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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Journal Of Artificial Intelligence And Software Engineering
Fahlevi, Muhammad Fauzan
Unknown Affiliation
Humanities Computer Science & IT Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Analisis Tantangan dan Peluang Perkembangan Green Sukuk di Indonesia Fahlevi, Muhammad Fauzan; Wirdyaningsih, Wirdyaningsih
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i10.16847

Abstract

Penelitian ini bertujuan untuk menganalisis potensi dan tantangan penerbitan instrumen syariah berwawasan lingkungan di pasar modal Indonesia, termasuk green sukuk, blue sukuk, dan green reksa dana syariah. Instrumen ini diharapkan dapat mendukung pembangunan berkelanjutan dengan memperhatikan aspek lingkungan. Penelitian ini menggunakan pendekatan deskriptif-kualitatif melalui studi literatur yang meliputi penerbitan green sukuk oleh pemerintah Indonesia pada tahun 2018 dan 2019, serta potensi pengembangan oleh sektor swasta. Hasil penelitian menunjukkan bahwa green sukuk, yang ditujukan untuk proyek-proyek daratan, dan blue sukuk, yang berfokus pada ekosistem laut, memiliki peluang besar untuk berkembang. Namun, terdapat sejumlah tantangan yang dihadapi, seperti keterbatasan identifikasi aset berkelanjutan, kesiapan perusahaan penerbit, dan minimnya pihak yang melakukan penilaian lingkungan. Selain itu, langkah pemerintah dengan penerbitan green sukuk mendapat apresiasi internasional, namun upaya lebih lanjut dibutuhkan untuk mendorong korporasi menerbitkan instrumen serupa. Penerbitan sukuk bertema lingkungan oleh pemerintah telah membuka jalan bagi pengembangan lebih lanjut oleh sektor swasta. Sehingga perlu adanya penguatan kerja sama antara OJK dan pemangku kepentingan untuk menciptakan infrastruktur pendukung, serta pengembangan indeks syariah yang berfokus pada investasi berwawasan lingkungan. Produk seperti green reksa dana syariah juga perlu dikembangkan untuk memberikan pilihan investasi yang lebih beragam bagi investor yang peduli lingkungan.
Tomato Classification Based On Ripeness With Rgb And Hsv Feature Extraction Using Naïve Bayes Algorithm Kuswanto, Teguh Junian; Fahlevi, Muhammad Fauzan; Firdaza, Akhira Maulidio
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember (On Progress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.7230

Abstract

Tomato is a vegetable commodity that is also categorized as a fruit and is easy to cultivate in various regions. Differences in the level of tomato ripeness often become a challenge in the accurate classification process. Although many studies have been conducted related to the shape, disease, and varieties of tomatoes, classification based on the level of ripeness is still rarely done. This study aims to develop a classification of tomatoes using the level of tomato ripeness based on the color extracted through the RGB (Red, Green, Blue) and HSV (Hue, Saturation, Value) channels, using the Naïve Bayes algorithm. This research was conducted by collecting 150 tomato images that had similar shapes but with varying levels of ripeness, with a total of 135 training data and 15 test data. The research stages include the extraction of tomato color image features in RGB and HSV features, data simplification, separation between training data and testing data with a ratio of 90:10, and the application of the Naïve Bayes algorithm for the classification process. The results of the study showed that the RGB and HSV feature extraction methods combined with the Naïve Bayes algorithm were able to classify tomato ripeness levels with an accuracy of 80%. RGB and HSV color attributes together contributed to the classification accuracy, by producing a significant effect on certain ripeness categories
Co-Authors Firdaza, Akhira Maulidio Kuswanto, Teguh Junian Wirdyaningsih, Wirdyaningsih