayani; Tursina; Uliya Safura
Journal of System & Technology (SYSTEC) Vol. 1 No. 2 (2025): Journal of System & Technology (December Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

The rapid development of digital technology has driven the significant growth of e-commerce platforms as a widely used medium for online transactions. Shopee is one of the most widely used e-commerce platforms in Indonesia, accessible through both mobile applications and websites. This study aims to analyze the user experience and usability of the Shopee mobile application and website using a Human–Computer Interaction (HCI) approach. The research employs a quantitative method, with data collected through questionnaires distributed to active Shopee users. The aspects analyzed include ease of use, navigation efficiency, clarity of the user interface, and overall user comfort in interacting with the system. The results indicate that Shopee generally demonstrates a good level of usability, particularly in terms of ease of use and feature completeness. However, some users still experience difficulties related to interface consistency and navigation complexity in certain features. This study is expected to provide valuable insights for developers in improving the quality of user experience on e-commerce platforms.
Analisis dan Implementasi Alat Administrasi Jaringan Berbasis Model FCAPS: Studi Efektivitas CMD dan Winbox Pada Lingkungan Mikrotik Elisa Soleha; Dahliyusmanto; Nanda Dwi Putra; Dimas Panji Eka Jala Putra; Khairul Umam Syaliman
Journal of System & Technology (SYSTEC) Vol. 2 No. 1 (2026): Journal of System & Technology (June Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

This study aims to perform an analysis and practical implementation of network administration tools based on the FCAPS model (Fault, Configuration, Accounting, Performance, Security) using Command Prompt (CMD) and WinBox on a simple network consisting of one MikroTik router and one laptop. The research method uses a Systematic Literature Review (SLR) approach and implementative experiments. CMD is used for connectivity testing and network performance, while WinBox is used for IP configuration, firewall management, and traffic monitoring. The results showed that CMD is effective for Fault and Performance Management, while WinBox excels in Configuration and Security Management. Despite limited devices, the application of FCAPS can still be done practically and measurably. This research provides a guide for students and novice network technicians in applying network administration principles simply yet comprehensively.
valuasi Kinerja Lima Algoritma Pembelajaran Mesin dengan SMOTE untuk Klasifikasi Sentimen Komentar YouTube terhadap Kebijakan Purbaya M. Darma Alfero
Journal of System & Technology (SYSTEC) Vol. 2 No. 1 (2026): Journal of System & Technology (June Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

The evolution of public policy communication in the digital age has encouraged social media to become a deliberative space that openly reflects the dynamics of public perception and sentiment. This paper aims to conduct a comparative analysis of the performance of several machine learning algorithms in classifying the sentiment of YouTube user comments as a representation of public response to policy communication delivered by Minister Purbaya. The research was conducted using web scraping techniques with the YouTube Data API v3 on three public policy videos, with a total of 6,466 comments. The text data were processed using preprocessing, lexicon-based sentiment labeling, TF-IDF feature weighting, and class imbalance handling via the Synthetic Minority Over-sampling Technique (SMOTE). Five machine learning algorithms were applied, comprising SVM, KNN, RF, NB, and LR. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The results showed that SVM produced the most optimal performance with an accuracy value of 0.78 and a consistent F1-score balance across all sentiment classes. These findings highlight the importance of algorithm suitability, feature representation, and data balancing strategies in developing reliable sentiment analysis models for evaluating data-driven public policy communication.
RANCANG BANGUN ROBOT 4WD KENDALI SUARA BERBASIS KEYWORD SPOTTING MENGGUNAKAN EDGE AI PADA MIKROKONTROLER ESP32-S3 Rehandra; Feri Candra
Journal of System & Technology (SYSTEC) Vol. 2 No. 1 (2026): Journal of System & Technology (June Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

Meningkatnya adopsi Kecerdasan Buatan (AI) dalam dunia pendidikan telah menciptakan kesenjangan yang signifikan antara alat pembelajaran robotika konvensional dengan kebutuhan industri saat ini. Platform yang ada, seperti robot Edubit berbasis BBC Micro:bit yang digunakan di Educourse.id, belum memiliki kemampuan pemrosesan AI secara asli (native) dan memiliki biaya yang relatif tinggi, sehingga kurang memadai untuk mengajarkan konsep embedded AI modern. Penelitian ini menyajikan desain dan implementasi purwarupa robot 4WD yang dikendalikan suara menggunakan teknologi Keyword Spotting yang diimplementasikan sepenuhnya pada perangkat melalui Edge AI. Sistem ini dibangun menggunakan mikrokontroler ESP32-S3 dengan memanfaatkan arsitektur dual-core Xtensa LX7 yang mendukung instruksi vektor untuk akselerasi jaringan saraf. Input audio ditangkap melalui mikrofon MEMS INMP441 melalui protokol I2S dan diproses oleh framework ESP-SR, yang mengintegrasikan WakeNet untuk deteksi wake word ("Hi ESP") dan MultiNet7 untuk klasifikasi perintah navigasi. Lima perintah arah didukung dalam sistem ini: maju, mundur, kiri, kanan, dan berhenti. Arsitektur FreeRTOS dual-core dengan penempatan tugas (task pinning) secara eksplisit memisahkan inferensi AI pada Core 1 dari logika Finite State Machine dan transmisi nirkabel pada Core 0 untuk memastikan performa real-time yang deterministik. Perintah navigasi yang telah divalidasi dikirimkan secara nirkabel ke unit robot menggunakan protokol ESP-NOW melalui struktur paket 7-byte yang ringkas dengan verifikasi integritas XOR checksum. Evaluasi sistem dilakukan menggunakan Black Box Testing melalui 50 percobaan yang melibatkan lima penutur berbeda di lingkungan dalam ruangan dengan tingkat kebisingan sedang. Hasil penelitian menunjukkan akurasi pengenalan perintah sebesar 100% di seluruh lima perintah navigasi, dengan skor kepercayaan rata-rata 17,62%. Temuan ini mengonfirmasi bahwa sistem yang diusulkan sangat andal dan layak digunakan sebagai platform pembelajaran Edge AI yang terjangkau dan interaktif untuk pendidikan robotika.
PERBANDINGAN KINERJA MODEL CNN EFFICIENTNETB0 DAN VISION TRANSFORMER UNTUK KLASIFIKASI CITRA REAL-FAKE Akhlaqul Muhammad Fadwa; M. Sohibbal; Rachel Ditya Syaharani; Dian Ramadhani; Al Aminuddin
Journal of System & Technology (SYSTEC) Vol. 2 No. 1 (2026): Journal of System & Technology (June Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

Model generatif berbasis Generative Adversarial Network (GAN) seperti StyleGAN, Stable Diffusion, DALL·E, dan DeepFaceLab kini mampu menghasilkan citra sintetis yang sulit dibedakan dari citra asli, memicu penyalahgunaan berupa deepfake, manipulasi identitas digital, dan misinformasi visual yang mengancam kepercayaan terhadap konten digital. Penelitian ini mengusulkan pendekatan komparatif antara Convolutional Neural Network (CNN) berbasis EfficientNetB0 dan Vision Transformer (ViT) untuk mengklasifikasikan citra real dan fake guna mengidentifikasi arsitektur paling efektif dalam deteksi konten sintetis. Kedua model dikonfigurasi dengan backbone frozen menggunakan bobot pre-trained dan classifier head identik: Dense(512, ReLU), Dropout(0,4), Dense(256, ReLU), Dropout(0,4), Dense(1, Sigmoid), untuk memastikan perbandingan yang objektif. Dataset CIFAKE terdiri dari 120.000 citra — 60.000 real (CIFAR-10) dan 60.000 fake (Stable Diffusion v1.4) — diproses dengan resizing ke 224×224 piksel, normalisasi, dan augmentasi data, dengan pembagian 80:20 untuk pelatihan-validasi dan 20.000 citra untuk pengujian. Evaluasi dilakukan menggunakan akurasi, precision, recall, F1-score, dan confusion matrix. EfficientNetB0 mencapai akurasi 84,79% dengan waktu pelatihan ±1 jam 12 menit, namun lemah pada deteksi kelas fake dengan recall 72,17% dan false positive 2.783 citra. Sebaliknya, Vision Transformer mencapai akurasi 97,15% dengan precision, recall, dan F1-score seimbang di atas 97% pada kedua kelas, dengan waktu pelatihan ±14 jam 18 menit. Vision Transformer terbukti mengungguli EfficientNetB0 pada seluruh metrik, sementara EfficientNetB0 tetap relevan pada skenario dengan keterbatasan komputasi. Secara khusus, untuk menekan angka false positive pada EfficientNetB0, penelitian selanjutnya dapat menerapkan class-weighted loss atau focal loss guna meningkatkan sensitivitas model terhadap kelas fake, serta threshold tuning pada output sigmoid untuk menyeimbangkan precision dan recall.
KOMPARASI K-MEANS DAN AGGLOMERATIVE CLUSTERING PADA SEGMENTASI PELANGGAN RITEL Muhammad Abidillah; Rehandra Rehandra; Dian Ramadhani
Journal of System & Technology (SYSTEC) Vol. 2 No. 1 (2026): Journal of System & Technology (June Edition)
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Riau

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Abstract

Segmentasi pelanggan merupakan strategi krusial dalam industri ritel modern untuk mengoptimalkan pemasaran berbasis data. Namun, mayoritas studi komparatif terdahulu hanya mengevaluasi Agglomerative Clustering pada satu konfigurasi linkage default, sehingga sensitivitas performa algoritma terhadap pemilihan kriteria jarak belum banyak dikuantifikasi secara eksplisit. Penelitian ini bertujuan mengisi kesenjangan tersebut dengan membandingkan kinerja K-Means terhadap empat varian Agglomerative Clustering (Single, Complete, Average, dan Ward Linkage) dalam mengelompokkan perilaku transaksi pelanggan, dievaluasi secara kuantitatif menggunakan Silhouette Score dan Davies-Bouldin Index. Lingkungan penelitian dibangun menggunakan platform RapidMiner untuk memproses Synthetic Customer Dataset yang terdiri dari 500 observasi, dengan validasi metrik dihitung secara konsisten melalui scikit-learn. Tahap pra-pemrosesan meliputi seleksi fitur dan normalisasi Z-transformation terhadap lima atribut numerik: Age, TotalSpend, AverageOrderValue, TotalOrders, dan LoyaltyPoints. Hasil eksperimen menunjukkan bahwa K-Means (Silhouette=0,165; DBI=1,592) secara konsisten mengungguli seluruh varian Agglomerative Clustering yang diuji. Single Linkage mengalami chaining effect yang tercermin dari Silhouette Score negatif (-0,123), meskipun nilai DBI-nya tampak rendah (0,777) akibat artefak klaster singleton yang hampir tidak memiliki dispersi internal. Complete (Silhouette=0,082; DBI=1,931), Average (Silhouette=0,108; DBI=1,792), dan Ward Linkage (Silhouette=0,111; DBI=1,927) berhasil menghindari chaining effect namun tetap menghasilkan kualitas partisi yang lebih rendah dibandingkan K-Means. Temuan ini menegaskan bahwa keberhasilan Agglomerative Clustering pada data ritel padat sangat bergantung pada pemilihan kriteria linkage, dan kontribusi utama penelitian ini adalah kuantifikasi eksplisit atas sensitivitas tersebut, termasuk pengungkapan bahwa Davies-Bouldin Index dapat menyesatkan ketika diterapkan pada distribusi klaster yang sangat tidak seimbang.

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