Peningkatan Akurasi Micro-Location Berbasis Ble Beacon Menggunakan Filter Kalman

Bachtiar, Syafrie Bachtiar (2026) Peningkatan Akurasi Micro-Location Berbasis Ble Beacon Menggunakan Filter Kalman. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Stabilitas sinyal Received Signal Strength Indicator (RSSI) merupakan tantangan utama dalam sistem Micro-Location berbasis Bluetooth Low Energy (BLE) Beacon, di mana noise lingkungan sering menyebabkan deviasi estimasi jarak dan inkonsistensi konten audio (switch- ing). Penelitian ini mengevaluasi efektivitas penerapan algoritma Filter Kalman pada dua lapisan arsitektur berbeda, yaitu Application Layer dan Data Link Layer (pada firmware ESP32), untuk meningkatkan akurasi dan stabilitas sistem. Hasil pengujian komparatif menunjukkan karakteristik kinerja yang berbeda pada kedua pendekatan. Implementasi pada Application Layer unggul dalam responsivitas dengan waktu proses rata-rata 108,47 ms, namun peningkatan akurasi estimasi jarak terbatas pada 7,2% (RMSE 2,2194 m). Selain itu, pada kondisi diam di titik referensi dengan gangguan sinyal tinggi, metode ini hanya mampu mencapai akurasi konten audio sebesar 80%, serta masih menyisakan frekuensi switching audio sebanyak 4 kali pada skenario bergerak. Sebaliknya, implementasi pada Data Link Layer terbukti menghasilkan stabilitas sistem yang lebih tinggi. Metode ini mencatatkan penurunan error estimasi jarak (RMSE) sebesar 18% menjadi 1.9636 m dan mereduksi frekuensi switching audio secara signifikan dari 10 kali (tanpa filter) menjadi 1 kali. Meskipun waktu respons rata-rata meningkat menjadi 221,67 ms, hasil pengujian pada posisi diam menunjukkan konsistensi akurasi konten mencapai 100% di seluruh titik uji. Penelitian ini menyimpulkan bahwa pemrosesan sinyal pada Data Link Layer merupakan pendekatan yang lebih efektif untuk aplikasi yang memprioritaskan validitas data
dan kenyamanan pengguna dibandingkan kecepatan respons sistem.
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Signal stability of the Received Signal Strength Indicator (RSSI) presents a major challenge in Bluetooth Low Energy (BLE) based Micro-Location systems, where environmental noise often causes distance estimation deviations and audio content inconsistency (switching). This study evaluates the effectiveness of applying the Kalman Filter algorithm at two differ- ent architectural layers, namely the Application Layer and the Data Link Layer (on ESP32 firmware), to enhance system accuracy and stability. Comparative test results demonstrate distinct performance characteristics between the two approaches. Implementation at the Application Layer excels in responsiveness with an average processing time of 108.47 ms, but distance estimation accuracy improvement is limited to 7.2% (RMSE 2.2194 m). Furthermore, in static conditions at a reference point with high signal interference, this method is only able to achieve an audio content accuracy of 80%, and still leaves an audio switching frequency of 4 times in moving scenarios. In contrast, implementation at the Data Link Layer proves to yield higher system stability. This method records a reduction in distance estimation error (RMSE) of 18% to 1.9636 m and significantly reduces audio switching frequency from 10 times (without filter) to 1 time. Although the average response time increases to 221.67 ms, test results in static positions show audio content accuracy consistency reaching 100% across all test points. This study concludes that signal processing at the Data Link Layer is a more effective approach for applications prioritizing data validity and user comfort over system response speed.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Micro-Location, BLE Beacon, RSSI, Filter Kalman, Application Layer, Data Link Layer, ESP32
Subjects:	T Technology > T Technology (General) > T58.5 Information technology. IT--Auditing
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Syafrie Bachtiar Bachtiar
Date Deposited:	20 Jan 2026 03:43
Last Modified:	20 Jan 2026 03:43
URI:	http://repository.its.ac.id/id/eprint/129793

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