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Evaluasi Kapasitas dan Level of Service (LOS) pada Kawasan Pendidikan dan Komersial di Purwokerto Muhammad Edwin Rachmanudin; Nabillah Febi Saputri; Bayu Septiaji Wicaksana
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk menganalisis kinerja ruas Jalan Letjend Pol. Soemarto di Purwokerto sebagai kawasan pendidikan dan komersial melalui evaluasi kapasitas jalan dan tingkat pelayanan (Level of Service/LOS). Survei dilakukan pada dua sesi waktu, yaitu pagi (10.20–11.20 WIB) dan sore (16.00–17.00 WIB), dengan menggunakan metode classified count dan analisis berdasarkan Pedoman Kapasitas Jalan Indonesia (PKJI) 2023. Hasil penelitian menunjukkan bahwa volume lalu lintas rata-rata adalah 1.270 smp/jam dengan dominasi sepeda motor (58,5% dalam smp). Kapasitas efektif jalan sebesar 2.288 smp/jam diperoleh setelah mempertimbangkan faktor penyesuaian lebar jalur, hambatan samping, pemisahan arah, dan ukuran kota. Nilai Derajat Kejenuhan (Dj) sebesar 0,56 mengindikasikan kondisi jalan berada pada Level of Service (LOS) A, yaitu arus bebas dengan kecepatan tinggi dan tundaan minimal. Hambatan samping termasuk dalam kategori rendah dengan nilai total antara 110,2–156,3. Hasil ini menunjukkan bahwa ruas jalan masih memiliki cadangan kapasitas sekitar 44% dan berkinerja sangat baik, meskipun berlokasi di kawasan yang secara persepsi dianggap ramai. Studi ini merekomendasikan pemantauan berkala dan pengelolaan hambatan samping untuk mempertahankan kinerja optimal ruas jalan.
Applying Artificial Intelligence Algorithms for Optimalizing The Electricity Distribution Network Susatyo Adhi Pramono; Endang Sri Wahyuningsih; Basuki; Isra’ Nuur Darmawan; Muhammad Edwin Rachmanudin
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 3 (2024): November 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i3.4299

Abstract

Abstract: This research aims to apply artificial intelligence (AI) algorithms to optimize the electricity distribution network, focusing on improving efficiency, responsiveness, and integration of renewable energy. Deep learning and reinforcement learning algorithms are used to learn energy load patterns and adjust distribution in real-time. Through simulation of the electricity distribution network, this research found a 15% increase in energy efficiency, a reduction in response time by 85%, a 10% increase in maximum load capacity, and a 25% increase in the use of renewable energy. Additionally, operational costs of the network decreased by 12% due to automation generated by AI. The innovation of this research lies in the efficient integration of renewable energy sources and load management through more accurate prediction. The research results show that applying AI in the electricity distribution network can provide an effective and sustainable solution to reduce power loss and operational costs, as well as support the use of renewable energy. Therefore, this research contributes to the development of a smarter and more environmentally friendly electricity distribution system.
Sustainable Innovation in Community Service as an Effort to Build an Adaptive and Resilient Social Ecosystem Susatyo Adhi Pramono; Endang Sri Wahyuningsih; Basuki; Irawan Dharma Sukowati; Muhammad Edwin Rachmanudin
Tirakat: Jurnal Terobosan Peduli Masyarakat Vol 3 No 2 (2026): May 2026
Publisher : PT. LITERASI SAINS NUSANTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61100/j.tirakat.v3i2.334

Abstract

This study aims to enrich the body of knowledge related to community service, particularly in the context of sustainable innovation as an effort to develop an adaptive and resilient social ecosystem. The research employs a qualitative approach using a literature review method analyzed descriptively. Data were obtained from Google Scholar and various credible websites with a publication range from 1984 to 2026. Of the 50 articles identified in the initial stage, a rigorous selection process was conducted based on relevance, quality, and methodological suitability, resulting in 37 articles for further analysis. The findings indicate that sustainable innovation in community service plays a strategic role in enhancing individual and community capacities, strengthening social resilience, and fostering the development of adaptive social ecosystems. Innovative approaches that integrate technology, community participation, and multi-stakeholder collaboration have proven effective in improving program effectiveness and sustainability. Furthermore, the findings reveal that successful implementation is significantly influenced by policy support, access to resources, and the community’s ability to adapt to change. However, several challenges remain, including limited innovation literacy, lack of synergy among stakeholders, and financial constraints. Therefore, more integrated and sustainable strategies are required to optimize the role of innovation in community service.