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Syafrijon, Syafrijon
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Efektivitas Pembelajaran Science Technology Engineering and Math (STEM) terhadap Hasil Belajar di Sekolah: Meta Analisis Siregar, Winda Lestari; Syafrijon, Syafrijon; Giatman, Giatman; Ganefri, Ganefri; Krismadinata, Krismadinata; Jalinus, Nizwardi
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3972

Abstract

Education at the high school (SMA) and vocational school (SMK) levels faces challenges in preparing creative and competent students. To address these challenges, a combination of technology is needed in the fields of science, mathematics, and engineering. A study on the implementation of STEM (Science, Technology, Engineering, and Mathematics) in learning in Indonesia. To test its effectiveness, a meta-analysis was conducted which included 25 articles published between 2018 and 2023. The findings showed that STEM learning has a significant role in improving student learning outcomes with an overall effect size of 6,89. Based on the data analysis of the application of the STEM approach, it can develop the ability to solve problems rationally, conduct research, question, collaborate, criticize, analyze and can also improve the ability to access information, adapt to change, make decisions, produce, be responsible, show curiosity, interact in a social and cultural context, and develop leadership and entrepreneurship traits in students. The STEM approach provides a solid foundation for developing a variety of skills and attitudes that are important in facing the challenges and demands of the modern world of students.
Optimization of Digital Technology Utilization for Improving the Skills of Karang Taruna in Nagari Sungai Beringin, 50 Kota Regency Hendriyani, yeka; Syafrijon, Syafrijon; Diputra, Yudhi
Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Vol 26, No 1 (2026): Suluah Bendang: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/sb.07020

Abstract

This community service activity aimed to optimize the use of digital technology to improve the skills of Karang Taruna members in Nagari Sungai Beringin, 50 Kota Regency. The activity was motivated by several problems, including limited access to digital technology, low digital skills among youth, and the absence of structured skill development programs relevant to current needs. The solution offered was training on the use of Canva for social media content design and logo creation to support youth creativity and entrepreneurship. The program involved 22 participants and was conducted on September 6–7, 2024. The implementation methods included preparation, pretest, training sessions, guided practice, independent assignments, posttest, and participant response questionnaires. The results showed that the training was carried out well and received positive responses from participants. The activity increased participants’ interest, confidence, and practical skills in designing digital content. Participants were able to produce valid and usable social media designs and logo products for Karang Taruna. This activity demonstrates that digital technology-based training can be an effective strategy for strengthening youth capacity, encouraging productive creativity, and supporting community empowerment at the village level.
Perancangan Sistem Prediksi Pola Permintaan Layanan Internet FTTH Menggunakan Model LSTM Berbasis Web Putry, Shalshabila Shafa; Hendriyani, Yeka; Fatmi, Yulia; Syafrijon, Syafrijon
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/tjm6wa36

Abstract

Penelitian ini bertujuan merancang sistem berbasis web untuk memprediksi pola permintaan layanan internet Fiber to the Home (FTTH) dengan memanfaatkan model Long Short-Term Memory (LSTM) sebagai komponen analitik. Permasalahan yang dihadapi penyedia layanan FTTH adalah fluktuasi permintaan antarwaktu dan antarwilayah yang berdampak pada perencanaan stok perangkat, penjadwalan pemasangan, dan pengembangan infrastruktur. Penelitian menggunakan pendekatan Cross Industry Standard Process for Data Mining (CRISP-DM) dengan data historis permintaan layanan FTTH periode 2022 sampai 2025 yang diagregasi menjadi data runtun waktu bulanan. Sistem dikembangkan menggunakan Python, Flask, dan SQLite, sedangkan model LSTM dikonfigurasi dengan dua layer, 50 unit neuron, optimizer Adam, dan 50 epoch. Hasil penelitian menunjukkan bahwa sistem mampu mengintegrasikan pengelolaan data pelanggan, proses prediksi, visualisasi tren, dan rekomendasi kebutuhan stok dalam satu platform. Pada evaluasi awal, nilai loss pelatihan menurun dari 0.8541 menjadi 0.0064, sedangkan evaluasi prediksi menghasilkan Mean Absolute Error sebesar 32.43 dan Root Mean Squared Error sebesar 32.68. Temuan ini menunjukkan bahwa model telah mampu mengikuti pola umum permintaan pada data yang digunakan, tetapi kinerja operasionalnya masih perlu divalidasi lebih lanjut melalui pembandingan dengan model baseline, skema evaluasi time-series yang lebih ketat, dan konteks volume permintaan per wilayah. Kontribusi utama penelitian ini terletak pada integrasi hasil prediksi ke dalam sistem operasional FTTH berbasis web, bukan pada pengusulan arsitektur LSTM baru. This study aimed to design a web-based system to predict Fiber to the Home (FTTH) internet service demand patterns using a Long Short-Term Memory (LSTM) model as the analytical component. The main challenge faced by FTTH providers is the fluctuation of demand across time periods and service areas, which affects equipment stock planning, installation scheduling, and infrastructure expansion. The study adopted the Cross Industry Standard Process for Data Mining (CRISP-DM) and used historical FTTH service demand data from 2022 to 2025, aggregated into monthly time-series data. The system was developed using Python, Flask, and SQLite, while the LSTM model was configured with two layers, 50 neurons, the Adam optimizer, and 50 epochs. The results show that the system integrates customer data management, prediction processes, trend visualization, and stock requirement recommendations within a single platform. In the initial evaluation, the training loss decreased from 0.8541 to 0.0064, while the prediction evaluation yielded a Mean Absolute Error of 32.43 and a Root Mean Squared Error of 32.68. These findings indicate that the model captured the general demand pattern in the available data, although its operational validity still requires further verification through baseline comparisons, stricter time-series evaluation schemes, and demand-scale context. The main contribution of this study lies in integrating forecasting outputs into an FTTH operational web system rather than proposing a new LSTM architecture.
Platform Adaptive Learning Berbasis NLP untuk Pembelajaran Literasi Siswa Disleksia Sekolah Dasar Cakranata, Raden Galuh Garhadi; Syafrijon, Syafrijon; Farell, Geovanne; Sandra, Randi Proska
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/j27kax12

Abstract

Penelitian ini bertujuan mengembangkan platform pembelajaran berbasis web yang mengintegrasikan Adaptive Learning dan Natural Language Processing (NLP) untuk mendukung pembelajaran membaca dan menulis siswa sekolah dasar dengan gangguan disleksia. Permasalahan utama yang melatarbelakangi penelitian ini adalah terbatasnya platform pembelajaran digital yang mampu menyesuaikan materi, latihan, dan rekomendasi pembelajaran berdasarkan respons teks siswa disleksia. Penelitian ini menggunakan metode pengembangan perangkat lunak model Waterfall yang meliputi analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan pemeliharaan. Sistem dikembangkan dengan antarmuka web AdaptLearn, backend berbasis Gin Framework, frontend berbasis Next.js, basis data PostgreSQL, cache Redis, serta keamanan autentikasi menggunakan bcrypt. Modul NLP digunakan untuk menganalisis jawaban teks siswa dan mengklasifikasikan tingkat pemahaman ke dalam kategori Paham, Cukup Paham, dan Belum Paham. Hasil pengujian menunjukkan bahwa seluruh fitur utama sistem berjalan sesuai skenario black-box testing. Evaluasi model NLP menghasilkan accuracy sebesar 0,99 dengan nilai precision, recall, dan F1-score yang tinggi pada seluruh kategori. Hasil usability testing menggunakan System Usability Scale memperoleh skor rata-rata 73,33 yang termasuk kategori baik dan acceptable. Dengan demikian, platform yang dikembangkan layak digunakan sebagai alternatif media pembelajaran literasi dasar yang lebih personal, adaptif, dan inklusif bagi siswa disleksia. This study aimed to develop a web-based learning platform integrating Adaptive Learning and Natural Language Processing (NLP) to support reading and writing instruction for elementary school students with dyslexia. The study was motivated by the limited availability of digital learning platforms that can adjust learning materials, exercises, and recommendations based on dyslexic students’ text responses. This research used the Waterfall software development model, consisting of requirements analysis, system design, implementation, testing, and maintenance. The system was implemented as the AdaptLearn web platform using a Next.js frontend, Gin Framework backend, PostgreSQL database, Redis cache, and bcrypt-based authentication security. The NLP module was designed to analyze students’ written responses and classify their understanding into three categories: Understanding, Partially Understanding, and Not Yet Understanding. The Adaptive Learning mechanism then used the NLP results and learning interactions to recommend remedial or advanced learning materials. The results showed that all major system functions performed as expected in black-box testing. NLP model evaluation produced an accuracy of 0.99, with high precision, recall, and F1-score across all categories. Usability testing using the System Usability Scale obtained an average score of 73.33, indicating good and acceptable usability. Therefore, the developed platform is feasible as an alternative digital learning medium that supports more personalized, adaptive, and inclusive literacy learning for students with dyslexia.
Implementasi Smart Contract Ethereum dengan Pendekatan Hybrid untuk Verifikasi Dokumen dan Transparansi pada Sistem Crowdfunding Beasiswa Aviola, Rawim Puja; Farell, Geovanne; Syafrijon, Syafrijon; Sandra, Randi Proska
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/rm4ggv60

Abstract

Penelitian ini bertujuan mengimplementasikan smart contract Ethereum dengan pendekatan hybrid untuk memperkuat verifikasi dokumen dan transparansi pada sistem crowdfunding beasiswa. Permasalahan utama yang diangkat adalah rendahnya kepercayaan publik terhadap platform donasi pendidikan ketika dokumen persyaratan, status verifikasi, dan realisasi penggunaan dana hanya dikelola melalui basis data terpusat. Metode yang digunakan adalah penelitian pengembangan perangkat lunak dengan model prototype yang mencakup komunikasi kebutuhan, perencanaan cepat, pemodelan desain, konstruksi prototipe, serta penyerahan dan evaluasi umpan balik. Sistem dibangun menggunakan Next.js, SQLite, Prisma ORM, Solidity, Ethers.js, MetaMask, dan jaringan Ethereum Sepolia Testnet. Hasil penyusunan sistem menunjukkan bahwa arsitektur hybrid mampu memisahkan penyimpanan dokumen fisik secara off-chain dari pencatatan bukti integritas secara on-chain. Smart contract ScholarshipRegistry dirancang untuk mencatat hash dokumen, status verifikasi, alamat wallet verifikator, timestamp, dan log nominal donasi tanpa menggunakan mata uang kripto sebagai alat pembayaran. Fitur audit publik memungkinkan donatur dan masyarakat mencocokkan hash dokumen, memantau bukti pencairan dana, serta melaporkan indikasi kejanggalan. Secara kritis, blockchain meningkatkan integritas rekam jejak, tetapi tidak otomatis menjamin kebenaran substantif isi dokumen; karena itu validasi administratif, kontrol akses, dan mekanisme pelaporan publik tetap diperlukan. Penelitian ini berkontribusi pada model crowdfunding beasiswa yang lebih transparan, efisien, dan dapat diaudit. This study aims to implement an Ethereum smart contract using a hybrid approach to strengthen document verification and transparency in a scholarship crowdfunding system. The main problem addressed is the limited public trust in digital education donation platforms when eligibility documents, verification status, and fund realization records are controlled only through a centralized database. The study applied a software development method based on the prototype model, consisting of communication, quick planning, quick design modeling, prototype construction, and delivery with feedback evaluation. The prototype was developed using Next.js, SQLite, Prisma ORM, Solidity, Ethers.js, MetaMask, and the Ethereum Sepolia Testnet. The resulting design demonstrates that the hybrid architecture can separate physical document storage in an off-chain layer from integrity proof recording in an on-chain layer. The ScholarshipRegistry smart contract records document hashes, verification status, verifier wallet addresses, timestamps, and donation amount logs without using cryptocurrency as the payment instrument. The public audit feature enables donors and the public to compare document hashes, monitor disbursement evidence, and submit reports on suspected irregularities. Critically, blockchain improves the integrity of audit trails, but it does not automatically verify the substantive truth of uploaded documents; therefore, administrative validation, role-based access control, and participatory reporting remain necessary. This study contributes a transparent, cost-efficient, and auditable model for scholarship crowdfunding systems.
Rancang Bangun Sistem Informasi Pesanan Terintegrasi Multi-Role Berbasis Web Untuk Industri Galaxy Digital Printing Najna, Kimi Maulana; Delianti , Vera Irma; Hendriyani, Yeka; Syafrijon, Syafrijon
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/0ahzps29

Abstract

Digitalisasi proses bisnis menjadi kebutuhan penting bagi usaha mikro, kecil, dan menengah digital printing karena alur pesanan, desain, pembayaran, dan produksi saling bergantung serta rentan terfragmentasi apabila masih dikelola secara manual. Penelitian ini bertujuan mengembangkan sistem informasi pesanan terintegrasi berbasis Role-Based Access Control (RBAC) pada Galaxy Digital Printing untuk memperbaiki pencatatan pesanan, konsistensi kalkulasi harga, kontrol pembayaran bertahap, koordinasi antarperan, dan pelacakan status pesanan berbasis web. Penelitian menggunakan metode Research and Development dengan model Incremental yang mencakup komunikasi kebutuhan, perencanaan, pemodelan, konstruksi, pengujian, dan deployment. Data kebutuhan dikumpulkan melalui observasi, wawancara, dan studi literatur, sedangkan evaluasi dilakukan melalui validasi produk, Black Box Testing, User Acceptance Testing, dan System Usability Scale. Sistem dikembangkan menggunakan Laravel, MySQL, RBAC untuk lima peran pengguna, kalkulator harga otomatis, manajemen file desain, integrasi Midtrans, reminder pembayaran, dan tracking status pesanan. Kebaruan penelitian terletak pada model integrasi workflow pesanan digital printing yang menghubungkan kalkulasi harga, manajemen revisi desain, staged payment, payment gateway, produksi, dan tracking dalam satu platform multi-role. Hasil validasi produk memperoleh skor 93,29% dengan kategori sangat valid. Sepuluh skenario Black Box Testing utama berhasil 100%, UAT memperoleh rata-rata 4,35 dari skala 5, dan SUS mencapai 85,50 dengan Grade A. Temuan ini menunjukkan bahwa sistem dinilai layak secara fungsional dan diterima oleh pengguna awal pada konteks Galaxy Digital Printing. Namun, generalisasi hasil masih terbatas karena penelitian merupakan single case dengan jumlah responden kecil, belum mencakup load testing, uji keamanan mendalam, dan pengukuran efisiensi berbasis waktu kerja aktual. Business process digitalization is increasingly important for digital printing micro, small, and medium enterprises because order, design, payment, and production workflows are interdependent and vulnerable to fragmentation when managed manually. This study aims to develop an integrated order information system based on Role-Based Access Control (RBAC) at Galaxy Digital Printing to improve order recording, price calculation consistency, staged payment control, multi-role coordination, and web-based order status tracking. The study employed a Research and Development method using the Incremental model, covering requirement communication, planning, modeling, construction, testing, and deployment. Requirement data were collected through observation, interviews, and literature studies, while system evaluation was conducted using product validation, Black Box Testing, User Acceptance Testing, and the System Usability Scale. The system was developed using Laravel, MySQL, RBAC for five user roles, an automatic price calculator, design file management, Midtrans integration, payment reminders, and order status tracking. The novelty of this study lies in an integrated digital printing workflow model that connects price calculation, design revision management, staged payment, payment gateway, production, and tracking within a multi-role platform. Product validation achieved 93.29%, categorized as highly valid. Ten core Black Box Testing scenarios achieved 100% success, UAT produced an average score of 4.35 out of 5, and SUS reached 85.50 with Grade A. These findings indicate that the system is functionally feasible and accepted by initial users in the Galaxy Digital Printing context. However, the generalizability of the findings remains limited because this is a single-case study with a small number of respondents and does not yet include load testing, in-depth security testing, or objective work-time efficiency measurement.
Co-Authors Agustanto, Dedy Ahmaddul Hadi, Ahmaddul ANIP FEBTRIKO Aviola, Rawim Puja Bismihayati, Bismihayati Budayawan, Khairi Budi Prasetyo Cakranata, Raden Galuh Garhadi Dedy Irfan Delianti , Vera Irma Dony Novaliendry Ednofri Emon Azriadi Fahmi Rahmatia Fatmawati Fatmawati Fatmi, Yulia Febrian, Febrian Ganefri . Geovanne Farell Gusfira, Mona Insan Aljundi, Ihsanul Ismail, Ainaa Maya Munira binti Ismail Joni, Riri Rahmawati Krismadinata Krismadinata, Krismadinata Makmur, Brian Mila Sari Muhammad Anwar Muhammad Giatman Muhammad Rasyid Ridha Mulya Gusman Muzirwan Najna, Kimi Maulana Nata, Lismomon Naufan Islami, Fattan Nizwardi Jalinus Novaldi, Farhan Pati Harau, Frans Surya Putry, Shalshabila Shafa Rahmi Putri Wirman Ridho Pratama Sandra, Randi Proska Sari, Serly Mutia Suciko, Adelina Teguh Nugraha Pratama Titin Sriwahyuni Tri Rahayuningsih Wardeni, Siska Warmansyah, Frinsis Winda Lestari Siregar Yeka Hendriyani Yudhi Diputra