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Optimalisasi Penentuan Bonus Karyawan dengan Sistem Pendukung Keputusan Metode TOPSIS di PT. Elizabeth Hanjaya Asia, Siti Nur; Fuad, M Noor; Saleh, Husna; As'ad, Muhammad; Irfan, Irfan
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 6 No. 4 (2025)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol6iss4pp996-1009

Abstract

PT. Elizabeth Hanjaya is a retail company that provides various fashion products, PT. Elizabeth Hanjaya is a retail company that offers a variety of fashion products such as bags, shoes, accessories, and fashion supplies for men and women. This study uses the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method to build a decision support system in determining employee bonus recipients in this company. The purpose of the study is to design a system that can assess the feasibility of receiving employee bonuses based on the TOPSIS method. This method works by choosing an alternative that has the closest distance from the positive ideal solution and the furthest from the negative ideal solution based on geometric principles. The system is designed using Unified Modeling Language (UML) and developed with the PHP programming language. The results of the study show that the assessment system is able to produce accurate decisions. Based on testing with four alternatives, the TOPSIS method determines alternative 1 as the employee who is most eligible to receive a bonus with a final value of 0.675360. In addition, user evaluation results showed a high level of satisfaction, with 92% of respondents giving a "strongly agree" rating.
Rancang Bangun Tong Sampah Cerdas Menggunakan Suara Sebagai Media Informasi Berbasis Arduino Uno Nur Asia, Siti; Sofyan, Sofyan; Saleh, Husna; Ikhwan Mardin, Muhammad; Noor Fuad, M
Jurnal JEETech Vol. 6 No. 1 (2025): Nomor 1 May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v6i1.6108

Abstract

Garbage is one of the problems that we often encounter in the community. One of the factors causing the accumulation of garbage is the lack of public awareness to dispose of garbage in its place. In this problem, it is necessary to have a smart trash can using sound information media which includes Ultrasonic Sensors as distance detectors and trash volume detectors, Servos are used to control the trash can cover, Speakers are used as information media, DFPlayer mini is used as a voice recorder and microcontrollers are used as input data processors from the components used. The trash can cover will open and close automatically by detecting humans at a distance of ≤ 30 cm then detecting the height of the trash from the trash can cover ≤ 10 cm then the trash can is full then the trash can cover will not open and emit information in the form of sound. The method used in this study is the experimental method, namely by designing, assembling, and testing a smart trash can system based on Arduino Uno. Testing was conducted to evaluate the performance of the sensor, and the voice module in responding to the presence of objects in front of the trash can. This research is useful for the community because it can increase awareness in disposing of garbage in its place through an interactive approach in the form of sound, thus supporting the creation of a cleaner and more orderly environment. In addition, scientifically, this research contributes to the development of science and technology, especially in the field of hardware that can be used as a basis for similar innovations in various fields of life.
An analysis of speech act in whatsapp Syawal, La Ode Muhamad Irwin; Mardin, Muhammad Ikhwan; Saleh, Husna; Fuad, M. Noor; As’Ad, Muhammad
Indonesia Berdaya Vol 5, No 2 (2024)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.2024774

Abstract

Language is a crucial aspect of our lives, serving as a bridge for communication among individuals. People use language to convey emotions, ideas, desires, and feelings. One platform for communication is WhatsApp. Many people enjoy chatting on WhatsApp, but not all of them grasp the meaning behind each utterance spoken or sent by the speaker or sender. Various linguistic aspects, including speech acts, can be explored on WhatsApp, such as pragmatics, semantics, and sociolinguistics. This study aims to analyze the factors that lead to misunderstandings when performing perlocutionary acts on WhatsApp and how locutionary acts influence perlocutionary acts on the platform. The research findings identify several causes of misunderstandings in the communication process through WhatsApp. Firstly, incorrect punctuation usage contributes to misunderstandings. Secondly, typographical errors are another common factor. Thirdly, incomplete sentences resulting from typing too quickly make it challenging to comprehend the intended message. Fourthly, issues such as poor network connectivity lead to only a fraction of the message reaching the recipient. Additionally, locutionary acts represent the literal meaning of a sentence. The conclusion of this research is the impact of locution on perlocution depends on how effectively locution can convey instructions or meanings of the spoken sentence. If the utterance is not well-understood by the listener, they may not execute or comprehend the intended meaning, leading to perlocutionary acts and miscommunication between the individuals involved.
Application of Computer Vision for Customer Insights: Demographics and Visit Duration in Coffee Shops Faisal; Rachmat; Saleh, Husna; Irfan; As’ad, Muhammad
Research Horizon Vol. 5 No. 5 (2025): Research Horizon - October 2025
Publisher : LifeSciFi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54518/rh.5.5.2025.811

Abstract

The coffee shop industry is increasingly competitive, requiring business owners to adopt data-driven strategies rather than rely solely on intuition, as traditional approaches such as surveys and manual observation are often subjective, time-consuming, and lack scalability. This study aims to design, implement, and evaluate an end-to-end intelligent system based on computer vision to automatically and non-intrusively analyze customer demographics (age and gender) and visit duration (dwell time). The proposed framework emphasizes both technical accuracy and privacy-by-design principles, where facial data is processed in real time without storage, and only anonymized metadata is utilized for business analysis. Using a simulated 60-minute test video containing 50 virtual customers with balanced gender, varied age groups, and predetermined visit durations, the system was evaluated and demonstrated strong performance, achieving 96% accuracy in gender classification, 89% in age group classification, and a Mean Absolute Error (MAE) of less than 45 seconds in dwell time measurement. The findings confirm that the ethical application of computer vision can provide valuable business insights, including the identification of demographic-based peak hours, the recognition of product preferences, and the optimization of spatial layouts, ultimately enabling coffee shops and SMEs to enhance competitiveness and profitability through data-driven decision-making.