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All Journal Infotech Journal Jurnal Sains Teknologi dan Sistem Informasi Jurnal Impresi Indonesia Journal Research of Social Science, Economics, and Management Blockchain Frontier Technology (BFRONT)
Sigit Anggoro
Universitas Jenderal Achmad Yani
Religion Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences

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SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU TERBAIK PADA SMK NEGERI 1 MAJA MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) Hary Rizqi Ramadhani; Gunawan Abdillah; Sigit Anggoro
INFOTECH journal Vol. 10 No. 2 (2024)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v10i2.10097

Abstract

A decision support system is a system using a model that is built to help solve semi-structured problems. The Analytical Hierarchy Process (AHP) method is a method for solving a complex, unstructured situation into several components in a hierarchical arrangement, by giving a subjective value about the relative importance of each variable, and determining which variable has the highest priority in order to influence the outcome. this situation. The results of accuracy testing can be concluded that testing data on civil servant teachers which was carried out by comparing the data of civil servant teachers selected by the principal and using the system obtained an accuracy of 83.3%. In previous research, the Teacher Performance Assessment Team (PKG) was carried out by assuming the importance of each criterion without being given a weight, while the results obtained from system calculations, there was a weight given to each criterion. Testing was carried out on 47 civil servant teacher data with six planned civil servant teachers by the Principal in order to obtain the title of best teacher. Based on the test results, there were two civil servant teachers who were different from the data planned by the Principal, so the level of accuracy of the decision support system for selecting the best teacher using the AHP method was 83.3%.
Blockchain Integration to Enhance Federated Learning Model Integrity Yane Devi Anna; Sherli Triandari; Sigit Anggoro; Ardirra Yolandita; Adele Valerry
Blockchain Frontier Technology Vol. 5 No. 2 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i2.929

Abstract

Federated Learning is a distributed machine learning approach that enables model training without transferring raw data, thereby preserving user privacy. To improve conciseness, overlapping explanations of FL’s privacy benefits across the Abstract, Introduction, and Literature Review have been consolidated, highlighting its importance in sensitive domains while removing redundancy. This allows greater emphasis on the study’s novelty, particularly the Smart Contract design featuring multi-layer verification and reputation checking mechanisms. Despite its advantages, FL faces significant challenges related to model integrity, including parameter manipulation, model poisoning attacks, and limited trust among participating nodes. This study explores the integration of blockchain technology to address these issues. Leveraging decentralization, immutability, and transparency, blockchain is used to validate model updates, record contributions, and manage node reputation. The study employs a literature review and technical architecture design for a blockchain-integrated FL system. The results indicate that blockchain implementation enhances the reliability and security of FL training, especially in low-trust environments, with strong relevance for healthcare, finance, and IoT applications.
Analisis Data Log Sistem Informasi Laboratorium Menggunakan Pendekatan Business Intelligence untuk Rekomendasi Perbaikan Kualitas Layanan Laboratorium Rumah Sakit Nadhifa Qatrunnada; Sigit Anggoro; Tacbir Hendro Pudjiantoro
Jurnal Impresi Indonesia Vol. 5 No. 7 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i7.7968

Abstract

Laboratory Information System (LIS) menghasilkan data log yang merekam aktivitas pelayanan laboratorium, namun pemanfaatannya masih terbatas sebagai arsip operasional sehingga belum dimanfaatkan secara optimal untuk mendukung monitoring dan evaluasi layanan. Penelitian ini bertujuan menganalisis karakteristik pelayanan laboratorium menggunakan pendekatan Business Intelligence berdasarkan data log Laboratory Information System (LIS). Penelitian menggunakan metode kuantitatif deskriptif dengan data historis pelayanan laboratorium Rumah Sakit Wijaya Kusumah periode Maret–Mei 2026. Data diproses melalui tahapan Extract, Transform, and Load (ETL) menggunakan Microsoft Power BI, kemudian dianalisis berdasarkan enam indikator, yaitu Turnaround Time (TAT), Peak Hour, distribusi jenis pemeriksaan, beban layanan, asal rujukan, dan kepatuhan terhadap Standar Operasional Prosedur (SOP). Hasil penelitian menunjukkan rata-rata Turnaround Time sebesar 38,15 menit, lebih rendah dari standar pelayanan ?140 menit, dengan tingkat kepatuhan terhadap SOP sebesar 97,25%. Analisis juga menunjukkan bahwa puncak pelayanan terjadi pada pukul 06.00, jenis pemeriksaan yang paling dominan adalah Hematologi Rutin, serta sebagian besar permintaan pemeriksaan berasal dari unit Ruangan dan Instalasi Gawat Darurat (IGD). Seluruh indikator berhasil diintegrasikan ke dalam Dashboard Business Intelligence yang memberikan gambaran operasional laboratorium secara komprehensif. Penelitian ini menunjukkan bahwa pemanfaatan data log LIS melalui pendekatan Business Intelligence mampu mendukung monitoring operasional, evaluasi kinerja, serta penyusunan rekomendasi peningkatan kualitas pelayanan laboratorium berbasis data.
RFM-Based Customer Segmentation Using K-Means Clustering to Recommend Marketing Strategies for Motorcycle Repair Shops Nanda Oberusti; Sigit Anggoro; Tacbir Hendro Pudjiantoro
Journal Research of Social Science, Economics, and Management Vol. 5 No. 12 (2026): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i12.1610

Abstract

Motorcycle repair workshops, as service-based businesses, require an understanding of customer characteristics to develop more effective marketing strategies. However, differences in customer transaction behavior make generalized marketing strategies less effective in meeting the needs of different customer groups. Customer segmentation is an approach that enables businesses to classify customers based on their transaction characteristics, allowing the identification of valuable customers and the development of more targeted marketing strategies. This study aims to apply the Recency, Frequency, Monetary (RFM) method and the K-Means Clustering algorithm to segment customers of AHASS Cimalaka Sumedang Motorcycle Workshop. The resulting customer segments are expected to support the formulation of marketing strategy recommendations, improve customer loyalty, and facilitate more effective marketing decision-making. Differences in customer transaction behavior reduce the effectiveness of generalized marketing strategies, highlighting the need for customer segmentation based on transaction data. To apply the Recency, Frequency, Monetary (RFM) method and the K-Means Clustering algorithm for customer segmentation and to develop marketing strategy recommendations. This study employed a quantitative approach consisting of data preprocessing, RFM calculation, data normalization, K-Means clustering, and cluster evaluation. The proposed approach successfully segmented customers into five clusters based on their RFM characteristics, namely Potential Loyal Customer, At Risk Customer, Lost Customer, Inactive Customer, and Loyal Customer, which served as the basis for prioritizing targeted marketing strategies. The combination of the RFM method and the K-Means Clustering algorithm effectively supports customer segmentation and provides a reliable basis for developing more targeted and effective marketing strategies.
Peningkatan UX Melalui Perancangan dan Pengujian Sistem Pembelajaran Digital Berbasis Buku menggunakan Design Thinking Dian Ayu Cahyani; Irma Santikarama; Sigit Anggoro
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 5 No. 2 (2025): Oktober 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v5i2.5372

Abstract

User Experience (UX) is a crucial aspect in determining the effectiveness of digital learning systems. This study aims to design and evaluate a book-based digital learning system prototype using the Design Thinking approach. The research was conducted through five stages: Empathize, Define, Ideate, Prototype, and Test. Data were collected using questionnaires, interviews, and observations involving students, lecturers, and publishers. The evaluation applied a triangulation strategy combining the System Usability Scale (SUS), heatmap analysis, and semi-structured interviews. The results indicate an average SUS score of 70, which is above the minimum benchmark of 68, although improvements are still needed in visual design and navigation. Heatmap analysis revealed that most navigation elements were successfully used, but some icons were not recognized and certain menus were rarely accessed. The interviews reinforced these findings, highlighting that the system supports lecturers in monitoring and enhances student engagement, yet issues remain regarding button color contrast, label consistency, and the speed of accessing large files. These results demonstrate that Design Thinking, when combined with triangulated evaluation, can produce a book-based digital learning system that is more interactive, adaptive, and collaborative. This study contributes to the literature by emphasizing that integrating user-centered design with triangulation methods can significantly improve UX quality in higher education digital learning contexts.
Pengaruh Literasi Digital dan Kesiapan Teknologi terhadap Keberlanjutan Bisnis UMKM Kuliner dalam Konteks Pemanfaatan QRIS di Kabupaten Bekasi Kayla Sejatining Pangesti; Sigit Anggoro; Dea Destiani
Jurnal Impresi Indonesia Vol. 5 No. 7 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i7.7953

Abstract

Transformasi digital mendorong pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) untuk mengadopsi berbagai teknologi, termasuk Quick Response Code Indonesian Standard (QRIS), sebagai sistem pembayaran digital. Namun, keberhasilan pemanfaatan QRIS tidak hanya ditentukan oleh ketersediaan teknologi, tetapi juga dipengaruhi oleh literasi digital dan kesiapan teknologi pelaku usaha dalam mengelola aktivitas bisnis secara efektif. Penelitian ini bertujuan menganalisis pengaruh literasi digital dan kesiapan teknologi terhadap keberlanjutan bisnis UMKM kuliner pengguna QRIS di Kabupaten Bekasi. Penelitian menggunakan pendekatan kuantitatif dengan desain explanatory research. Data dikumpulkan melalui penyebaran kuesioner kepada 155 pelaku UMKM kuliner yang dipilih menggunakan teknik purposive sampling. Literasi digital diukur berdasarkan kerangka Digital Competence Framework (DigComp 2.1), sedangkan kesiapan teknologi diukur menggunakan Technology Readiness Index (TRI). Analisis data dilakukan menggunakan metode Structural Equation Modeling–Partial Least Squares (SEM-PLS) dengan bantuan perangkat lunak SmartPLS 4 melalui evaluasi outer model, inner model, dan pengujian hipotesis. Hasil penelitian menunjukkan bahwa literasi digital dan kesiapan teknologi berpengaruh positif dan signifikan terhadap keberlanjutan bisnis UMKM kuliner pengguna QRIS. Kesiapan teknologi memiliki pengaruh yang lebih dominan dibandingkan literasi digital, yang menunjukkan bahwa kesiapan pelaku usaha dalam menerima dan memanfaatkan teknologi menjadi faktor penting dalam mendukung keberlanjutan usaha. Temuan penelitian ini memperkuat perspektif Resource-Based View (RBV) dan Technology Readiness Index (TRI) bahwa kapabilitas digital dan kesiapan teknologi merupakan sumber daya strategis yang mendukung keberlanjutan bisnis UMKM. Hasil penelitian diharapkan dapat menjadi masukan bagi pemerintah, Bank Indonesia, dan lembaga pendamping UMKM dalam merancang program peningkatan literasi digital serta kesiapan teknologi guna memperkuat transformasi digital dan keberlanjutan UMKM.
Co-Authors Adele Valerry Ardirra Yolandita Dea Destiani Dian Ayu Cahyani Gunawan Abdillah Hary Rizqi Ramadhani Irma Santikarama Kayla Sejatining Pangesti Nadhifa Qatrunnada Nanda Oberusti Sherli Triandari Tacbir Hendro Pudjiantoro Yane Devi Anna