PRASETYANI, Marita and Isnanto, R. Rizal and Widodo, Catur Edi (2025) PENENTUAN LOKASI POTENSIAL UNTUK PEMBANGUNAN REST AREA BARU PADA JALAN RAYA BERBASIS DATA GOOGLE MAPS DAN ANALISIS MULTIKRITERIA. Doctoral thesis, UNIVERSITAS DIPONEGORO.

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Abstract

Peningkatan keselamatan dan kenyamanan pengguna jalan merupakan faktor krusial dalam pengelolaan infrastruktur transportasi, khususnya melalui penyediaan rest area yang strategis. Penelitian ini bertujuan untuk menentukan lokasi potensial rest area baru di jalan raya berbasis analisis data Google Maps dan metode MultiCriteria Decision-Making (MCDM). Data dikumpulkan melalui teknik web scraping untuk memperoleh pola kunjungan rest area dari fitur Jam Favorit Google Maps serta pengolahan citra digital untuk menganalisis tingkat kepadatan lalulintas. Alternatif lokasi potensial dihasilkan berdasarkan data tersebut. Penentuan kriteria didasarkan pada integrasi dari tiga sumber utama: kajian literatur terkini, kuesioner terhadap responden ahli untuk mengidentifikasi atribut penting, analisis Principal Component Analysis (PCA) terhadap hasil kuesioner, serta sinkronisasi dengan ketentuan teknis dalam Permen PUPR No. 28 Tahun 2021 tentang Tempat Istirahat. Hasil penelitian menunjukkan bahwa integrasi data pola kunjungan, kepadatan lalu lintas, dan pendekatan MCDM mampu menghasilkan rekomendasi lokasi rest area yang optimal. Evaluasi alternatif dilakukan dengan metode MCDM, yaitu TOPSIS dan WASPAS, menggunakan bobot kriteria yang ditentukan secara objektif melalui metode MEREC. Prototipe sistem informasi yang dikembangkan mendukung pengambilan keputusan berbasis data, meningkatkan efektivitas operasional rest area, serta berkontribusi pada pengelolaan infrastruktur transportasi yang lebih adaptif dan berkelanjutan. Penelitian ini juga membuka peluang inovasi lebih lanjut dalam penerapan teknologi big data dan sistem pendukung keputusan untuk perencanaan transportasi berbasis real-time.
Kata Kunci: Sistem Informasi, Data Mining, Web Scraping, Google Maps, Rest Area, Pengambilan Keputusan Multi-Kriteria, Pengolahan Citra

Enhancing the safety and comfort of road users is a crucial factor in the management of transportation infrastructure, particularly through the provision of strategically located rest areas. This study aims to identify potential locations for new highway rest areas based on Google Maps data analysis and Multi-Criteria Decision-Making (MCDM) methods. Data were collected through web scraping techniques to obtain visitation patterns from Google Maps’ Popular Times feature, as well as through digital image processing to analyze traffic density levels. Potential alternative locations were generated based on the collected data. The determination of evaluation criteria was based on the integration of three main sources: a comprehensive review of current literature, questionnaires distributed to expert respondents to identify key attributes, Principal Component Analysis (PCA) applied to the questionnaire results, and synchronization with the technical standards stipulated in the Indonesian Ministry of Public Works Regulation No. 28 of 2021 regarding Rest Areas. The findings indicate that the integration of visitation pattern data, traffic density, and the MCDM approach can effectively generate optimal recommendations for rest area locations. The evaluation of alternatives was conducted using MCDM methods, namely TOPSIS and WASPAS, with criterion weights objectively determined using the MEREC method. The developed information system prototype supports data-driven decision-making, enhances the operational effectiveness of rest areas, and contributes to the more adaptive and sustainable management of transportation infrastructure. This research also opens further opportunities for innovation in the application of big data technologies and decision support systems for real-time transportation planning.
Keywords: Information Systems, Data Mining, Web Scraping, Google Maps, Rest Area, Multi-Criteria Decision-Making, Image Recognition

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