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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Regional Innovation
Septem Riza, Lala
Unknown Affiliation
Humanities Computer Science & IT Economics, Econometrics & Finance Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Eligibility rate of applicant’s LinkedIn account: a naïve bayes classification and visualization Fariza Abu Samah, Khyrina Airin; Athirah Ahmad, Nurul; Amilah Shari, Anis; Fakhira Almarzuki, Hana; Arafah, Zuhri; Septem Riza, Lala; Abdul Halim, Amir Haikal
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4334-4343

Abstract

In the digital era, social media platforms like LinkedIn have become famous for recruitment, and recruiters widely use them to find potential employees. The recruitment process is crucial in organizations, as it involves selecting qualified applicants from a diverse pool. However, the screening process and manual recruitment process entail significant time, high costs, and potential bias. Consequently, it may cause recruiting unqualified applicants and may affect the organizations. Thus, this study aims to classify and generate a list of potential job applicants by analyzing seven attributes of their LinkedIn accounts: title, location, skills, education, language, certification, and years of experience. Data are collected from LinkedIn profiles and then undergo data pre-processing. The naive Bayes (NB) algorithm is implemented as the classification algorithm and sets the classification as “eligible” or “ineligible”. The NB model achieved an accuracy testing of 89.8%, indicating good performance in classifying potential job applicants. At the same time, we measure the similarity cosine score to set the mean of the eligibility. The classification results are visualized for the suitable applicants in descending rank, allowing users to choose the applicants’ classification status efficiently. For the system usability, we managed to get 90% from the recruitment expert.
Energy Management of a Low-Cost Power Meter using ESP8266 and PZEM-016 Syafri Syamsudin, Muhammad; Septem Riza, Lala; Rasim, Rasim
International Journal of Regional Innovation Vol. 4 No. 1 (2024): International Journal of Regional Innovation
Publisher : Inovbook Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52000/ijori.v4i1.97

Abstract

The burgeoning significance of the Internet of Things (IoT) lies in its capacity to configure interconnected environments and facilitate human-object interactions through collaborative services. This study proposes an efficient energy management approach leveraging cost-effective technologies like the ESP8266 microcontroller and the PZEM-016 Modbus RTU energy monitoring module. Tailored towards wireless connectivity, this solution is purposefully crafted for diverse sectors operating within constrained budgets, obviating the need for intricate infrastructure. A systematic deployment of the forward engineering research methodology is undertaken to discern the requisites and hurdles inherent in energy management. The amalgamation of ESP8266, PZEM-016, and the MQTT protocol, with RabbitMQ serving as a message broker, forges an efficacious framework for inter-device information exchange. The solution's instantiation entails the interconnection of power meter devices using the MQTT protocol, transmitting data in JSON format. The PZEM-016 sensor constitutes the crux, adeptly measuring voltage, current, frequency, and power with precision. Furthermore, the solution encompasses a prototype Smart Meter fortified with Wi-Fi connectivity to the internet, thus extending network coverage ubiquitously. Economic scrutiny reveals that the resultant power meter device costs less than 100 USD, competitively positioning it against analogous market offerings. This economically optimized design advocates for widespread adoption across multifarious sectors constrained by budgetary limitations, assuaging the complexities inherent in energy management through a trifecta of efficiency, reliability, and affordability.
Co-Authors Abdul Halim, Amir Haikal Amilah Shari, Anis Arafah, Zuhri Athirah Ahmad, Nurul Fakhira Almarzuki, Hana Fariza Abu Samah, Khyrina Airin Rasim, Rasim Syafri Syamsudin, Muhammad