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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Armada Informatika Jurnal Mahasiswa Ilmu Komputer Jurnal Komputasi
M. Yhogha Ismail Ibn Ibrahim
Universitas Lampung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Analisis Penerimaan dan Penggunaan Website Training Center di Universitas X Menggunakan Technology Acceptance Model (TAM) Muhammad Galih Ramaputra; Hendri Purnomo; M. Yhogha Ismail Ibn Ibrahim
Jurnal Komputasi Vol. 13 No. 2 (2025)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v13i2.285

Abstract

In the digital era, the use of information technology in education is crucial to enhance the effectiveness of learning and training. University X has developed a Training Center website as a supporting platform for academic and professional activities for students and educators. This study analyzes the acceptance and use of the website using the Technology Acceptance Model (TAM), with the main variables being Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Use (ATU), Behavioral Intention to Use (BI), and Actual System Usage (ASU). The research method employed is a quantitative survey through the distribution of questionnaires to students, lecturers, and educational staff. The results show that PU scored 75.2%, PEOU 8.69%, ATU 75.37%, and BI 77.5%, indicating that users have a positive perception of the benefits and intention to use the website, although there are still challenges regarding ease of use. To improve the website's effectiveness, it is recommended to optimize features, integrate with the Learning Management System (LMS), and enhance outreach and training for users. The results of this study are expected to serve as a basis for further development to increase the acceptance and usage of the Training Center website at University X.
XR-VITS: Extended Reality-Based Vehicle Tracking For Traffic Monitoring And Risk Assessment Dewi Yulianti; Allwine; M. Yhogha Ismail Ibn Ibrahim
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

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Abstract

Extended Reality (XR) technology represents a promising advancement for intelligent transportation systems by enhancing traffic monitoring, situational awareness, and operator interaction. Despite progress, conventional vehicle tracking systems continue to exhibit limitations, such as inaccurate trajectory estimation, restricted risk prediction capabilities, and non-intuitive visualization interfaces. This study introduces XR-VITS (Extended Reality Vehicle Intelligent Tracking System), an integrated framework that unifies YOLO-based vehicle detection, Kalman filter-based multi-object tracking, homography-based real-world coordinate mapping, trajectory prediction, collision risk assessment, and immersive XR visualization within a single traffic monitoring architecture. The framework was evaluated on diverse traffic datasets, including urban, highway, adverse weather, and low-light scenarios. Experimental results indicate that XR-VITS achieved a Multiple Object Tracking Accuracy (MOTA) of 89.3% and an Identification F1 Score (IDF1) of 86.2%, surpassing several state-of-the-art tracking methods, such as DeepSORT, StrongSORT, ByteTrack, and QDTrack. Additionally, the system attained a collision risk prediction F1-score of 86.4% while maintaining real-time processing at 25.1 FPS. The XR visualization module further enhanced operator situational awareness and reduced response times compared to conventional 2D monitoring systems. These results demonstrate that XR-VITS provides an effective and scalable solution for next-generation intelligent transportation systems requiring predictive intelligence, immersive visualization, and real-time traffic monitoring.
Rule-Based Expert System Model with Backward Chaining Algorithm for Symptom-Based Skin Disease Diagnosis Sandi Badiwibowo Atim; M. Yhogha Ismail Ibn Ibrahim
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.v8i1.4416

Abstract

A rule-based expert system was a computational model designed to emulate expert decision-making using a knowledge base and inference algorithms. This research developed a rule-based expert system model with a backward chaining algorithm to diagnose skin diseases based on clinical symptoms. Backward chaining, a goal-driven inference method, started with a disease hypothesis (e.g., psoriasis) and verified related symptoms (e.g., kemerahan, sisik keperakan), enabling efficient differentiation of skin diseases with overlapping symptoms, such as dermatitis, psoriasis, and scabies. The model provided advantages in handling uncertainty, produced accurate diagnoses, and supporting interactive symptom verification. Developed using a knowledge base from credible sources like WHO and AAD, the model was intended to assist in clinical decision-making. The results showed that the backward chaining algorithm effectively improved the accuracy and efficiency of diagnosing skin diseases based on patient-reported symptoms
IMPLEMENTASI ALGORITMA NAÏVE BAYES UNTUK KLASIFIKASI KELAYAKAN PENERIMA PROGRAM INDONESIA PINTAR (PIP) PADA SD NEGERI X M. Yhogha Ismail Ibn Ibrahim; Istiana Ruswita
Jurnal Mahasiswa Ilmu Komputer Vol. 7 No. 1 (2026): Jurnal Mahasiswa Ilmu Komputer March 2026
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ilmukomputer.v7i1.11457

Abstract

Abstrak : Efektivitas distribusi Program Indonesia Pintar (PIP) sangat bergantung pada akurasi proses seleksi di tingkat sekolah. Di SD Negeri X, mekanisme penentuan penerima bantuan masih menghadapi kendala akibat proses verifikasi manual yang cenderung subjektif dan tidak efisien. Penelitian ini mengeksplorasi penggunaan teknik data mining dengan algoritma Naïve Bayes untuk mengotomatisasi klasifikasi kelayakan siswa. Atribut yang diuji meliputi indikator ekonomi dan kondisi sosial keluarga siswa yang diolah menggunakan metode 10-Fold Cross Validation. Temuan penelitian menunjukkan bahwa model Naïve Bayes berhasil mencapai tingkat akurasi sebesar 78,20%. Walaupun nilai recall (52,68%) dan presisi (53,64%) dipengaruhi oleh karakteristik dataset yang ada, penggunaan algoritma ini memberikan landasan pengambilan keputusan yang lebih terukur dan transparan. Implementasi sistem ini diharapkan dapat meminimalisir kesalahan manusia dalam identifikasi penerima bantuan sehingga penyaluran PIP menjadi lebih tepat sasaran. Abstract: The effectiveness of the Indonesia Smart Program (PIP) distribution significantly depends on the accuracy of the selection process at the school level. At SD Negeri X, the mechanism for determining aid recipients still faces challenges due to manual verification processes that tend to be subjective and inefficient. This study explores the application of data mining techniques using the Naïve Bayes algorithm to automate student eligibility classification. The tested attributes include economic indicators and the social conditions of the students' families, which were processed using the 10-Fold Cross-Validation method. The research findings demonstrate that the Naïve Bayes model successfully achieved an accuracy rate of 78.20%. Although the recall (52.68%) and precision (53.64%) values were influenced by the characteristics of the existing dataset, the use of this algorithm provides a more measurable and transparent basis for decision-making. The implementation of this system is expected to minimize human error in identifying aid recipients, thereby ensuring that PIP distribution is more targeted.
Analisis Sentimen Ulasan Digital Menggunakan Naive Bayes dan Pengaruhnya terhadap Keputusan Calon Tamu: Studi Kasus Hotel Santika Premiere Bandara Palembang Istiana Ruswita; M. Yhogha Ismail Ibn Ibrahim
Jurnal Komputasi Vol. 14 No. 1 (2026)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v14i1.350

Abstract

Perkembangan teknologi informasi meningkatkan peran ulasan digital sebagai referensi utama dalam pengambilan keputusan pemesanan hotel. Penelitian ini bertujuan untuk menganalisis sentimen ulasan digital menggunakan metode Naive Bayes serta menguji pengaruhnya terhadap keputusan calon tamu pada Hotel Santika Premiere Bandara Palembang. Data penelitian terdiri dari 15.463 ulasan yang diperoleh dari Google Review dan Traveloka, serta responden kuesioner yang pernah membaca ulasan sebelum melakukan pemesanan. Tahapan penelitian meliputi preprocessing teks, klasifikasi sentimen, dan analisis regresi linier. Hasil menunjukkan bahwa 73,3% ulasan tergolong positif dengan tingkat akurasi model sebesar 88,2%. Analisis regresi menunjukkan bahwa sentimen ulasan digital berpengaruh positif dan signifikan terhadap keputusan calon tamu (p < 0,05) dengan koefisien determinasi (R²) sebesar 0,458. Temuan ini menegaskan bahwa reputasi digital berbasis e-WOM berperan penting dalam membentuk kepercayaan dan niat pemesanan, serta dapat dimanfaatkan sebagai dasar pengambilan keputusan manajerial berbasis data di industri perhotelan.
Co-Authors Allwine Dewi Yulianti Hendri Purnomo Istiana Ruswita Muhammad Galih Ramaputra Sandi Badiwibowo Atim