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All Journal SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL d'Cartesian: Jurnal Matematika dan Aplikasi Jurnal Informatika dan Rekayasa Perangkat Lunak
Winsy Weku
Universitas Sam Ratulangi
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Mathematics Social Sciences Other

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Sistem Pendukung Keputusan Dalam Memetakan Wilayah Risiko Banjir Menggunakan Fuzzy Multi Criteria Decision Making Glorya Ontah; Winsy Weku; Altien Rindengan
d\'Cartesian: Jurnal Matematika dan Aplikasi Vol. 3 No. 2 (2014): September 2014
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/dc.3.2.2014.5439

Abstract

Abstrak Banjir yang melanda di berbagai wilayah Indonesia merupakan suatu fenomena logis karena negara ini berada di daerah tropis dengan intensitas curah hujan yang sangat tinggi. Penelitian bertujuan untuk memetakan daerah berisiko banjir di Kota Manado. Pemetaan wilayah berisiko banjir di Kota Manado memerlukan beberapa pendapat atau masukan dari berbagai pihak. Atribut yang digunakan yaitu kemiringan lahan (%), ketinggian wilayah (%), DAS (km), luas pemukiman/wilayah tutupan lahan (%) dan curah hujan (mm). Penentuan wilayah banjir di Kota Manado menggunakan Fuzzy Multi Criteria Decision Making (MCDM) dengan dua (2) metode yaitu Simple Additive Weighting Method (SAW) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Hasil dengan menggunakan metode SAW dan SAW Fuzzy menunjukkan bahwa wilayah paling berisiko banjir yaitu Kecamatan Wenang. Hasil dengan menggunakan metode TOPSIS dan TOPSIS Fuzzy menunjukkan bahwa wilayah paling berisiko banjir yaitu Kecamatan Bunaken. Wenang sebagai wilayah banjir disebabkan lahan yang berada di dataran landai, ketinggian wilayah di bawah 240 meter, memiliki aliran sungai, intensitas curah hujan tinggi, dan besarnya tutupan lahan mencapai 94,59%. Bunaken menjadi wilayah banjir karena Bunaken memiliki aliran sungai terpanjang di Kota Manado yaitu 17,9 km. Kata kunci: Fuzzy, Kota Manado, MCDM, SAW, TOPSIS, Wilayah Banjir.
Extreme Programming Method for Efficient and User-Friendly Web-Based Photo Studio Reservations: Pilvi Project Case Gherika Gerungan; Winsy Weku; Eric Alfonsius
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 2 (2026): Volume 7 Number 2 June 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v7i2.704

Abstract

The development of information technology has accelerated the digitalization of services across various sectors, including the photography industry. Pilvi Project is a photo studio that offers photography services for various needs, such as graduation photos, ID photos, and more. However, the current reservation process, which is still carried out manually via WhatsApp, presents several challenges, including scheduling conflicts and limited access to service information for users. This study aims to design and develop a web-based photo studio reservation system using the Extreme Programming (XP) methodology. XP was chosen for its iterative and flexible approach, which allows for rapid adaptation to user needs. The system includes key features such as user registration and login, studio reservations based on availability, service package selection, and admin-controlled data management. The result of this study is a structured and organized photo studio reservation website capable of efficiently managing bookings. Based on black-box testing, all system features functioned as intended. Questionnaire results indicated positive user responses, highlighting the system's ease of use and overall user experience. An evaluation by the Pilvi Project team confirmed that the system successfully met their requirements.
GEOAI-BASED SPATIOTEMPORAL ASSESSMENT OF SURFACE URBAN HEAT ISLAND DYNAMICS AND LAND COVER CHANGE USING GOOGLE EARTH ENGINE: EVIDENCE FROM MANADO CITY, INDONESIA Fidelia Anninda Fabiolani; Winsy Weku; Eric Alfonsius
SOSIOEDUKASI Vol 15 No 3 (2026): SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL
Publisher : Fakultas Keguruan Dan Ilmu Pendidikan Universaitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/sosioedukasi.v15i3.9248

Abstract

Rapid urbanization has significantly transformed land cover patterns and intensified the Surface Urban Heat Island (SUHI) phenomenon in many tropical cities, posing increasing environmental and public health challenges. However, comprehensive long-term assessments integrating land cover dynamics, land surface temperature (LST), and SUHI using cloud-based geospatial platforms remain limited, particularly in rapidly developing cities of eastern Indonesia. This study investigates the spatiotemporal relationship between land cover change and SUHI dynamics in Manado City, Indonesia, between 2000 and 2023 by integrating Landsat imagery, Google Earth Engine (GEE), and a GeoAI-based Random Forest classification approach. Landsat 7 ETM+ and Landsat 9 OLI/TIRS datasets were processed to generate land cover maps and retrieve LST, while SUHI intensity was derived from spatial thermal anomalies. Classification accuracy was evaluated using confusion matrices, achieving Overall Accuracy of 95.28% (Kappa = 0.915) for 2000 and 92.00% (Kappa = 0.870) for 2023. Results reveal a substantial decline in vegetation from 10.844,523 ha (75,69%) to 9.724,045 ha (67,87%), accompanied by an expansion of built-up land from 3.374,629 ha (23,55%)  to 3.939,957 ha (27,49%). These land cover transformations corresponded with an increase in average LST from 33.79°C to 37.08°C and a spatial expansion of high-intensity SUHI zones from the urban core toward developing suburban districts. Subdistrict-level analysis further shows considerable spatial heterogeneity in thermal conditions, with the greatest warming occurring in the most intensively developed areas. The results confirm that urban expansion and vegetation loss are the principal drivers of increasing SUHI intensity in Manado, supporting climate-responsive urban planning and sustainable land-use management
Co-Authors Alfonsius, Eric Altien Rindengan Fidelia Anninda Fabiolani Gherika Gerungan Glorya Ontah