Yusni Amaliah
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Implementasi Moora Pada Penilaian K3 Pemerintah Kota Tarakan Romadan; Rusmin; Yusni Amaliah; Anto, Anto
Journal of Big Data Analytic and Artificial Intelligence Vol 5 No 1 (2019): JBIDAI Juni 2019
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Tarakan City Government, specifically the Organization Division of the Regional Secretariat (Setda), has struggled to maintain clean, organized, and aesthetically pleasing office environments, leading to numerous public complaints. These issues have negatively impacted the government's image and service quality. To address this, a decision support system is needed to help the Regional Secretary identify which government offices meet the standards for being comfortable and welcoming, based on Occupational Health and Safety (OHS) criteria outlined in Perwali No. 14 of 2017. Currently, Setda lacks an integrated information system to assess which offices meet these standards and identify which criteria require improvement. The existing evaluation method, done through Microsoft Excel, is inefficient, making the decision-making process less effective. In response, this study proposes a system that can categorize offices based on OHS standards and highlight criteria for improvement using the MOORA method. The study evaluates 16 government offices as alternatives, with data collected from interviews and the 2017 OHS evaluation sheets, covering eight criteria (seven benefit and one cost criterion) and 24 sub-criteria. The MOORA method is applied to generate final scores that provide rankings, categories, and improvement criteria. The OHS categories are defined as Green (scores between 70 and 90, indicating a high level of OHS), Yellow (scores between 50 and 70, indicating a moderate level of OHS), and Red (scores between 30 and 50, indicating a low level of OHS). The results show that the system is effective, informative, and efficient in displaying the OHS status of the offices. Out of the 16 offices, 11 are classified in the Green category, while 5 fall into the Yellow category. The Green category scores range from 70.78 to 79.63, and the Yellow category scores range from 66.26 to 69.09. The study identifies the need for improvements, particularly in Waste Management and Policies/Innovations by the Heads of Offices. This MOORA-based decision support system enables the government to better evaluate and improve the OHS performance of its offices, contributing to enhanced service quality and government reputation.
Perbandingan Metode Euclidean Probability dan Teorema Bayes untuk Diagnosa Penyakit Gigi Natalia Cangera; Yusni Amaliah; Gusmana, Roman
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.42

Abstract

Dental disease is a disease that interferes with the normal function of the teeth. Dental disease has almost similar symptoms, so it requires an expert system of dental disease diagnosis for the proper treatment before the disease becomes more serious. The research employs Euclidean probability and Bayes' Theorem. Euclidean probability is a case approach for measuring probability based on causes, while Bayes' Theorem is a mathematical formula for determining conditional probability. Both of these methods determine the disease percentage based on the input symptoms. Their differences reflect in the calculation. Research shows that the Bayesian analysis is better than Euclidean probability, as evidenced by the similarity in the systems diagnostic with experts of 80% accuracy, while Euclidean probability is 40%.
Analisa Metode Association Rule Untuk Penjualan Skincare Menggunakan Algoritma Pincer Serach Nadia Indah Tarakanita; Yusni Amaliah; Anto, Anto
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 2 (2023): JBIDAI Desember 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i2.46

Abstract

Rumah Masker Tarakan is a business entity in the field of selling cosmetic and skincare products. A common problem faced by Rumah Masker is the placement of products, which often leads to difficulties in finding similar products. Therefore, a method is needed to organize the layout of skincare products that are frequently purchased together, making it easier for customers to select the products they want. The Pincer Search Algorithm, also known as the Two-Way Search, uses two approaches: Top-Down and Bottom-Up. In its process, the primary direction of the Pincer Search is Bottom-Up. The Maximum Frequent Set is a collection of maximal itemsets that are classified as frequent. The purpose of the Maximum Frequent Set is to reduce (prune) the number of candidate Frequent Itemsets that need to be examined in the Bottom-Up process. Based on research conducted using the Pincer Search Algorithm with sales data from January to June 2022, involving a total of 148 data points, it was found that 72 transactions yielded a value of 0.028% for a candidate of 3 itemsets. This demonstrates that the best sales performance occurs with a combination of 3 itemsets.