iFinderTC: Solusi Navigasi Indoor Berbasis AR dan BLE pada Platform iOS untuk Gedung Teknik Informatika ITS

Simanjuntak, Jesse (2026) iFinderTC: Solusi Navigasi Indoor Berbasis AR dan BLE pada Platform iOS untuk Gedung Teknik Informatika ITS. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

**Bahasa Indonesia (rapi tanpa alenia baru):**

Navigasi indoor di lingkungan kampus, khususnya pada bangunan dengan karakter arsitektur yang homogen seperti Gedung Teknik Informatika Institut Teknologi Sepuluh Nopember (ITS), masih menjadi tantangan bagi pengunjung yang belum familiar karena solusi konvensional berupa rambu fisik kurang efektif, Global Positioning System (GPS) berperforma buruk di dalam ruangan, dan navigasi Augmented Reality (AR) berbasis kamera rentan gagal melacak pada area bertekstur minim atau pencahayaan yang tidak konsisten. Penelitian terdahulu di ITS juga belum berfokus pada kegunaan nyata sistem serta jarang membahas implementasi native pada platform iOS. Penelitian ini bertujuan merancang, mengembangkan, dan mengevaluasi aplikasi navigasi indoor berbasis kombinasi AR dan Bluetooth Low Energy (BLE) bernama iFinderTC pada Gedung Teknik Informatika ITS. Pengembangan sistem menggunakan pendekatan Lean Software Development yang dipandu oleh siklus Plan-Do-Check-Act (PDCA) secara iteratif. Aplikasi dibangun pada iOS menggunakan Swift, memanfaatkan ARKit untuk visualisasi dan pelacakan berbasis Visual-Inertial Odometry, enam beacon BLE Minew i10 untuk lokalisasi berbasis Received Signal Strength Indicator (RSSI) yang difilter menggunakan Exponential Moving Average, diestimasi melalui trilaterasi dengan Linear Least-Squares dan algoritma Levenberg–Marquardt, distabilkan menggunakan Kalman Filter, serta menerapkan algoritma A* untuk pencarian jalur optimal. Pengujian dilakukan terhadap 10 partisipan yang terbagi menjadi kelompok yang tidak familiar dan cukup familiar terhadap gedung melalui pengujian fungsional black-box, System Usability Scale (SUS), serta konstruk Technology Acceptance Model (TAM), yaitu Perceived Usefulness (PU) dan Behavioral Intention to Use (BI). Hasil pengujian menunjukkan tingkat keberhasilan fungsional sebesar 90% (36 dari 40 skenario), skor SUS rata-rata 73 pada kelompok tidak familiar dan 78 pada kelompok cukup familiar (kategori *Good*), serta persepsi PU dan BI yang positif dengan median dan modus dominan sebesar 4 dan 5. Kendala utama ditemukan pada ketidakstabilan lokalisasi yang memengaruhi konsistensi visualisasi jalur AR, meskipun peta dua dimensi dapat berfungsi sebagai alternatif navigasi. Penelitian ini menyimpulkan bahwa iFinderTC berhasil memenuhi tujuan sebagai solusi navigasi indoor berbasis AR dan BLE yang dapat diterima dan bermanfaat bagi pengguna dengan tingkat familiaritas lingkungan yang berbeda, dengan peningkatan stabilitas lokalisasi sebagai area pengembangan utama pada penelitian selanjutnya.
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Indoor navigation in campus environments, particularly within buildings characterized by homogeneous architectural layouts such as the Informatics Engineering Building at Institut Teknologi Sepuluh Nopember (ITS), remains a challenge for unfamiliar visitors because conventional solutions such as physical signage are often ineffective, the Global Positioning System (GPS) performs poorly indoors, and camera-based Augmented Reality (AR) navigation is prone to tracking failures in low-texture areas or under inconsistent lighting conditions. Previous studies conducted at ITS have also paid limited attention to the real-world usability of such systems and have rarely addressed native implementation on the iOS platform. This study aims to design, develop, and evaluate an indoor navigation application that combines AR and Bluetooth Low Energy (BLE), named iFinderTC, for deployment in the ITS Informatics Engineering Building. The system was developed using a Lean Software Development approach guided by iterative Plan-Do-Check-Act (PDCA) cycles. The application was built for iOS using Swift, leveraging ARKit for visualization and Visual-Inertial Odometry-based tracking, six Minew i10 BLE beacons for Received Signal Strength Indicator (RSSI)-based localization filtered using an Exponential Moving Average, estimated through trilateration with Linear Least-Squares and the Levenberg–Marquardt algorithm, stabilized using a Kalman Filter, and employing the A* algorithm for optimal pathfinding. Evaluation involved 10 participants divided into unfamiliar and moderately familiar groups through black-box functional testing, the System Usability Scale (SUS), and Technology Acceptance Model (TAM) constructs consisting of Perceived Usefulness (PU) and Behavioral Intention to Use (BI). The results showed a functional success rate of 90% (36 out of 40 scenarios), average SUS scores of 73 for the unfamiliar group and 78 for the moderately familiar group (both classified as *Good*), and positive PU and BI perceptions with dominant median and mode values of 4 and 5. The primary limitation identified was localization instability, which affected the consistency of AR path visualization, although the two-dimensional map served as a reliable alternative navigation method. This study concludes that iFinderTC successfully achieves its objective as an AR- and BLE-based indoor navigation solution that is both acceptable and beneficial for users with different levels of environmental familiarity, while improved localization stability remains the primary direction for future development.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Navigasi indoor, Augmented Reality, Bluetooth Low Energy, trilaterasi, usability. Indoor navigation, Augmented Reality, Bluetooth Low Energy, trilateration, usability.
Subjects:	T Technology > T Technology (General) > T58.62 Decision support systems
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis
Depositing User:	Jesse Robinson Junior Simanjuntak
Date Deposited:	22 Jul 2026 05:40
Last Modified:	22 Jul 2026 05:40
URI:	http://repository.its.ac.id/id/eprint/136023

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