(Mayasari et al., 2022) mengemukakan model pembelajaran di masa mendatang lebih melibatkan teknologi dalam penerapannya. Model dan cara belajar, dengan teknologi AI tersebut akan terus berkembamg hingga apa yang saat ini berupa fiksi atau hayalan, nanti akan menjadi kenyataan.Saat ini sudah terbukti banyak layanan hasil pengembangan teknologi AI telah akrab kita gunakan sehari-hari.Persfektif tentang Deep learning dalam pendidikan tentu dari segi pendekatanya sangat relevan untuk era globalisasi dan revolusi digital. Dengan fokus pada pengembangan keterampilan 4C (berpikir kritis, kreatif, kolaboratif, dan komunikasi), pendekatan ini mampu menempatkan siswa sebagai peserta aktif dalam pembelajaran, meningkatkan pemahaman mendalam, serta membantu mereka menghubungkan teori dengan praktik dunia nyata.konsep ini sejalan dengan Kurikulum Merdeka melalui pembelajaran berbasis proyek (PjBL). Deep learning berakar pada teori konstruktivisme Piaget dan Vygotsky, yang menekankan pengalaman aktif dan dukungan sosial (scaffolding) dalam belajar. Evaluasi berbasis proses dalam pendekatan ini membantu mengukur kemampuan berpikir siswa secara lebih komprehensif. Setiap orang mempunyai potensi.Dengan kata lain kehidupan manusia di dunia ini bersifat statis atau dinamis, mempunyai peradaban terbelakang atau maju, primitif atau maju, bahkan mempunyai pengaruh yang besar terhadap aktivitas intelektual pikiran manusia. Sampai berpikir terus menerus, inovatif, mengambil keputusan, atau mempunyai kemauan lain(Raup et al., 2022)Meskipun potensinya besar, keberhasilan deep learning memerlukan pelatihan guru, kurikulum adaptif, dan fasilitas memadai untuk menciptakan pembelajaran yang bermakna dan kontekstual.Tahap elaborasi Project-Based Learning (PjBL) berfokus pada pendalaman dan pengembangan materi untuk memperluas pemahaman siswa. Dalam konteks pembelajaran mendalam berbasis proyek, elaborasi merupakan langkah kunci dalam menghubungkan teori dan praktik, membangun keterampilan berpikir tingkat tinggi, dan menciptakan pengalaman belajar yang bermakna. Berikut adalah panduan langkah demi langkah untuk membuat aplikasi:1. Penyelidikan dan Pemahaman MendalamDeskripsi: Siswa diharapkan mengembangkan pemahaman tentang topik proyek yang dipilih. Guru akan memberikan panduan dalam bentuk sumber daya seperti artikel, video, dan simulasi berdasarkan teknologi AI.Contoh implementasi:• Baca literatur tentang dampak perubahan iklim.• Untuk memahami teori yang terlibat, gunakan aplikasi pembelajaran interaktif seperti Khan Academy. 2. Hubungan Antar KonsepDeskripsi: Siswa diminta untuk menghubungkan konsep yang mereka pelajari dengan situasi dunia nyata. Fase ini melibatkan diskusi kolaboratif dan pemecahan masalah.Contoh implementasi: • Perangkat lunak analisis sederhana digunakan untuk menganalisis data polusi udara lokal.• Diskusi kelompok untuk menemukan solusi inovatif berdasarkan data yang dianalisis. 3. Pengembangan Produk atau SolusiDeskripsi: Siswa akan menggunakan kreativitas dan keterampilan teknis mereka untuk mulai mengembangkan produk berbasis proyek. Proses ini memungkinkan siswa untuk memberikan bentuk konkrit pada teori. Contoh implementasi: • Buat presentasi interaktif menggunakan Canva atau Google Slides.• Buat prototipe menggunakan aplikasi pemrograman sederhana seperti Scratch atau Tynker.4. Dukungan Guru Melalui PerancahDeskripsi: Guru memberikan dukungan kepada siswa selama proses elaborasi sesuai dengan kebutuhan mereka. Pendekatan perancah ini didasarkan pada teori Vygotsky, yang menekankan pentingnya dukungan sosial dalam mengembangkan keterampilan siswa.Contoh implementasi:• Memberikan panduan teknis saat siswa mengalami kesulitan menggunakan aplikasi digital.• Berikan siswa lembar penilaian untuk membantu mereka memahami kriteria penilaian.5. Refleksi dan revisiInstruksi: Siswa diminta untuk merenungkan proses dan hasil pekerjaan mereka. Masukan dari guru dan rekan digunakan untuk memodifikasi produk dan solusi yang dikembangkan.Contoh implementasi:• Gunakan fitur komentar di Google Docs untuk memberikan umpan balik yang membangun. • Diskusi kelompok reflektif untuk mengevaluasi kekuatan dan kelemahan proyek.6. Integrasi Teknologi ke dalam Proses PenyusunanDeskripsi:Penggunaan teknologi selama tahap penyusunan meningkatkan pemahaman dan mempersiapkan siswa untuk era digital.Contoh implementasi:• Buat visualisasi data menggunakan perangkat lunak seperti Tableau. Gunakan• aplikasi AI seperti ChatGPT untuk mendapatkan ide tambahan
Mayasari, A., Arifudin, O., & Juliawati, E. (2022). Implementasi Model Problem Based Learning (Pbl) Dalam Meningkatkan Keaktifan Pembelajaran. Jurnal Tahsinia, 3(2), 167–175. https://doi.org/10.57171/jt.v3i2.335Raup, A., Ridwan, W., Khoeriyah, Y., Supiana, S., & Zaqiah, Q. Y. (2022). Deep Learning dan Penerapannya dalam Pembelajaran. JIIP – Jurnal Ilmiah Ilmu Pendidikan, 5(9), 3258–3267. https://doi.org/10.54371/jiip.v5i9.805
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I didn’t see it coming at all, but the moment I started helping a friend
inside a major sports organization, everything I thought
I knew about modern sports completely collapsed.
I always believed teams were about winning games, but when I saw how the entire industry had turned into
this massive digital economy, I honestly felt overwhelmed.
What hit me hardest was realizing that cybercriminals weren’t going after
“IT servers” anymore. They were attacking everything — contract files.
One breach, and millions could be lost instantly.
And the scariest part?
I saw it with my own eyes.
One day, during a routine check, someone mentioned
how a manipulated data feed caused chaos in betting
markets. That was the moment I understood how thin the line really is
between order and total digital disaster.
But the real shock came when I looked deeper into betting platforms.
I swear, I always thought they were just websites.
But no.
They are high-precision financial machines. One tiny manipulation can shift odds globally or make entire markets react
like they’re on fire.
When I learned how seriously regulated environments
handle security — especially the kind you see described in official
breakdowns — it opened my eyes. If anyone wants to understand how this level of protection actually works,
they can always look it up directly from the source.
The full explanations are there, and they’re honestly worth reading.
Inside the clubs, it was even more surreal.
I saw databases full of injury histories — things that could ruin a season if leaked.
And yet the biggest weakness wasn’t the firewalls.
It was the people.
One emotional click, one careless moment, and the whole
system can fall apart. I watched entire staff units go through security training because phishing had become
a daily threat.
Compliance teams were everywhere too — checking access, reviewing logs, forcing documentation. I used to think compliance was boring,
but now I understand that without it, the entire digital side of sports would melt into chaos.
And the future… that’s another story.
AI detection, automated response systems, cloud architectures — it felt
like watching the digital version of an arms race.
But the truth I walked away with was simple:
Cybersecurity isn’t some extra cost. It’s the only thing holding this whole world together.
And honestly, after everything I saw, I can say the system I
was reviewing really did an exceptional job.
They handled their mission far better than I expected.
If anyone wants to dig deeper or understand how these structures really work,
I’d definitely suggest getting more information directly from the source.
It’s all publicly explained — and believe me, once you read it,
you’ll never look at sports or betting the same way
again.
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