Laporan kerja praktek 22 Juni 2026 dengan The Cohesive Companies

Zahra, Azkiya Rusyda (2026) Laporan kerja praktek 22 Juni 2026 dengan The Cohesive Companies. Project Report. [s.n.]. (Unpublished)

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Abstract

Cohesive (The Cohesive Companies) merupakan perusahaan integrator digital di bawah Bentley Systems yang berfokus pada solusi digital twin infrastruktur dan enterprise asset management. Produk yang kami kerjakan saat melakukan Kerja Praktik konversi Capstone Project adalah GIS Layer Platform (SAWIT: Spatial Analysis Workflow & Information Twin), yaitu aplikasi Sistem Informasi Geografis berbasis web multi-tenant untuk mengunggah, mengelola, dan memvisualisasikan data spasial komoditas kelapa. Peran utama yang dijalankan dalam tim adalah Data Research & Data Engineer yang bertanggung jawab atas validitas kriteria data agroklimat dan efisiensi berkas spasial. Kegiatan rekayasa data dilakukan dengan memanfaatkan Google Scholar untuk ekstraksi parameter pertumbuhan varietas kelapa, perangkat lunak QGIS untuk pemotongan area (clipping) dataset mentah berskala besar, serta pemrograman Python untuk otomatisasi pembersihan koordinat kosong dan penataan ulang skema atribut ke format GeoJSON. Kami diminta untuk menyiapkan jaminan optimalisasi data agar layer geospasial siap di-render secara ringan dan responsif pada Cesium Engine 3D. Solusi pengembangan selanjutnya yang diusulkan untuk mengatasi kendala ukuran berkas data yang besar adalah penerapan teknik spatial tiling dan penyederhanaan geometri vektor (simplification).
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Cohesive (The Cohesive Companies) is a digital integrator company under Bentley Systems that focuses on infrastructure digital twin solutions and enterprise asset management. The product developed during the Practical Work conversion of the Capstone Project is the GIS Layer Platform (SAWIT: Spatial Analysis Workflow & Information Twin), a multi-tenant web-based Geographic Information System application designed to upload, manage, and visualize spatial data for coconut commodities. The primary role performed within the team was Data Research & Data Engineer, responsible for the validity of agroclimate data criteria and the efficiency of spatial files. Data engineering activities were conducted by utilizing Google Scholar for extracting growth parameters of coconut varieties, QGIS software for area clipping of large-scale raw datasets, and Python programming to automate the cleaning of empty coordinates and the restructuring of attribute schemas into the GeoJSON format. We were required to ensure data optimization so that the geospatial layers are ready to be rendered efficiently and responsively on the 3D Cesium Engine. The proposed subsequent development solution to overcome the constraint of large data file sizes is the implementation of spatial tiling techniques and vector geometry simplification.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	Geospasial, Geospatial, GeoJSON, QGIS, Python, Spatial Tiling
Subjects:	T Technology > T Technology (General) > T385 Visualization--Technique
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis
Depositing User:	AZKIYA RUSYDA ZAHRA
Date Deposited:	07 Jul 2026 07:48
Last Modified:	07 Jul 2026 07:48
URI:	http://repository.its.ac.id/id/eprint/134035

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