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A Quantum Perceptron: A New Approach for Predicting Rice Prices at the Indonesian Wholesale Trade Level Solikhun; Yunita, Tri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5869

Abstract

The wholesale rice trade in Indonesia encounters various challenges in forecasting prices. These challenges are influenced by factors such as weather, government policies, global market conditions, and other economic variables. Accurate price predictions are crucial for informing government policy in a timely manner. This research introduces a new approach that utilizes the Quantum Perceptron algorithm to forecast rice prices. The algorithm, an innovative method in quantum computing, is expected to enhance the efficiency and effectiveness of price predictions. Although the research is still in the analytical stage, the use of Quantum Perceptron shows promise in dynamically addressing the complexity of market data and the variability of factors affecting rice prices. The method focuses on developing models that can leverage quantum computing to process information more effectively than classical methods. By harnessing the unique properties of quantum mechanics, such as superposition and entanglement, Quantum Perceptron can identify complex patterns and optimize predictions of future rice prices. The research describes the implementation of quantum algorithms in the context of the Indonesian rice wholesale market, including the technical challenges encountered and future development prospects. The research utilizes quantum computing along with the perceptron algorithm. The researchers focused on analyzing the quantum perceptron algorithm because of the limited availability of quantum computing devices. The findings of this research are confined to analysis. In order to advance this research, the author recommends that future studies employ quantum devices to achieve more accurate predictions
Pengaruh Penggunaan Gadjet Dalam Menurunkan Kemampuan Belajar Siswa Yunita, Tri; Masriadi, Masriadi
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.1866

Abstract

Penggunaan Gadget di kalangan siswa telah menjadi fenomena umum seiring berkembangnya teknologi digital. Namun, penggunaan Gadget yang berlebihan dan tidak terkontrol justru dapat berdampak negatif terhadap kemampuan belajar siswa. Penurunan konsentrasi, motivasi belajar, dan keterampilan sosial menjadi persoalan yang perlu ditinjau secara serius dalam dunia pendidikan. Mengetahui pengaruh penggunaan Gadget terhadap penurunan kemampuan belajar siswa melalui analisis berbagai penelitian ilmiah terkini. Metode: Metode yang digunakan adalah studi literatur dengan menelusuri artikel ilmiah melalui basis data Google Scholar, DOAJ, dan Semantic Scholar. Penelitian ini didasarkan pada telaah terhadap delapan artikel terpilih yang dipublikasikan antara tahun 2020 hingga 2025, yang terdiri dari enam jurnal nasional dan dua jurnal internasional. Hasil tinjauan menunjukkan bahwa mayoritas penelitian menemukan adanya hubungan negatif antara intensitas penggunaan Gadget dengan hasil belajar siswa. Gadget berdampak pada penurunan fokus, disiplin, interaksi sosial, serta prestasi akademik. Penggunaan Gadget secara pasif dan tanpa arahan terbukti mengganggu proses belajar yang efektif. Penggunaan Gadget yang tidak terarah merupakan faktor yang signifikan dalam menurunnya kemampuan belajar siswa. Oleh karena itu, dibutuhkan pengawasan dan regulasi penggunaan Gadget yang melibatkan peran aktif guru dan orang tua.
Macroprudential Policy, Islamic Banking, and Economic Transformation: Ensuring Pro-Poor Stability Abadiyah, Fajriyatul; Yunita, Tri
Jurnal Penelitian Ekonomi dan Bisnis Vol. 11 No. 2 (2026): September 2026
Publisher : Universitas Dian Nuswantoro Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jpeb.v11i2.16143

Abstract

Persistent poverty across Organisation of Islamic Cooperation (OIC) member states remains a formidable challenge, even as Islamic financial assets continue to expand at double-digit rates. This study investigates a relatively unexplored intersection: whether macroprudential instruments embedded within the Islamic banking architecture, specifically the Sharia-compliant Capital Adequacy Ratio (CAR), Loan-to-Value (LTV) regulation, and Sharia Banking Depth, exert measurable long-run effects on national poverty rates across OIC economies. Using an annual panel dataset of 30 OIC countries spanning 2000 to 2022, sourced from Bloomberg, the World Development Indicators (WDI), and SESRIC, we deploy a Vector Error Correction Model (VECM) framework to capture both long-run cointegrating relationships and short-run adjustment dynamics. System GMM estimation further validates the findings against potential endogeneity. Results confirm that Sharia Banking Depth and Islamic bank CAR exercise significant negative effects on poverty in the long run, while consumer price inflation remains the strongest pro-poverty force in the system. LTV regulation, conversely, demonstrates a regressive long-run effect, restricting credit access most acutely for lower-income households. Fiscal policy shows a conditional, governance-dependent impact. The Error Correction Term coefficient of −0.387 indicates a convergence speed of approximately 38.7% per annum. These findings yield actionable policy prescriptions for OIC financial regulators seeking to embed pro-poor objectives within macroprudential design.