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All Journal Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi EMITTER International Journal of Engineering Technology JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer Technomedia Journal Jurnal Tekno Insentif Jurnal Agregasi JATI (Jurnal Mahasiswa Teknik Informatika) Competitive Journal Informatic, Education and Management (JIEM) Merpati Jurnal Teknologi dan Manajemen Industri Terapan JEECS (Journal of Electrical Engineering and Computer Sciences) Competitive Journal of Information Technology and Cyber Security Jurnal MediaTIK
Rolly Maulana Awangga, Rolly Maulana
Politeknik Pos Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Transportation Other

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Efficiency in Cloud Computing through Serverless and Green Computing based on Microarchitecture Fahira, Fahira; Awangga, Rolly Maulana; Gopikrishnan, Sundaram
Journal of Information Technology and Cyber Security Vol. 2 No. 1 (2024): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.10479

Abstract

PT Pelindo Multi Terminal is a subholding of PT Pelabuhan Indonesia (Persero), a State-Owned Enter-prise (SOE). PT Pelindo Multi Terminal carries out Kesehatan dan Keselamatan Kerja (K3) or Occupa-tional Health and Safety (OHS) monitoring, which currently still uses manual methods with paper. This method causes problems, such as delays in decision making and the inability to monitor events in real-time. This research aims to overcome these problems by proposing an application called "Portsafe+". Portsafe+ is developed using microservices architecture and micro frontend, with Progressive Web Apps (PWA) as the interface and Google Cloud Function as the backend. Portsafe+ was tested by measuring the response speed of the backend that responds to each request. The test results show that this application improves the response speed with 99% execution time of 880.37 ms. Based on the test results, Portsafe+ successfully overcomes the existing problems. The application of PWA technol-ogy facilitates access and improves the efficiency of OHS management compared to the previously used paper-based manual system.
Sistem Rekomendasi Warna Kontekstual untuk Desain UI/UX Menggunakan Random Forest Agita Nurfadillah; Andarsyah, Roni; Awangga, Rolly Maulana
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 3 (2025): Jurnal Teknologi dan Manajemen Industri Terapan (in press)
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i3.1023

Abstract

Pemilihan warna dalam desain antarmuka pengguna (UI/UX) memegang peranan penting dalam menciptakan pengalaman visual yang konsisten dan menarik. Namun, proses pemilihan warna masih sering didasarkan pada intuisi subjektif. Penelitian ini mengembangkan sistem rekomendasi warna kontekstual berdasarkan kategori aplikasi, menggunakan algoritma Random Forest. Dataset diperoleh dari Dribbble dan Kaggle, mencakup fitur warna RGB, HSL, serta fitur turunan lainnya. Proses pengembangan sistem mengikuti tahapan ADDIE, dimulai dari analisis hingga evaluasi performa. Eksperimen dilakukan dengan tahapan rekayasa fitur, pemilihan fitur, tuning parameter (GridSearchCV), serta penyeimbangan data menggunakan SMOTE. Model terbaik menghasilkan akurasi sebesar 39,2% dan menunjukkan peningkatan pada kategori aplikasi edukatif setelah balancing. Sistem ini diimplementasikan dalam bentuk dashboard interaktif berbasis Streamlit, memungkinkan pengguna memilih kategori aplikasi dan memperoleh rekomendasi warna secara visual. Penelitian ini merupakan kontribusi awal dalam integrasi klasifikasi warna berbasis konteks ke dalam proses desain UI digital, sebagai solusi berbasis data yang dapat mengurangi ketergantungan pada intuisi subjektif.
Machine Learning Models for Predicting Mental Health Indicators Using Digital Physical Activity Data: A Systematic Literature Review Dirga Febrian; Rolly Maulana Awangga
Journal Informatic, Education and Management (JIEM) Vol 7 No 2 (2025): AUGUST
Publisher : STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61992/jiem.v7i2.142

Abstract

This systematic literature analysis examines 40 studies (2020–2025) on the use of machine learning to predict mental health using digital activity data. Two research questions are presented: algorithm performance comparison and model effectiveness factor. Data surveys (43,9%) are a more widely used data collection method. Because of its interpretability, Logistic Regression is the most popular (29.3%), whereas Random Forest (26.8%) is best for performance-interpretability. With a rata-rata accuracy of 80.1% ± 4.2% and an AUC of 87.1% ± 1.8%, XGBoost provides superior performance. The best study achieves an AUC >0,98 through feature engineering that canggih using SHAP and recursive feature elimination. Critical success factors include cermat fitur selection, temporal dinamika, cross-validation, and clinical interpretability. Although machine learning has significant potential, there are still challenges with standardization, generalizability, and real-world implementation. Research in the long term requires longitudinal studies, external validation, and standard protocols to realize this technology's potential in improving mental health outcomes.
Digital Payment Adoption in Crowdfunding Platforms: Systematic Literature Review Gilar Wahibul Azhar; Rolly Maulana Awangga
Journal Informatic, Education and Management (JIEM) Vol 7 No 2 (2025): AUGUST
Publisher : STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61992/jiem.v7i2.143

Abstract

Digital payment adoption on crowdfunding platforms has emerged as a significant research area in the field of financial technology. This study presents a systematic literature review of 40 peer-reviewed articles published between 2020 and 2025, using the PRISMA 2020 framework to analyze digital payment adoption patterns in crowdfunding platforms. Three main research questions are addressed: (1) factors influencing user preferences between traditional digital payments and cryptocurrency, (2) mechanisms by which payment technologies enhance platform security and trust, and (3) the most effective research methodologies for analyzing digital payment adoption. From an initial pool of 847 articles across four major databases (Scopus, Web of Science, IEEE Xplore, and ScienceDirect), 40 studies met the inclusion criteria. The analysis reveals that trust is the dominant factor (80%), followed by ease of use (70%), and social influence (55%). The Technology Acceptance Model (TAM) is the most commonly used theoretical framework (47.5%), with Structural Equation Modeling as the primary analytical method (32.5%), and surveys employed in 65% of the studies. QR-based mobile payments show the highest adoption rates (78%) due to perceived ease of use and the influence of the COVID-19 pandemic. Cryptocurrency adoption varies by demographics, with Millennials and Generation Z demonstrating 40% higher acceptance compared to older generations. Blockchain-based payment systems significantly improve transaction security (up to 85%) through smart contracts and decentralized architecture, yet face barriers related to technical complexity and regulatory uncertainty. These findings offer practical implications for platform developers, policymakers, and fintech stakeholders, including trust-centered design, user-friendly blockchain integration, and digital financial literacy programs. Future research should adopt standardized methodologies and longitudinal approaches to better understand long-term adoption dynamics.
Prediksi dan Koreksi Error Servo Base Motor pada Robot Tangan Berbasis IoT Menggunakan Model Linear Regresi Maulana, Farhan Rizki; Setyawan, Muhammad Yusril Helmi; Awangga, Rolly Maulana
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13818

Abstract

Kebutuhan akan presisi pergerakan pada lengan robot berbasis Internet of Things (IoT) memunculkan tantangan terkait deviasi sudut antara posisi target dan aktual pada motor servo. Penelitian ini mengusulkan pendekatan regresi linier untuk memprediksi dan mengoreksi kesalahan sudut pada motor servo bagian base. Model dibangun menggunakan data simulasi yang mencakup sudut target, sudut aktual (disimulasikan), dan jarak objek dari sensor ultrasonik. Nilai koreksi dihitung berdasarkan selisih sudut ditambah komponen acak dan non-linear berbasis jarak, yang ditambahkan sebagai label target. Model dilatih menggunakan metode Ordinary Least Squares dan dievaluasi menggunakan metrik MAE, MSE, dan R². Hasil menunjukkan MAE sebesar 3.49°, MSE sebesar 19.49, dan R² sebesar 0.9808. Simulasi koreksi menurunkan rata-rata error dari 9.97° menjadi 1.17°. Visualisasi melalui scatter plot, histogram, dan boxplot menunjukkan peningkatan presisi dan stabilitas sistem. Model ini mampu meningkatkan akurasi pergerakan servo secara signifikan tanpa penambahan sensor atau modifikasi perangkat keras, menjadikannya solusi prediktif yang efisien untuk sistem robotik tertanam dengan kontrol terbuka.   Kata kunci: robot tangan IoT, koreksi sudut servo, regresi linier, akurasi pergerakan, simulasi kendali terbuka
Enhancing OCR Accuracy on Indonesian ID Cards Using Dual-Pipeline Tesseract and Post-Processing Reksiyano, Rendy Dwi; Pane, Syafrial Fachri; Awangga, Rolly Maulana
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.3

Abstract

Manual transcription of data from Indonesian identity cards (KTP) remains prevalent in public institutions, often resulting in inefficiencies and human errors that compromise data accuracy. While Optical Character Recognition (OCR) technologies such as Tesseract have been widely adopted. However, the performance on KTP images is still inconsistent due to non-uniform layouts, low contrast, and background noise. This study proposes a dual-pipeline OCR framework designed to enhance the recognition accuracy of Indonesian KTPs under real-world conditions. First, the pipeline performs static region segmentation based on predefined Regions of Interest (ROI), then uses dynamic keyword heuristics to locate text adaptively across varying layouts. The outputs of both pipelines are merged through a voting and regex-based post-processing mechanism, which includes character normalization and field validation using predefined dictionaries. Experiments were conducted on 78 annotated KTP samples with diverse resolutions and quality of images. Evaluation using Character Error Rate (CER), Word Error Rate (WER), and field-level accuracy metrics resulted in an average CER of 69.82%, WER of 80.20%, and character-level accuracy of 30.18%. Despite moderate performance in free-text areas such as address or occupation, structured fields achieved higher accuracy above 60%. The method runs efficiently in a CPU-only environment without requiring large annotated datasets, demonstrating its suitability for low-resource OCR deployment. Compared to conventional single-pipeline approaches, the proposed framework improves robustness across heterogeneous document layouts and illumination conditions. These findings highlight the potential of lightweight, rule-based OCR systems for practical e-KYC digitization and form a foundation for integrating deep-learning-based layout detection in future research.
Implementasi Face Recognition Untuk Mengakses Ruangan Alwan Suryansah; Roni Habibi; Rolly Maulana Awangga; Rd. Nuraini Siti Fatonah
Jurnal MediaTIK Volume 3 Issue 3, September (2020)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v3i3.1563

Abstract

Teknologi biometrik yang berkembang saat ini seperti pengenalan sidik jari, pengenalan retina mata dan sebagainnya mengharuskan seseorang memposisikan tubuh pada posisi yang sesuai dengan posisi kamera yang membuat teknologi ini terkesan kaku, untuk itu sebuah sistem identifikasi lebih fleksibel dan bersifat otomatis dapat mencegah pencurian. Pada penelitian ini dirancang sebuah sistem keamanan yang dapat mengakses pintu masuk menggunakan face recognition berbasis Arduino Uno. Salah satu solusi keamanan dalam melakukan ototentikasi adalah menggunakan bagian tubuh manusia yaitu wajah. Sistem dapat mendeteksi objek wajah sebagai citra dari kamera. Setelah objek terdeteksi, sistem akan melakukan pencocokan wajah dengan citra wajah yang terdapat pada database sistem. Citra akan diproses dengan menggunakan metode LBPH. Sistem ini merupakan penerapan Smart Gate dalam sistem keamanan dengan tujuan dapat mengamankan ruangan yang bersifat pribadi/ private dengan menggunakan biometric fece recognition, penggunaan komponen-komponen elektronik dapat digunakan sebagai alat yang dapat mengenal karakter wajah agar dapat mengakses ruangan, dan dapat mengimplementasikan algoritma LBPH dalam pengenalan karakter wajah pada sistem yang akan di bangun. Hasil dari penelitian ini adalah kendali privilege pada Smart Gate menggunakan Arduino Uno dan biometric face recognition dapat meningkatkan keamanan pada ruangan, dapat memaksimalkan penggunaan komponen-komponen elektronik dan dapat mengimplementasikan algoritma LBPH
Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity Awangga, Rolly Maulana; Pane, Syafrial Fachri; Tunnisa, Khaera
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (209.522 KB) | DOI: 10.24003/emitter.v7i1.317

Abstract

Indonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision (Fmadm) and K-Means Clustering method in managing Operational Plan activities. Fmadm to select the best alternative from a number of alternatives, alternatives from this study proposed activity proposals, then ranking to determine the optimal alternative. The K-Means Clustering Method to obtain cluster values for alternatives on the criteria for activity dates, types of activities, and activity ceilings. The last iteration of the Euclidian distance calculation data on k-means shows that alternatives that have the smallest centroid value are important proposal criteria and the largest centroid value is an insignificant proposal criteria. The results of the collaboration of the Fmadm and K-Means Clustering methods show the optimal ranking of activities (proposal activities) and the centroid value of each alternative.
GURILEM : A Novel Design of Customer Rating Model using K-Means and RFM Awangga, Rolly Maulana; Pane, Syafrial Fachri; Wijayanti, Diana Asri
EMITTER International Journal of Engineering Technology Vol 7 No 2 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i2.325

Abstract

A rating system or reviews are generally used to assist in making decisions. Rating system widely used as a technique in the recommendation of one of them used by the customer, as in determining the resort to be used. However, the credibility of the rating looks vague because the rating could only represent some points of service. So that customer preference with each other is very different. Personalized recommendation systems offer more personalized advice, precisely knowing the preferences or tastes of the customers. Especially for customers who have a transaction history or reservation as at their resorts provide good information used by managers to design a recommendation model for their customers. In this study aims to create a model of resort recommendations based on a rating of frequency. This frequency is the number of resort use by the customer within the specified time frame. With the frequency can represent the preferences of customers. The RFM method is used to measure the reservation frequency value of the customer. The K-Means method is used to categorize customer data with its frequency and classify the type of resort. Recommendation resort to the customer based on the dominant use in one of the resort types. The recommended type of resort based on the similarity between the types of resorts used with other types of resorts.
Co-Authors Adji Suradji Muhammad Ady Muzwardi Agita Nurfadillah Akik Hidayat Alwan Suryansah Aminuyati Andarsyah, Roni Arjuna Rizaldi Asyhari, Mochamad Yusuf Atje Setiawan Abdullah Bayu Rahmad Azhari Cahya Kurniawan Cartono Cartono Dani Leonidas Sumarna Dinda Majesty Dirga Febrian Dzikri Ahmad Ghifari Esi Vidia Rahcmadani Fahira, Fahira Fatonah, Rd. Nuraini Siti Fazriyah, Nurul Gatto, Petrolina Anastasia Gilang Romadhanu Tartila Gilar Wahibul Azhar Gopikrishnan, Sundaram Habibi, Roni - Intan Nurma Yulita, Intan Nurma Iping Supriana Suwardi Khaera Tunnisa, Khaera Kurniawan, Alit Fajar Kurniawan, Cahya Maulana, Farhan Rizki Maulyanda, Maulyanda Muchamad Innal Kariem Muhammad Firman Kahfi Muhammad Wahyu Ardi Muhammad Yusril Helmi Setyawan Muhammad Yusril Helmi Setyawan Nadia Ayu Lestari Nisa Hanum Harani Nuha Hanifatul Khonsa' Prianto, Cahyo Rd. Nuraini Siti Fatonah Reksiyano, Rendy Dwi Restiyana Dwi Astuti Rezka Afriyanti Roni Habibi Roni Habibi Rony Andarsyah Rudi Rosadi Seta Permana Setiawan Assegaf Setyawan, Muhammad Yusril Helmi Sri Purwani Suryansah, Alwan - Syafrial Fachri Pane Syafrial Fachri Pane Syafrial Fachri Pane, Syafrial Fachri Tamadara Hilman Tasya Wiendhyra Tri Angga Dio Simamora Vebi Natasya, Salsabila Wijayanti, Diana Asri