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All Journal Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Education Technology JURTEKSI Infotekmesin Journal of Information Systems and Informatics Jurnal Sistem Komputer dan Informatika (JSON) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Pengabdian Mitra Masyarakat (JPMM) Electronic Journal of Education, Social Economics and Technology Bulletin of Social Informatics Theory and Application CSRID Southeast Asia Journal on Open and Distance Learning
Rujianto Eko Saputro
Universitas Amikom Purwokerto
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Improving Dolan Banyumas App: A Design Thinking Approach to Enhance Tourism Services Indriyani, Ria; Saputro, Rujianto Eko
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.991

Abstract

The Dolan Banyumas application is a digital step to support tourism in Banyumas Regency. However, the results of observations and evaluations conducted show that the design of the user interface (UI) and user experience (UX) of this application is still less than optimal, with incomplete information, confusing navigation, and unattractive application design. This study aims to redesign the application using the Design Thinking approach, which consists of five stages: empathize, define, ideate, prototype, and test stages. Usability was assessed using the System Usability Scale (SUS) with a 10-question Likert scale survey distributed to 30 respondents. Evaluation results using the System Usability Scale (SUS) method showed an increase in the average score from 63 to 81.42, which classifies the app into the “Good” and “Acceptable” categories. Improvements include easier-to-use navigation, more complete tourist information, and the addition of new features such as ticket booking and bus tour maps. The user satisfaction rate increased from 60% to 87%, while efficiency rose by 30%. Based on Net Promoter Score (NPS), the app is categorized as “Promoter.” The Design Thinking approach proved effective in improving the quality of user experience.
Eksplorasi Model Hybrid Transformer-Latent Semantic Analysis (LSA) Untuk Pemahaman Konteks Teks Berita Berbahasa Indonesia Sofa, Nur; Utomo, Fandy Setyo; Saputro, Rujianto Eko
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 5 (2025): JPTI - Mei 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.662

Abstract

Kemajuan teknologi informasi meningkatkan konsumsi berita digital, menuntut sistem Natural Language Processing (NLP) yang efisien dalam memahami bahasa Indonesia. Namun, kompleksitas morfologi bahasa Indonesia menyulitkan model NLP konvensional dalam menangkap makna semantik secara akurat. Model deep learning seperti Transformer unggul dalam menangkap hubungan semantik lokal, sementara Latent Semantic Analysis  (LSA) memahami hubungan semantik global melalui reduksi dimensi. Namun, Transformer membutuhkan sumber daya komputasi besar, sedangkan LSA cenderung kehilangan konteks sintaksis. Penelitian ini mengusulkan model hybrid yang mengintegrasikan Transformer dan LSA untuk meningkatkan pemahaman teks berita Indonesia serta mengevaluasi performanya dibandingkan model individu dan deep learning yang lebih kompleks. Evaluasi menggunakan Accuracy, F1-Score, BLEU Score, ROUGE, dan Perplexity. Model hybrid mencapai akurasi 0.510760 dan F1-Score 0.520486, lebih baik dari LSA dan Transformer, tetapi masih tertinggal dari BERT dan GPT. Meski demikian, model hybrid lebih efisien secara komputasi dibandingkan model deep learning yang lebih kompleks. Penelitian ini berkontribusi pada pengembangan NLP bahasa Indonesia dengan pendekatan yang lebih ringan. Implikasi penelitian menunjukkan perlunya dataset lebih besar dan teknik embedding lebih maju. Penelitian selanjutnya dapat mengeksplorasi integrasi model hybrid dengan BERT atau GPT, serta teknik embedding lain seperti word2vec atau fastText untuk meningkatkan pemahaman semantik.
Technology Acceptance Model TAM using Partial Least Squares Structural Equation Modeling PLS- SEM Latif, Imam Sofarudin; Saputro, Rujianto Eko; Barkah, Azhari Shouni
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1104

Abstract

The rapid advancement of digital technologies necessitates a deeper focus on user acceptance and satisfaction, particularly within the framework of the Technology Acceptance Model (TAM), analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This systematic literature review examines 36 articles published between 2020 and 2025, revealing that factors such as trust, system quality, perceived enjoyment, service quality, and technological self-efficacy significantly influence user satisfaction. These external variables enhance the explanatory power of TAM, providing a richer understanding of user interactions with digital platforms such as e-commerce, e-learning, and mobile banking. PLS-SEM's ability to manage model complexity, non-normal data distributions, and interrelated constructs further validates its suitability for this research. The findings suggest that integrating these external factors improves both the theoretical and practical aspects of TAM in the context of technology adoption. Future research could explore additional industry-specific applications for emerging technologies.
Penerapan Algoritma FP-Growth Untuk Menentukan Pola Penjualan Najah Mart Serli, Serli; Saputro, Rujianto Eko
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.1-19

Abstract

This research aims to apply the FP-Growth algorithm at Najah Mart with a focus on identifying significant sales patterns. By recognizing products that are frequently purchased together, this study is expected to help Najah Mart optimize inventory management, enhance customer shopping experiences, and design more efficient marketing strategies. The methodology employed in this study includes collecting sales transaction data and preprocessing to ensure optimal data quality. Subsequently, the FP-Growth algorithm is applied to uncover patterns and associations within the sales data. The analysis focuses on identifying strong product correlations based on customer purchasing patterns. The research findings reveal relevant and significant purchasing patterns, such as combinations of specific products frequently bought together. These insights can be utilized to improve marketing strategies and inventory management. This study not only provides practical benefits for Najah Mart in enhancing operational effectiveness and supporting strategic decision-making but also contributes to the advancement of knowledge by expanding the application of the FP-Growth algorithm in the retail sector, particularly in sales data analysis to support business growth.
Optimalisasi UX Aplikasi Penyewaan Peralatan Bayi dengan Design Thinking dan Evaluasi SUS Ismail, Dimas Shafa Malik; Saputro, Rujianto Eko
Jurnal Sistem Komputer dan Informatika (JSON) Vol 6, No 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8657

Abstract

Penyewaan perlengkapan bayi menjadi solusi praktis bagi orang tua yang membutuhkan alat dalam jangka waktu terbatas. Namun, dalam praktiknya, masih banyak layanan penyewaan yang berjalan secara manual dan belum efisien, sehingga menimbulkan kendala seperti keterbatasan informasi, proses pemesanan yang rumit, serta waktu layanan yang tidak fleksibel. Penelitian ini bertujuan untuk merancang dan meningkatkan kualitas antarmuka pengguna (UI) serta pengalaman pengguna (UX) melalui pengembangan aplikasi mobile berbasis metode Design Thinking, guna meningkatkan efisiensi layanan dan kepuasan pengguna. Proses perancangan mengikuti lima tahap, yaitu Empathize, Define, Ideate, Prototype, dan Test, dengan diawali wawancara serta observasi untuk memahami kebutuhan pengguna, kemudian dilanjutkan dengan perancangan wireframe, alur navigasi, hingga pengujian prototipe low-fidelity dan high-fidelity. Evaluasi dilakukan dengan metode System Usability Scale (SUS) terhadap 15 responden yang merepresentasikan target pengguna. Hasil pengujian menunjukkan skor rata-rata SUS sebesar 77,17, yang menandakan aplikasi memiliki tingkat kegunaan tinggi dan respons positif dari pengguna. Temuan ini membuktikan bahwa pendekatan Design Thinking efektif dalam menghasilkan desain aplikasi penyewaan yang intuitif, ramah pengguna, dan mampu meningkatkan pengalaman digital pelanggan secara signifikan.
Effectiveness of The Gamified LMS Platform on The Level of Online Course Completion Rujianto Eko Saputro; Wiga Maulana Baihaqi; Sarmini
Southeast Asian Journal on Open and Distance Learning Vol. 1 No. 01 (2023): Strategies for Cultivating Active Learning in Online Environment
Publisher : SEAMEO SEAMOLEC

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

Abstract

Gamified Massive Open Online Courses (G-MOOCs) is a Learning Management System (LMS) platform built on the gamification framework (MARC Gamification Framework) that has been proposed in previous studies based on various aspects of game elements, social learning, motivation and interactive theory learning environment (ILE). G-MOOC is a background element that can motivate them when taking courses in online learning. This program is intended to increase the intrinsic motivation of participants in completing their courses. Tests are carried out using the experimental group method using two indicators, namely the level of mastery of the course (performance) and the status of learning courses (Done/Not Done). To produce data from used indicators, researchers gave four weeks to take the course. The courses are compared with the LMS platform which has no gamification element (SIMOOC), the performance indicators are tested in the participant values between the G-MOOCs platform and the SIMOOC platform. Based on the results of the test, the platform is a platform that is better and different compared to the SIMOOC platform. Judging from the status of the participants, out of 71 participants who took the course on the G-MOOC platform there were 46.5% which were declared completed, while on the SIMOOC platform only 7% had completed status. It can be concluded that the G- MOOC platform can increase the effectiveness of the value courses compared to the SIMOOC platform.
Analisis Tingkat Akurasi Metode Naive Bayes dan Random Forest dalam Prediksi Penjualan Emas Pandu W, Muhammad Arfianto; Saputro, Rujianto Eko; Purwadi, Purwadi; Rohmah, Umdah Aulia
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 7 (2025): JPTI - Juli 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.732

Abstract

Penelitian ini bertujuan untuk menganalisis tingkat akurasi metode Naive Bayes dan Random Forest dalam prediksi penjualan emas, yang memainkan peran penting dalam perencanaan investasi dan strategi bisnis di sektor pertambangan, terutama dalam menghadapi volatilitas pasar yang tinggi. Metode penelitian yang digunakan adalah narrative literature review, yang berfokus pada perbandingan dan analisis teori-teori yang ada sebelumnya. Pendekatan ini memungkinkan peneliti untuk mengevaluasi, mengidentifikasi, dan menganalisis literatur yang relevan serta menyarikan temuan-temuan penting yang dapat memberikan wawasan lebih dalam tentang topik yang dikaji. Dalam konteks ini, Naive Bayes dan Random Forest digunakan untuk meramalkan fluktuasi harga emas dan perilaku pembelian produk, dengan fokus pada pengoptimalan strategi pemasaran. Hasil analisis menunjukkan bahwa Naive Bayes efektif dalam mengidentifikasi produk yang diminati dan memfasilitasi perencanaan pemasaran. Namun, Random Forest menunjukkan keunggulan dalam prediksi yang lebih kompleks, seperti perilaku repeat order pelanggan, berkat kemampuannya untuk menangani data variatif dan mengurangi risiko overfitting melalui pendekatan ensemble yang menggabungkan banyak pohon keputusan. Meskipun terdapat sedikit penurunan akurasi pada data pengujian, Random Forest tetap dapat menghasilkan prediksi yang akurat dan robust. Oleh karena itu, kedua metode ini memberikan kontribusi signifikan dalam merancang strategi bisnis dan keputusan investasi yang lebih akurat, dengan Random Forest lebih unggul dalam menghadapi data yang lebih kompleks. Kontribusi penelitian ini yakni memberikan landasan teoretis tentang penerapan algoritma pembelajaran mesin di sektor pemasaran berbasis data, serta menjadi panduan bagi praktisi dan peneliti dalam memilih metode prediktif yang tepat.
An Analisis Penerimaan Pengguna Quizizz pada SMPN 3 Susukan Banjarnegara dengan Menggunakan Pendekatan Technology Acceptance Model (TAM) yang diperluas Safitri Maharani, Titi; Eko Saputro, Rujianto; Setyo Utomo, Fandy
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1017

Abstract

Pemanfaatan teknologi dalam pendidikan telah mengalami perkembangan pesat, terutama dalam metode evaluasi pembelajaran. Salah satu platform yang banyak digunakan adalah Quizizz, sebuah aplikasi berbasis gamifikasi yang memungkinkan kuis interaktif secara daring. Quizziz menawarkan berbagai keunggulan seperti fleksibilitas, umpan balik instan, dan pengalaman belajar yang lebih menarik, akan tetapi pengguna masih menghadapi berbagai tantangan adopsi terhadap teknologi. Penelitian ini bertujuan untuk menganalisis penerimaan penggunaan Quizizz dalam pembelajaran menggunakan pendekatan Technology Acceptance Model (TAM). Data dikumpulkan dari 222 responden, yang terdiri dari siswa dan guru yang aktif menggunakan Quizizz dalam pembelajaran. Analisis data dilakukan menggunakan metode Partial Least Squares Structural Equation Modeling (PLS-SEM) dengan perangkat lunak SmartPLS untuk menguji validitas, reliabilitas, serta hubungan antar variabel dalam model penelitian ini. Hasil analisis kuantitatif menunjukkan bahwa seluruh konstruk dalam model memiliki reliabilitas dan validitas yang sangat baik, dengan nilai Cronbach’s Alpha dan Composite Reliability masing-masing berada di atas 0,70 dan 0,90, serta nilai AVE di atas 0,50, yang menandakan konsistensi internal dan validitas konvergen yang memadai. Hasil uji model struktural menunjukkan bahwa sikap terhadap penggunaan (Attitude Toward Using/AM) memiliki pengaruh paling kuat dan signifikan terhadap niat perilaku (Behavioral Intention/BI) dengan nilai koefisien ? = 0,744 dan p < 0,001. Selain itu, efikasi diri (Self-Efficacy/SE) dan kondisi yang memfasilitasi teknologi (Technology Facilitating Conditions/TF) berpengaruh signifikan terhadap persepsi kemudahan penggunaan (Perceived Ease of Use/PEU), masing-masing dengan ? = 0,340 dan ? = 0,586 (p < 0,001). Kualitas pengetahuan (Knowledge Quality/KQ) berpengaruh positif terhadap persepsi kegunaan (Perceived Usefulness/PU), sementara kualitas informasi (Information Quality/IQ) justru menunjukkan pengaruh negatif yang signifikan terhadap PU. Di sisi lain, hubungan antara PU dan BI, PEU dan BI, serta Social Influence (SI) terhadap BI tidak menunjukkan signifikansi statistik. Hasil ini menunjukkan bahwa penerimaan Quizizz lebih ditentukan oleh faktor personal pengguna, khususnya sikap dan kepercayaan diri, dibandingkan dengan aspek fungsional platform atau dorongan eksternal. Penelitian ini merekomendasikan pengembangan fitur yang lebih ramah pengguna serta optimalisasi pelatihan bagi guru dan siswa untuk memaksimalkan manfaat dari platform ini.
Comparative Analysis of ArUco Marker Detection Techniques Using Adaptive Thresholding, CLAHE, and Kalman Filter for Smart Cane Applications Yulianto, Koko Edy; Saputro, Rujianto Eko; Utomo, Fandy Setyo
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4883

Abstract

This study aims to analyze and compare the effectiveness of three image processing techniques  Adaptive Thresholding, CLAHE, and Kalman Filter in enhancing the performance of ArUco marker detection for a smart cane system designed for visually impaired individuals at SLB Kuncup Mas Banyumas. The evaluation method includes detection accuracy, marker position precision, and computational time required by each technique under two different lighting conditions: daytime and nighttime. The results show that all three image processing techniques successfully achieved a 100% detection accuracy for ArUco markers. However, significant differences were observed in computational time, with Kalman Filter demonstrating the fastest processing speed, making it the most efficient option for real-time applications requiring quick response. CLAHE and Adaptive Thresholding performed better in uneven lighting conditions, although they required longer computational times. Kalman Filter is therefore recommended for marker-based navigation systems in environments demanding fast response times, while CLAHE and Adaptive Thresholding are better suited for settings with variable lighting intensities. The implications of these findings open opportunities for developing adaptive navigation systems capable of dynamically adjusting image preprocessing methods based on real-time environmental conditions. This study contributes practically to the advancement of assistive navigation technologies for visually impaired individuals, particularly in the development of visual marker-based detection systems. The results also provide a useful guideline for selecting appropriate image processing techniques according to environmental characteristics, thereby improving the accuracy and adaptability of navigation systems across diverse lighting conditions and operational environments.
Lightweight Visual Detection System for Object Identification with ArUco Markers in Resource-Constrained Environments Yulianto, Koko Edy; Saputro, Rujianto Eko; Utomo, Fandy Setyo
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.757

Abstract

Object detection is a fundamental task in computer vision systems used in robotics, automation, and real-time tracking applications. However, implementing accurate and responsive detection on low-cost embedded hardware presents significant challenges due to limited processing power and environmental variability. This study aims to evaluate the performance of an object detection system utilizing ArUco markers on a Raspberry Pi-based platform. The research investigates the system’s ability to detect and identify three types of physical objects—a plastic bottle, a flower pot, and a glass cup—as well as the performance when all three objects are present simultaneously. The system was tested under controlled static conditions using a camera to capture real-time video streams. Detection time, computation time, and accuracy were measured across five consecutive frames for each scenario. Results show that the system achieved consistent detection and processing times below 0.14 seconds per frame, meeting real-time performance criteria. Detection accuracy across all individual object scenarios exceeded 91%, with the highest accuracy recorded in the multi-object scenario at 93.44%. No detection failures occurred during the experiments, and frame-by-frame analysis confirmed temporal stability. These findings indicate that marker-based detection is a reliable and efficient approach for real-time applications in structured environments. The study provides a foundation for extending the system to more dynamic conditions in future research.
Co-Authors Adam Prayogo Kuncoro Adiatma, Febriansyah Husni Adiya, Az Zahra Dwi Nur Anugerah Bagus Wijaya Armeyta Putri Tanzilla Arum Vika Ndari Aulia Hamdi Azhari Shouni Barkah Bagaskoro, Galih Berlilana Berlilana Cahyo, Samsul Dwi Chyntia Raras Ajeng Widiawati Dani Arifudin Deasy Komarasary Dhanar Intan Surya Saputra Dhanar Intan Surya Saputra Diah Ratna Febrianti Ely Purnawati Embong Octavianto Fandy Setyo Utomo Fatudin, Arif Faturama, Rafi Fery Afriansyah Filanzi, Shendy Giat Karyono Hanif Hidayatulloh Hasna Salsa Dhia Ikmah Ikmah Ilham, Rifqi Arifin Indriyani, Ria Inka Saputri Irwansyah Munandar Ismail, Dimas Shafa Malik Junianto, Haris Kusuma, Bagus Adhi Latif, Imam Sofarudin Maharani, Revalyna Octavia Maulana Baihaqi, Wiga Mohd. Hafiz Zakaria Nanjar, Agi Nia Millatul Izza Nurfaizi, Maulana Pandu W, Muhammad Arfianto Prasetyo, Agung Pungkas Subarkah Purwadi Purwadi Putranto, R. Vitto Mahendra Radeta Tea Makdatuang Ria Indriyani Rio Fadly Ramadhan Rizqi Aulia Widianto Rohmah, Umdah Aulia Rosana Fadila Sari safitri feriawan, Titi Safitri Maharani, Titi Salam, Sazilah Samsul Aimah Saputra , Dhanar Intan Surya Saputra, Alfin Nur Aziz Sari, Rida Purnama Sarmini Sarmini - Sarmini Sarmini Sarmini Sazilah Salam Serli, Serli Sofa, Nur Sri Hartini Suliswaningsih Syahputra, Akhmal Angga Tarwoto, T Toni Anwar Turino, Turino Wahyuni, Irmawati Tri Wenti Risma Damayanti Wiga Maulana Baihaqi Yuli Purwati Yulianto, Koko Edy