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Jurnal Nasional Teknologi Komputer
Published by CV. HAWARI
ISSN : 28087801     EISSN : 28084845     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Nasional Teknologi Komputer di bidang ilmu komputer dan teknologi. Jurnal JNASTEK diterbitkan oleh CV. Hawari. Redaksi mengundang peneliti, praktisi, dan mahasiswa untuk menulis perkembangan ilmiah di bidang-bidang yang berkaitan dengan teknologi informasi, teknik informatika dan sistem komputer. Jurnal JNASTEK terbit 4 (Empat) kali dalam setahun pada bulan Januari, April, Juli dan Oktober. Jurnal ini berisi artikel penelitian dan kajian ilmiah.
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 341 Documents
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Analisis dan perancangan sistem informasi e catreing berbasis wordpress Irvan Maulana; Doughlas Pardede; Aulia Ichsan
Jurnal Nasional Teknologi Komputer Vol 6 No 3 (2026): Juli 2026
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v6i3.505

Abstract

Digitalisasi layanan pada usaha catering diperlukan untuk mempermudah penyampaian informasi, promosi, dan proses pemesanan yang sebelumnya dilakukan secara manual. Penelitian ini bertujuan merancang dan mengimplementasikan sistem informasi e-catering berbasis WordPress pada Bakso Rizky sebagai solusi terapan terhadap kebutuhan tersebut. Jenis penelitian yang digunakan adalah penelitian terapan dengan pendekatan pengembangan sistem yang meliputi pengumpulan data, analisis kebutuhan, perancangan, implementasi, pengujian fungsional, dan evaluasi. Data kebutuhan sistem diperoleh melalui observasi, wawancara dengan pengelola usaha, dan dokumentasi. Sistem dikembangkan menggunakan CMS WordPress dengan dukungan PHP, HTML, CSS, dan MySQL. Hasil penelitian berupa website e-catering yang menyediakan informasi usaha, katalog menu dan paket catering, detail layanan, konten promosi, informasi kontak, fasilitas pemesanan daring, serta halaman administrator untuk pengelolaan konten dan pesanan. Pengujian fungsional menunjukkan bahwa fungsi utama sistem dapat dijalankan sesuai kebutuhan pengguna. Penelitian ini menghasilkan solusi teknologi terapan yang mengintegrasikan informasi, promosi, dan pemesanan catering dalam satu sistem berbasis web. Kata Kunci: e-catering, WordPress, sistem informasi, penelitian terapan, UMKM
Penerapan algoritma naive bayes untuk memprediksi bantuan subsidi upah bsu di kantor pos cabang binjai mayla zuhrina; Relita Buaton; Selfira
Jurnal Nasional Teknologi Komputer Vol 6 No 3 (2026): Juli 2026
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v6i3.507

Abstract

Bantuan Subsidi Upah (BSU) merupakan salah satu program pemerintah yang bertujuan membantu pekerja atau buruh dalam menghadapi tekanan ekonomi serta menjaga daya beli masyarakat. Dalam proses penyalurannya, Kantor Pos Cabang Binjai memiliki peran penting sebagai lembaga penyalur bantuan. Namun, proses analisis dan pengolahan data penerima bantuan masih menghadapi kendala, seperti ketidaktepatan sasaran dan keterbatasan dalam melakukan analisis terhadap data historis penerima bantuan. Penelitian ini bertujuan untuk menerapkan algoritma Naïve Bayes dalam memprediksi penerima Bantuan Subsidi Upah (BSU) di Kantor Pos Cabang Binjai. Metode yang digunakan dalam penelitian ini adalah metode data mining dengan algoritma Naïve Bayes sebagai metode klasifikasi. Data yang digunakan berupa data historis penerima BSU yang diperoleh dari Kantor Pos Cabang Binjai. Variabel yang digunakan dalam proses prediksi meliputi usia, jenis kelamin, status pekerjaan, pendapatan, wilayah domisili, tahun penerimaan, dan status penerimaan BSU. Hasil penelitian menunjukkan bahwa penerapan algoritma Naïve Bayes dapat digunakan untuk melakukan klasifikasi dan prediksi terhadap status penerimaan Bantuan Subsidi Upah berdasarkan data historis yang tersedia. Sistem yang dibangun mampu membantu proses pengolahan data penerima bantuan secara lebih cepat dan terstruktur dengan menghasilkan prediksi berupa kategori menerima atau tidak menerima bantuan berdasarkan nilai probabilitas yang diperoleh dari proses perhitungan algoritma Naïve Bayes. Berdasarkan penelitian yang dilakukan, dapat disimpulkan bahwa algoritma Naïve Bayes dapat diterapkan sebagai metode pendukung dalam proses analisis prediksi penerima BSU di Kantor Pos Cabang Binjai.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KEPALA DUSUN TERBAIK DENGAN MENGGUNAKAN METODE MFEP Zulfi Azhar
Jurnal Nasional Teknologi Komputer Vol 3 No 4 (2023): Volume 3 Nomor 4 Oktober 2023
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v3i4.508

Abstract

In village administration, the hamlet head plays a crucial role in facilitating governance, development, community guidance, and community empowerment at the hamlet level. The current issue at the Hilisimaetano village office is that the process of selecting the best hamlet head is still conducted manually and suffers from data inconsistencies, resulting in lengthy decision-making times. To address this problem, a decision support system for selecting the best hamlet head is required; by implementing the Multi-Factor Evaluation Process (MFEP) method, the system can assist in the selection process and provide accurate results. A decision support system is a computer-based system featuring an interface between the machine (or computer) and the user. By designing this system—which utilizes the MFEP method—using Microsoft Visual Basic 2008, a system capable of performing accurate calculations and ranking will be produced.
Sistem Pendukung Keputusan Pemilihan Fotografer Terbaik Menggunakan Metode MOORA Fadlina
Jurnal Nasional Teknologi Komputer Vol 3 No 4 (2023): Volume 3 Nomor 4 Oktober 2023
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v3i4.509

Abstract

Selecting the best photographer is a multi-criteria decision problem because each candidate must be evaluated simultaneously on technical and interpersonal competencies. This study develops a decision-support analysis using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to rank photographer candidates at PW Al Washliyah. Five alternatives were assessed using four benefit criteria: graphic design, photo-editing technique, basic videography, and communication ability, with weights of 0.35, 0.30, 0.20, and 0.15, respectively. Linguistic assessments were converted into numerical scores and normalized using vector normalization before weighted optimization values were calculated. Recalculation of the original dataset produced preference values of 0.431819, 0.433131, 0.459764, 0.438805, and 0.404119 for A1–A5. Alternative A3 (Ferry) achieved the highest score and was therefore ranked first. A simple ±10% weight-sensitivity test showed that A3 remained the top-ranked alternative in all tested scenarios. The results indicate that MOORA provides a transparent and reproducible ranking mechanism and can reduce reliance on purely subjective judgments in photographer selection.
Penentuan Penerima Beasiswa KIP Kuliah Menggunakan ROC dan SAW M Syaifuddin
Jurnal Nasional Teknologi Komputer Vol 3 No 4 (2023): Volume 3 Nomor 4 Oktober 2023
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v3i4.510

Abstract

The selection of KIP Kuliah scholarship recipients involves multiple criteria and a limited quota, so a structured decision model is required to reduce inconsistent manual assessment. This study applies Rank Order Centroid (ROC) to derive criterion weights and Simple Additive Weighting (SAW) to rank applicants. Seven applicant records from Universitas Budi Darma were used as a calculation sample. Five benefit criteria were assessed: competency relevance, foreign-language proficiency, social-card ownership, general-knowledge examination score, and interview score. ROC produced weights of 0.4567, 0.2567, 0.1567, 0.0900, and 0.0400, respectively. SAW normalization used the benefit formula xij/max(xij), ensuring normalized values in the interval 0–1. The recalculated preference scores ranged from 0.996386 to 0.998261. Alternative A5, Citra Lisensya Manurung, obtained the highest preference value of 0.998261, followed by A2 and A7. A ±10% one-at-a-time weight sensitivity check retained A5 as the top-ranked alternative in all scenarios. The ROC–SAW combination therefore provides a transparent ranking mechanism; however, the sample also shows that three high-weight criteria are identical across all candidates, limiting their discriminatory contribution.
Sistem Pendukung Diagnosis Kehamilan dan Kelainannya Menggunakan Jaringan Saraf Tiruan Backpropagation M. Syaifuddin; Risky Hadiansyah; Nancy Armaya
Jurnal Nasional Teknologi Komputer Vol 4 No 4 (2024): Oktober 2024
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v4i4.511

Abstract

Pregnancy-related complications require timely recognition, while symptom patterns may vary among patients. This study develops a decision-support model based on a backpropagation artificial neural network to classify six pregnancy-related conditions from symptom data. The dataset contains 172 records represented by 17 input variables and six output classes: normal pregnancy, early pregnancy, hyperemesis gravidarum, preeclampsia/eclampsia, hydatidiform mole, and ectopic pregnancy. Experiments evaluated training-test proportions of 90:10, 80:20, 70:30, 60:40, and 50:50, in addition to a resubstitution experiment using all records. The selected network used 17 input neurons, 50 hidden neurons, six output neurons, a sigmoid activation function, learning rate 0.1, target error 0.01, and a maximum of 50,000 epochs. Training accuracy reached 100% in the reported scenarios, whereas independent test accuracy ranged from 71.43% to 85.71%. The best holdout result was obtained with the 80:20 split, recognizing 30 of 35 test records (85.71%). These findings indicate that backpropagation can support multiclass pregnancy-condition classification, but further stratified validation and external clinical evaluation are required before practical diagnostic use.
Analisis Peminatan Penggunaan SIAKAD Menggunakan PCA pada Data Simulasi Fithry Tahel; Nabilah Aulia
Jurnal Nasional Teknologi Komputer Vol 5 No 4 (2025): Oktober 2025
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v5i4.512

Abstract

Academic information systems are a primary channel for students to access academic services, so user intention and perceptions of system quality need to be evaluated systematically. This study verifies a Principal Component Analysis (PCA) workflow for summarizing student-interest indicators toward an academic information system. The instrument contains 18 Likert-scale indicators covering perceived usefulness, perceived ease of use, information quality, system quality, accessibility, and behavioral intention. Because field data were not yet available in the source report, the analysis uses 180 simulated questionnaire records and is interpreted as methodological verification rather than an empirical survey of Universitas Budi Darma students. Internal consistency reached Cronbach's alpha 0.888; KMO was 0.887; and Bartlett's test was significant (chi-square=1354.07, df=153, p<0.001). Four components with eigenvalues above one explained 62.66% of total variance. Varimax rotation produced interpretable groups representing usefulness/ease, information/system quality, accessibility, and behavioral intention. Mean behavioral intention was 3.51, with 53.9% of simulated respondents classified as high interest. These results show that PCA can simplify correlated indicators, but empirical conclusions require actual survey data and replication of the analysis.
OPTIMASI CNN DENGAN ADAM OPTIMIZER UNTUK KLASIFIKASI DATA JAMUR Dika; Zulham Sitorus; Muhammad Syahputra Novelan
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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

Abstract

Mushrooms are one of the most nutritious food sources; however, several species contain toxic compounds that can cause serious poisoning or even death if incorrectly identified. The high visual similarity between edible and poisonous mushrooms makes manual identification difficult, especially for non-experts. Therefore, an automatic image classification system is needed to improve the accuracy and consistency of mushroom identification. This study aims to develop a mushroom image classification model using a Convolutional Neural Network (CNN) optimized with the Adam Optimizer. The dataset was obtained from Kaggle and consisted of 2,820 images, divided into 2,256 training images, 282 validation images, and 282 testing images. The model was further validated using an external dataset of 83 real mushroom images to evaluate its generalization capability. All images were preprocessed through image resizing to 224 × 224 pixels and pixel normalization before model training. Model performance was evaluated using accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). Experimental results on the Kaggle test dataset achieved an accuracy of 62.77%, precision of 58.28%, recall of 71.97%, F1-score of 64.41%, and an AUC of 0.6482. Evaluation on the external dataset demonstrated improved performance, achieving an accuracy of 85.54%, precision of 94.59%, recall of 77.78%, and F1-score of 85.37%. These findings indicate that the CNN model optimized with the Adam Optimizer is capable of performing mushroom image classification effectively and demonstrates good generalization performance on real-world data, making it a promising approach for automatic mushroom identification.
PERENCANGAN RESERVASI DAN PENJADWALAN TERAPIS BERBASIS WEBSITE Muhammad Ikram Laksana; Ruly Dwi Arista; Suheri
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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

Abstract

The rapid development of information technology today has triggered innovation across various business and service sectors, including the healthcare, wellness, and therapist service industry. The main problem frequently encountered in the management of clinics or therapy centers that still utilize conventional or manual systems is the limited access to real-time schedule availability information for therapists. This requires prospective customers to conduct repetitive communication via telephone or visit the location in person just to ensure available slot availability. This operational situation is not only inefficient in terms of time and energy for patients, but also carries a high risk of causing overlapping daily schedules, irregular queue accumulations in the clinic waiting area, and triggering fatal operational miscommunications among administrative staff. To overcome all these problems, this research aims to design and develop a centrally integrated website-based therapist reservation and scheduling information system application. The scope of this system design focuses deeply on independent patient account registration features, online therapy session booking, internal therapist work calendar management, daily quota limitation systems, and an automatic schedule reservation confirmation system to improve operational data accuracy. This study provides clear operational limitations that the service payment transaction process remains conducted offline directly at the clinic location cashier. The results of this study are expected to automate the entire reservation workflow, minimize the potential for human error, significantly reduce the administrative workload for clinic management, and enhance customer satisfaction through the provision of a fast, transparent, flexible, and accurate self-booking system.
PERANCANGAN SISTEM ADMINISTRASI DIGITAL BERBASIS WEB UNTUK OPTIMALISASI PELAYANAN DI KELURAHAN ALUR DUA BARU Riska Sandra; Juliandri; Leni Marlina
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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

Abstract

Administrative letter services at Alur Dua Baru Village Office are still carried out manually, requiring residents to visit the office to submit applications and collect completed documents. This condition reduces service efficiency, increases the risk of data recording errors, and makes it difficult for residents to obtain information regarding the progress of their applications. This study aims to design and implement a web-based digital administrative system to support administrative services at the Alur Dua Baru Village Office. The system was developed using the Waterfall method, which consists of the stages of requirements analysis, system design, implementation, testing, and maintenance. Data were collected through observation, interviews, and literature review, while the system was developed using PHP and MySQL. The results show that the system enables residents to submit letter applications through an online platform independently, upload supporting documents, monitor application status, obtain estimated completion time information, and receive letters in PDF format equipped with QR Codes for document authenticity validation and information on the document validity period. Black Box Testing conducted on 21 test scenarios demonstrated that all system functions operated according to the specified functional requirements. Therefore, the developed system improves the effectiveness of administrative services, enhances information transparency, and assists village office staff in managing administrative processes more efficiently.

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