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All Journal Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika International Journal of Social and Education (INJOSEDU)
Shafirah Fitri
Institut Teknologi dan Bisnis Bina Sarana Global
Computer Science & IT Social Sciences

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BODY LANGUAGE IN BUSINESS NEGOTIATIONS: STRENGTHS AND WEAKNESSES Melyana R Pugu; Nyi Dewi Puspitasari; Shafirah Fitri
INTERNATIONAL JOURNAL OF SOCIAL AND EDUCATION Vol. 1 No. 1 (2024): April
Publisher : Pondok Pesantren Baitul Quran

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Abstract

This research discusses the influence of body language in business negotiations, with an emphasis on analyzing the strengths and weaknesses of using body language as a non-verbal communication tool. The research was conducted through a literature review method, which involved collecting data from various relevant journal articles, books and other publications on the subject. The results show that body language consistently plays a vital role in supporting the effectiveness of business negotiations, where non-verbal cues such as eye contact, gestures, and facial expressions can reinforce verbal messages and foster trusting relationships. However, the study also revealed that cultural differences and potential misunderstandings can be a drawback in the application of body language, often leading to conflict and inaccurate perceptions of prosperity. The recommendations from this study conclude that training and awareness on multi-cultural body language is an important aspect that needs to be integrated in business negotiation practices in order to maximize the strengths and mitigate the weaknesses of body language.
Sistem Pakar Diagnosa Penyakit TBC Menggunakan Algoritma Forward Chaining dan Certainty Factor Berbasis Android di Puskesmas Kedaung Barat Ujang Sutisna; Argin Fiorenza; Detin Sofia; Shafirah Fitri
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 8, No 2 (2025): Juli
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v8i2.357

Abstract

Abstrak: Tuberkulosis (TBC) termasuk dalam kategori penyakit menular dan hingga sekarang masih menjadi tantangan besar dalam sektor kesehatan di Indonesia. Proses diagnosa dini sangat penting untuk mencegah penyebaran dan mempercepat penanganannya. Tujuan dari penelitian ini adalah membuat sistem pakar berbasis Android, yang dapat digunakan oleh pengguna untuk mendiagnosis penyakit TBC secara mandiri. Aplikasi dibuat menggunakan Flutter, sebuah framework UI lintas platform yang dikembangkan oleh Google dan bahasa pemrograman Dart untuk mendukung pengembangan aplikasi Android. Sistem ini menerapkan metode Forward Chaining untuk menelusuri gejala yang dimasukkan oleh pengguna, serta Certainty Factor untuk menghitung tingkat kepastian hasil diagnosis berdasarkan gejala yang dialami. Pengujian dilakukan terhadap 25 responden dengan membandingkan hasil sistem dan diagnosis tenaga medis. Tingkat akurasi yang diperoleh melalui pengujian menggunakan metode Confusion Matrix mencapai 84% dengan tampilan antarmuka yang memudahkan pengguna untuk mendapatkan indikasi awal TBC serta solusi tindak lanjut, sehingga mendorong pengguna untuk segera melakukan pemeriksaan ke fasilitas kesehatan.Kata kunci: Sistem Pakar, Tuberkulosis, Forward Chaining, Certainty Factor, AndroidAbstract: Tuberculosis (TB) is classified as a contagious disease and remains a significant challenge in the health sector in Indonesia to this day. Early diagnosis is crucial to prevent its spread and accelerate treatment. This study aims to develop an Android-based expert system that allows users to diagnose TB independently. The application was developed using Flutter, a cross-platform UI framework developed by Google, and the Dart programming language to support Android application development. The system employs the Forward Chaining method to trace symptoms input by users and the Certainty Factor method to calculate the confidence level of the diagnosis based on the experienced symptoms. Testing was conducted on 25 respondents by comparing the system’s results with diagnoses made by medical professionals. The accuracy rate obtained from testing using the Confusion Matrix method reached 84%, with a user-friendly interface designed to provide initial indications of TB and recommended follow-up actions, encouraging users to seek medical examinations promptly..Keywords: Expert System, Tuberculosis, Forward Chaining, Certainty Factor, Android 
Co-Authors Argin Fiorenza Detin Sofia Melyana R Pugu Nyi Dewi Puspitasari Ujang Sutisna