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All Journal Emerging Information Science and Technology Jurnal Informatika Teknologi dan Sains (Jinteks)
Christianto, Devri Budi
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Computer Science & IT Control & Systems Engineering

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Implementation of Finite State Automata to Optimize the Waste Collection Process in the Greenify Application Setyawan, Ryan Ari; Christianto, Devri Budi; Bening, Ridho Gilang
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.27032

Abstract

Efficient waste management is a major challenge in urban life. One promising solution is the use of Finite State Automata (FSA) to optimize the waste containment process within the Greenify application. This study aims to explore the application of FSA in designing the logical flow for waste management, which includes identifying waste types, collection locations, and pick-up schedules. The methodology employed is a theoretical approach that implements the FSA model to regulate statuses and transitions between different steps in the waste management process. The results demonstrate that FSA can improve operational efficiency, reduce management errors, and enhance the user experience. The application of FSA in Greenify facilitates a more structured and automated waste management system, while also improving the accuracy of scheduling and waste collection. This conclusion highlights the significant potential of FSA as a technological solution for environmentally friendly waste management, with the goal of optimizing the performance of the Greenify application and advancing urban waste management practices.
PENERAPAN STRING MATCHING PADA INFORMATION RETRIEVAL DARI EKSTRAKSI METADATA DAN ANALISIS AKURASI VIDEO YOUTUBE Christianto, Devri Budi; Setyawan, Ryan Ari; Bororing, Jemmy Edwin
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.5647

Abstract

Meningkatnya jumlah konten di platform youtube shorts menghadirkan tantangan dalam menyaring informasi yang relevan serta menghindari konten yang mengandung kata-kata negatif. Penelitian ini mengembangkan sistem information retrieval dengan metode string matching untuk mencocokkan kata kunci yang dimasukkan pengguna dengan metadata video, seperti judul, hashtag, dan transkripsi audio. Sistem ini dirancang sebagai aplikasi berbasis web menggunakan PHP dan Python dengan framework Laravel serta PostgreSQL sebagai basis data. Pengujian dilakukan untuk mengevaluasi tingkat akurasi dan performa sistem. Hasil pengujian menunjukkan bahwa sistem mencapai akurasi hingga 82,5% saat menggunakan lebih dari 10 kata kunci, dengan 33 data valid. Pengujian performa juga menunjukkan bahwa MacBook Pro M1 memiliki efisiensi terbaik dibandingkan perangkat lainnya. Penerapan semantik dalam sistem memungkinkan peningkatan akurasi dengan mengurangi ambiguitas makna kata kunci.
Co-Authors Bening, Ridho Gilang Bororing, Jemmy Edwin Ryan Ari Setyawan