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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.
Pemanfaatan Teknologi untuk Meningkatkan Pembelajaran Inklusif bagi Dosen Fakultas Ilmu Komputer Universitas Amikom Purwokerto Rujianto Eko Saputro; Arif Mu'amar Wahid; Novita Eka Ramadhani; Lughri Wijaya Pamungkas
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol. 6 No. 4 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v6i4.2629

Abstract

Pengabdian ini menjawab isu kurangnya pemahaman dan keterampilan dosen di Fakultas Ilmu Komputer Universitas AMIKOM Purwokerto terkait implementasi teknologi untuk mendukung pendidikan inklusif, khususnya bagi mahasiswa dengan Gangguan Spektrum Autisme (ASD) dan disabilitas penglihatan. Tujuan kegiatan ini adalah untuk meningkatkan kompetensi dosen dalam memanfaatkan teknologi bantu, seperti aplikasi pembelajaran multimedia, melalui webinar dan workshop yang dipimpin oleh Ts. Syariffanor Hisham dari Universiti Teknikal Malaysia Melaka (UTeM). Metode yang digunakan adalah pelatihan partisipatif dengan evaluasi melalui kuesioner umpan balik. Hasil menunjukkan respons peserta yang sangat positif, dengan nilai rata-rata evaluasi di atas 4.0 pada skala 1-5 untuk semua aspek. Ini membuktikan bahwa program berhasil memberikan wawasan baru dan meningkatkan pemahaman peserta, sekaligus menunjukkan relevansi topik dan efektivitas kolaborasi internasional.
Klasifikasi Spam Bahasa Indonesia dengan IndoBERT dan XLM-RoBERTa: Evaluasi Pooling, Stride, dan Late-Fusion Darmono, Darmono; Saputro, Rujianto Eko; Barkah, Azhari Shouni
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.8034

Abstract

Spam detection for Indonesian short messages such as SMS and email remains challenging due to lexical variation, character obfuscation, and class imbalance. This study provides a systematic evaluation to determine the most balanced configuration between accuracy and efficiency for Indonesian spam filtering. We compare two pretrained backbones (IndoBERT and XLM RoBERTa), along with representation strategies (truncation versus chunking), summarization schemes (pooling), and feature fusion approaches. The system follows a feature based design with an emphasis on simplicity, and is assessed using F1 Macro, spam class recall, AUPRC (Area Under the Precision Recall Curve), and efficiency metrics in terms of embedding build time and training latency. Results indicate that IndoBERT achieves superior binary classification performance with high efficiency, while XLM RoBERTa slightly outperforms on AUPRC, making it more suitable for risk ranking scenarios. Truncation combined with mean pooling consistently yields stable results. Although late fusion only provides marginal improvements, it remains relevant as it highlights the potential of domain specific signals to enhance robustness under heavy obfuscation. The final recommendation for production is IndoBERT with truncation, mean pooling, and embedding only. Limitations include the focus on short messages and the lack of evaluation under extreme obfuscation. Future work should explore character level augmentation, cross domain evaluation, and cost sensitive threshold tuning.
Pendampingan dan Pelatihan Metodologi Penelitian Kuantitatif Bagi Mahasiswa Pusat Studi MGM Prasetyo, Agung; Ndari, Arum Vika; Tanzilla, Armeyta Putri; Saputro, Rujianto Eko; Wijaya, Anugerah Bagus; Hamdi, Aulia; Suliswaningsih, Suliswaningsih
Jurnal Pengabdian Mitra Masyarakat (JPMM) Vol 5, No 2: Oktober (2023)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/jpmm.v5i2.2820

Abstract

AMIKOM University in Purwokerto, through its 6 study centers, requires and trains each student to write scientific papers, such as scientific reports, articles, theses, and scientific journals. The survey results agreed upon by the partners highlight several issues in this program. These issues include students' lack of understanding regarding the core issues in research, insufficient preparedness in creating suitable materials, theories, and references before designing a research proposal, and ambiguity in formulating research problems. Students also lack understanding of the research methodology they will use and are not accustomed to writing and citing scientifically. Many students still do not understand research methodology and are less skilled in designing research proposals. The learning process in lectures often feels monotonous because they are dominated by speeches and Q&A sessions, and students are not actively involved enough in searching and digging for information or theories. Only a few students get the opportunity to participate in guided exercises in formulating problems, selecting theories relevant to the problem, and choosing research methodology. This becomes a challenge that must be addressed in this program. The solution to these problems is to conduct training and mentoring for students to improve the quality of student research. In implementing this service, we use the Direct Action Method. This method includes several steps, namely Diagnosing, Action Planning, Action Taking, Evaluating, and Learning. These steps refer to the diagnostic process, action planning, action implementation, evaluation, and learning. This service has been successful in increasing the capacity of student human resources and students' abilities in research, which will benefit students in the future.
Co-Authors Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adiatma, Febriansyah Husni Adiya, Az Zahra Dwi Nur Afriansyah, Fery Aimah, Samsul Arif Mu'amar Wahid Aulia Hamdi Azhari Shouni Barkah Bagaskoro, Galih Berlilana Berlilana Cahyo, Samsul Dwi Chyntia Raras Ajeng Widiawati Damayanti, Wenti Risma Dani Arifudin Darmono Deasy Komarasary Dhanar Intan Surya Saputra Dhanar Intan Surya Saputra Ely Purnawati Ely Purnawati, Ely Embong Octavianto Fandy Setyo Utomo Fatudin, Arif Faturama, Rafi Febrianti, Diah Ratna Fery Afriansyah Filanzi, Shendy Giat Karyono Hasna Salsa Dhia hidayatulloh, hanif Ikmah Ikmah Ikmah, Ikmah Ilham, Rifqi Arifin Indriyani, Ria Irwansyah Munandar Ismail, Dimas Shafa Malik Junianto, Haris Kusuma, Bagus Adhi Latif, Imam Sofarudin Lughri Wijaya Pamungkas Maharani, Revalyna Octavia Maulana Baihaqi, Wiga Millatul Izza, Nia Mohd. Hafiz Zakaria Munandar, Irwansyah Nanjar, Agi Ndari, Arum Vika Nia Millatul Izza Novita Eka Ramadhani Nurfaizi, Maulana Octavianto, Embong Pandu W, Muhammad Arfianto Prasetyo, Agung Pungkas Subarkah Purwadi Purwadi Putranto, R. Vitto Mahendra Radeta Tea Makdatuang Ramadhan, Rio Fadly Ria Indriyani Rizqi Aulia Widianto Rohmah, Umdah Aulia Rosana Fadila Sari safitri feriawan, Titi Salam, Sazilah Salsa Dhia, Hasna Samsul Aimah Saputra , Dhanar Intan Surya Saputra, Alfin Nur Aziz Saputri, Inka Sari, Rida Purnama Sarmini Sarmini - Sarmini Sarmini Sarmini Sazilah Salam Serli, Serli Sofa, Nur Sri Hartini Subarkah, Pungkas Suliswaningsih, Suliswaningsih Syahputra, Akhmal Angga Tanzilla, Armeyta Putri Tarwoto, T Tea Makdatuang, Radeta Titi Safitri Maharani Toni Anwar Turino, Turino Wahyuni, Irmawati Tri Wenti Risma Damayanti Wiga Maulana Baihaqi Wijaya, Anugerah Bagus Yuli Purwati Yulianto, Koko Edy