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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Nik Mohd Zarifie Hashim
Universiti Teknikal Malaysia Melaka (UTeM)

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Indoor positioning utilizing bluetooth low energy RSSI on LoRa system Kavetha Suseenthiran; Abd Shukur Ja'afar; Ku Wei Heng; Mohamad Zoinol Abidin Abd Aziz; Azmi Awang Md Isa; Siti Huzaimah Husin; Nik Mohd Zarifie Hashim
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp927-937

Abstract

Indoor positioning systems has become popular in this era where it is a network of devices used to locate people or object especially in indoor environment instead of satellite-based positioning. The satellite-based positioning global positioning system (GPS) signal is affected and loss incurred by the wall of the building causes the GPS lack of precision which leads to large positioning error. As a solution to the indoor area coverage problem, an indoor positioning based on bluetooth low energy (BLE) and long range (LoRa) system utilising the receive signal strength indicator (RSSI) is proposed, designed and tested. In this project, the prototype of indoor positioning system is built using node MCU ESP 32, LoRa nodes and BLE beacons. The node MCU ESP 32 will collect RSSI data from each BLE beacons that deployed at decided position around the area. Then, linear regression algorithm will be used in distance estimation. Next, particle filteris implemented to overcome the multipath fading effect and the trilateration technique is applied to estimate the user’s location. The estimated location is compared to the actual position to analyze the root mean square error (RMSE) and cumulative distribution function (CDF). Based on the experiment result, implementing the particle filter reduces the error of location accuracy. The particle filter achieves accuracy with 90% of the time the location error is lower than 2.6 meters.
Assessment of detection methods for back-end process defects in equipment and devices in semiconductor manufacturing Ameer Farhan Roslan; Masrullizam Mat Ibrahim; Nik Mohd Zarifie Hashim; Mohd Syahrin Amri Mohd Noh; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 2: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i2.pp494-503

Abstract

Defect detection plays a pivotal part in the manufacturing process of semiconductors. Defects can be rooted in the product on its own, as well as the tools used to process and make the product, particularly the equipment and machinery used. Defect detection is crucial in semiconductor manufacturing, where even minor flaws can compromise product performance. Defect detection in the backend process of semiconductor manufacturing, specifically in die attach and die bonding, is critical for ensuring product quality and reliability. Die attach involves securing semiconductor chips onto substrates, while die bonding involves connecting wires to the chip. Detecting defects during these processes is vital to prevent issues such as misalignment, inadequate bonding, or contamination, which can lead to malfunctioning chips or devices. Various techniques such as visual inspection, automated optical inspection (AOI), and X-ray imaging are utilized to identify defects like cracks, voids, or irregularities in bond formation. By employing rigorous defect detection measures, manufacturers can uphold stringent quality standards and produce reliable semiconductor devices for various applications.
Co-Authors Abd Shukur Ja'afar Ameer Farhan Roslan Azmi Awang Md Isa Kavetha Suseenthiran Ku Wei Heng Masrullizam Mat Ibrahim Mohamad Zoinol Abidin Abd Aziz Mohd Syahrin Amri Mohd Noh Siti Huzaimah Husin Tole Sutikno