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INDONESIA
Jurnal Ilmiah Teknologi dan Rekayasa
Published by Universitas Gunadarma
ISSN : 14109093     EISSN : 20898088     DOI : http://dx.doi.org/10.35760/tr.
Core Subject : Science, Engineering,
Automotive Engineering Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Jurnal ini diterbitkan secara berkala tiga kali dalam setahun, April, Agustus, dan Desember. Artikel yang dimuat dalam jurnal ini merupakan artikel ilmiah hasil penelitian tentang teknologi dan rekayasa yang meliputi teknik informatika, teknik elektro, teknik mesin, dan teknik industri. Artikel dapat ditulis dalam bahasa indonesia maupun bahasa inggris.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 236 Documents
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Implementasi model support vector machine sebagai sistem prediksi penyakit ginjal kronik berbasis data klinis Rama Dian Syah; Diandra Hasna Widianto; Bhakti Gunawan; Hadyanto Caputra; Widya Silfianti; Rena Fuji Erin Setyawati
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 1 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i1.218

Abstract

Chronic Kidney Disease (CKD) is one of the global health problems with increasing prevalence and mortality rates, requiring accurate early detection methods to support timely treatment and prevention. Various previous studies have applied machine learning techniques for CKD prediction; however, most studies are still limited to basic model implementation without systematic parameter optimization or real-time web-based prediction system deployment. This study aims to develop a CKD prediction model using the Support Vector Machine (SVM) algorithm optimized through GridSearchCV to improve classification performance. The research was conducted based on the CRISP-DM framework using the CKD dataset from the UCI Machine Learning Repository. The preprocessing stage included categorical data transformation, missing value handling using median imputation, and feature standardization using StandardScaler. Parameter optimization was performed by testing several SVM parameter combinations using a 5-fold cross-validation approach. The results showed that the optimized SVM model achieved an accuracy of 98.75%, with high precision, recall, and F1-score values in CKD and non-CKD classification. These results indicate better performance compared to several previous studies using similar datasets with accuracy below 98%. Furthermore, the model was implemented in a web-based application using Gradio and Hugging Face Spaces to support real-time prediction. Initial validation by an internal medicine specialist indicated that the system predictions were consistent with medical interpretation, suggesting that the proposed model has potential as a decision-support tool for early CKD detection
Pengembangan sistem pakar diagnosis tingkat depresi mahasiswa semester akhir berbasis android menggunakan metode certainty factor Maximilianus Amasanan; Yoseph Pius Kurniawan Kelen
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 1 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i1.143

Abstract

Depression is increasingly experienced by final-year university students due to academic pressure, with symptoms such as prolonged sadness, loss of motivation, sleep disturbances, and difficulty concentrating. Early detection remains limited because of restricted access to mental health professionals and the high cost of consultations. This study aims to develop an Android-based expert system for diagnosing depression levels using the Certainty Factor (CF) method. The research employed the Research and Development (R&D) method with the Rapid Application Development (RAD) model, which consists of requirements planning, design, construction, and implementation stages. The system utilizes 15 symptoms and classifies four levels of depression: mood disorder, mild depression, moderate depression, and severe depression. The evaluation was conducted on 20 respondents by comparing the system’s diagnostic results with expert analysis. The evaluation results showed that 17 out of 20 system diagnoses were consistent with the expert’s analysis, resulting in an accuracy rate of 85%. An example of the calculation process using the CF method produced a diagnostic value of 0.95 (95%), which falls into the severe depression category. The developed system is capable of supporting early detection of depression in a faster, more practical, and easily accessible manner through Android devices, and it can serve as an initial consultation tool for final-year students. The system can assist early detection more efficiently and with greater accessibility.
Evaluasi keamanan sistem e-journal berbasis web menggunakan framework NIST SP 800-115 dan analisis berdasarkan OWASP top 10 Ibnu Ajis; Tri Rochmadi; Yanuar Wicaksono; Dadang Heksaputra
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 1 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i1.158

Abstract

The use of web-based information systems in higher education institutions, particularly e-journal platforms, continues to rise. However, this is often not accompanied by adequate security measures, thereby threatening Confidentiality, Integrity, and Availability (CIA). This study aims to evaluate the security of a proceedings system based on Open Journal Systems (OJS) at the Adisutjipto Institute of Aeronautical Technology (ITDA) in Yogyakarta. The method used was penetration testing based on the NIST SP 800-115 standard via a black-box approach, which included the planning, discovery, attack, and reporting phases. Initial identification using the OWASP ZAP automated scanner identified 11 vulnerability indicators with estimated severity levels ranging from low to medium. However, after conducting the exploitation validation (proof-of-concept) phase and assessment using the OWASP Risk Rating method, it was found that some vulnerabilities posed a higher risk impact than the initial scan results indicated. The final research results confirmed the presence of 3 high-risk findings and 1 medium-risk finding. These high-risk vulnerabilities include Host Header Injection, which enables Reflected XSS attacks; a Security Misconfiguration on the /server-status endpoint; and the absence of a rate-limiting mechanism in the authentication feature. This study concludes that the system has significant security vulnerabilities that require immediate mitigation. Key recommendations include updating the OJS platform version, implementing server configuration hardening, and enhancing login security mechanisms to continuously protect the Integrity and Confidentiality of the institution’s academic data.
Sistem pakar diagnosis stadium rabies pada manusia menggunakan metode certainty factor berbasis web: studi kasus Puskesmas Oelolok Maria Gradiana Misa; Yoseph Pius Kurniawan Kelen; Krisantus Tey J Seran
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 1 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i1.167

Abstract

Delays in the early diagnosis of rabies remains a significant issue due to the limited of public knowledge in recognizing the symptoms of the disease, resulting in delayed medical treatment. This study aims to develop a web-based expert system designed to assist in the early diagnosis of rabies in humans using the Certainty Factor (CF) method. This method is used to calculate the confidence level of the diagnosis based on the symptoms selected by the user. The system knowledge base was obtained through expert interviews and literature studies, which were represented in the form of diagnostic rules. The system is capable of providing rabies diagnosis results along with their corresponding confidence values based on the symptoms entered by users. Functional testing using the Black Box Testing method showed that all system features functioned properly. In addition, system validation was carried out by comparing the system diagnosis results with expert diagnoses through 30 testing scenarios using different symptom combinations. The test results showed 27 matching data and 3 non-matching data, resulting in a system accuracy rate of 90%. This research contributes to the implementation of the CF method in a web-based expert system to support early rabies diagnosis in a fast and measurable manner.
Image captioning bilingual berbasis BLIP-2 dan MarianMT dengan integrasi text-to-speech untuk literasi visual siswa Rizka Oktaviani; Fauziah Fauziah
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 2 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i2.152

Abstract

Visual literacy is the ability to understand and interpret information from visual representations, which involves linguistic processing. In the context of elementary education, this ability is crucial for helping students associate visual objects with bilingual vocabulary. However, most image captioning research remains monolingual, few studies accommodate Indonesian, and none have integrated audio representations into a single multimodal learning system. This study develops a bilingual image captioning system based on BLIP-2 and MarianMT, integrated with Text-to-Speech (TTS) within a FastAPI-based web application. English captions are generated using a pretrained BLIP-2 model, then translated into Indonesian using MarianMT, and converted to audio using gTTS. Additionally, a QLoRA fine-tuning experiment was conducted to compare model performance. The dataset consists of 6400 animal images relevant to the elementary school learning context, with caption quality evaluated using the METEOR metric. The results show that the pretrained BLIP-2 model delivers relatively stable performance with a METEOR score of 0.3765 for English and 0.3295 for Indonesian. These scores indicate that the generated captions are semantically relevant, although the overall performance is still relatively moderate compared to advanced image captioning systems. Functional testing of the prototype involving five elementary school students showed that the system is capable of generating bilingual captions and audio in real time and is easy to use. This multimodal integration supports the visual–verbal association process and has the potential to enrich students’ bilingual vocabulary, although no controlled experimental testing has yet been conducted to quantitatively measure improvements in literacy.
Pengaruh variasi elektroda dan arus pengelasan terhadap kekuatan tarik sambungan las SMAW pada stainless steel 304 Ario Ardiansyah; Basuki; Retno Eka Pramitasari; Dian Anisa Rokhmah Wati
Jurnal Ilmiah Teknologi dan Rekayasa Vol. 31 No. 2 (2026)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2026.v31i2.367

Abstract

Penelitian ini bertujuan menganalisis pengaruh penggunaan elektroda E6013 dan E7016 serta variasi arus pengelasan terhadap kekuatan tarik sambungan las pada material Stainless Steel 304 yang dilas menggunakan metode Shielded Metal Arc Welding (SMAW). Metode yang diterapkan dalam penelitian ini adalah eksperimen kuantitatif dengan memvariasikan jenis elektroda dan besar arus pengelasan sebagai variabel bebas. Elektroda yang digunakan terdiri atas E6013 dan E7016 dengan variasi arus sebesar 75 A dan 80 A. Adapun variabel terikat yang diamati meliputi tegangan tarik, regangan, dan modulus elastisitas hasil pengelasan. Material uji berupa plat Stainless Steel 304 dengan ketebalan 1,8 mm yang dibuat menjadi 12 spesimen pengujian. Seluruh spesimen kemudian diuji menggunakan mesin uji tarik untuk mengetahui karakteristik mekanik sambungan las yang dihasilkan. Hasil pengujian menunjukkan bahwa kombinasi elektroda E6013 pada arus 75 A menghasilkan performa terbaik dengan nilai tegangan tarik rata-rata sebesar 527,94 MPa dan modulus elastisitas sebesar 15.994,9 MPa. Sementara itu, pada penggunaan elektroda E7016, nilai tegangan tarik rata-rata tertinggi diperoleh pada arus 80 A sebesar 409,3 MPa. Temuan penelitian menunjukkan bahwa jenis elektroda dan besar arus pengelasan memberikan pengaruh terhadap kekuatan tarik sambungan las. Peningkatan arus yang melebihi kondisi optimum cenderung menurunkan kekuatan tarik akibat bertambahnya masukan panas yang memengaruhi karakteristik daerah las dan daerah terpengaruh panas.

Page 24 of 24 | Total Record : 236

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