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Adaptive weighted multi-criteria decision making using modified dijkstra’s algorithm: integrating real-time traffic conditions with hybrid WSM-WPM for dynamic route optimization Basorudin Basorudin; Handaru Jati; Nurkhamid Nurkhamid; Antoni Pribadi; Satria Riki Mustafa; Puput Dani Prasetyo Adi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 4: December 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i4.pp1929-1943

Abstract

Traffic congestion is a problem that needs to be solved. A smart route optimization system is needed to overcome this problem, not only using traditional methods but also using algorithms that have the ability to find the shortest route. This study proposes a framework system for multi-criteria decision making that adapts and improves the Dijkstra and weighted product method (WPM) algorithms. The Dijkstra algorithm is modified to be more integrated in solving the fastest travel route, anticipating traffic congestion, improving road safety, saving fuel, and providing real-time data. The weighted sum method (WSM)-WPM hybrid framework has the advantage of WSM additive normalization with the zero-dimensional properties of WPM to overcome different measurement units. Experimental results show a significant reduction in travel time and fuel consumption, as well as an increase in route safety percentage. This system maintains computational efficiency, and this research provides a practical and scalable solution for intelligent transportation systems (ITS), improving the driver experience and overall traffic network safety. The results of the congestion avoidance configuration with the highest hybrid score show a result of 0.4573, yielding a viable alternative route, namely (V1→V3→V6→V9→V12→V14).
Implementasi pelatihan AI multimodal berbasis human-in-the-loop untuk penilaian melalui bank kasus lintas bidang di SMK Negeri 1 Bantul Handaru Jati; Yuniar Indrihapsari; Susilo Romadhon; Pradana Setialana; Rheisan Firnandatama Rizky Satria
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 4 (2026): November (In Progress)
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/px7a5s45

Abstract

Pemanfaatan kecerdasan buatan (AI) generatif dan multimodal membuka peluang untuk mendukung penilaian respons peserta didik. Namun, penggunaannya tetap memerlukan verifikasi manusia karena kesalahan dapat terjadi sejak pembacaan dokumen hingga pemberian skor dan umpan balik. Kegiatan pengabdian ini bertujuan mengimplementasikan pelatihan AI multimodal berbasis human-in-the-loop untuk mendukung penilaian dan mengembangkan bank kasus lintas bidang sebagai perangkat pelatihan. Kegiatan dilaksanakan pada 14–17 Juli 2026 di SMK Negeri 1 Bantul dan diikuti oleh 20 guru lintas bidang. Pelatihan mencakup pengenalan AI generatif dan multimodal, demonstrasi ChatGPT, Gemini, dan DeepSeek, latihan berbasis bank kasus, serta verifikasi keluaran AI. Bank kasus terdiri atas 30 butir dari Fisika, Kalkulus, barisan dan deret geometri, serta Sejarah Indonesia. Evaluasi tindak lanjut menggunakan 12 pernyataan skala Likert. Hasil evaluasi menunjukkan rerata penilaian sebesar 4,36 dari skala 5 dan 90,0% respons berada pada kategori setuju atau sangat setuju. Analisis artefak mengidentifikasi enam area yang memerlukan verifikasi manusia, mulai dari penyiapan dokumen hingga keputusan akhir. Hasil kegiatan menunjukkan bahwa AI dapat digunakan sebagai alat bantu penilaian, sedangkan keputusan akhir tetap berada pada guru.