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Analysis of Financial Annual Reports for Bankruptcy Predictions Using Altman Z-Score Method Kasman Wicaksono; Purnawarman Musa; Apriana Anggraeini Bangun; Octarina Budi Lestari; Witari Aryunani; Sigit Sukmono
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v5i2.79

Abstract

The study focused on comparisons to investigate a company's financial health situation in diagnosing early bankruptcy of tobacco-producing companies using the Altman Z-Score formula. The bankruptcy risk predictions were analyzed from 2013 to 2018 on the Indonesia Stock Exchange website. The investigative data obtained at the www.idx.co.id website address used annual financial statement data from three tobacco companies in Indonesia for six consecutive years. Research illustrates that from 2013 to 2018, tobacco-producing companies are in the healthy and low-risk category. The total variable is the key to changing its health condition if it changes its value. Therefore, the results of this study can analyze the company, especially financial statements, for information on fulfilling its obligations to investors and creditors and managing assets to increase sales in generate profits.
Pembelajaran Mendalam Pengklasifikasi Ekspresi Wajah Manusia dengan Model Arsitektur Xception pada Metode Convolutional Neural Network Purnawarman Musa; Wahid Khairul Anam; Saiful Bahri Musa; Witari Aryunani; Remi Senjaya; Puji Sularsih
Rekayasa Vol 16, No 1: April 2023
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v16i1.16974

Abstract

Deep learning is a neural network that creates innovations that give computer-implanted problem-solving expertise. One of the principles of computer vision is a detection system with a vision framework that can identify things encountered in the same manner as a human vision system. Using an artificial intelligence-based Convolutional Neural Network (CNN) model with deep learning techniques, we present a face emotion identification system. The categorization of facial expressions will be utilized as the basis for a face recognition system trained using CNN. The applications are intended to use the OpenCV, Keras, and TensorFlow libraries as the backend. We were discussing the study on the best use of xception architectural models in facial expression recognition systems. Based on the results of these tests, the study obtained an increased accuracy value in training and data testing on an xception architecture model trained for facial expressions using the FER-2013 dataset, resulting in an accuracy value of 66% as well as the value of each average for precision (76%), recall (65%), and F1 score (63%).
Pembuatan Company Profile Berbasis Website sebagai Media Informasi dan Promosi pada Hari Hari Pasar Swalayan Oktaviani Oktaviani; Endah Kurniasari; Rosdiana Rosdiana; Witari Aryunani; Yeni Setiani
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (258.001 KB) | DOI: 10.36418/syntax-literate.v7i8.9191

Abstract

Semakin hari kebutuhan informasi semakin meningkat, banyak pelanggan yang membutuhkan informasi pada Hari Hari Pasar Swalayan namun tidak ada media online untuk menemukan informasi tersebut sehingga menjadi permasalahan yang menyebabkan pelanggan harus datang langsung ke tempatnya untuk mendapatkan informasi atau mengetahui promosi yang ditawarkan. Seiring berkembangnya teknologi, banyak lembaga atau perusahaan mulai menerapkan suatu teknologi yang dapat membantu suatu pekerjaan menjadi lebih efisien. Oleh karena itu, dibuatlah Company Profile Berbasis Website Sebagai Media Informasi dan Promosi Pada Hari Hari Pasar Swalayan. Pembuatan website ini menggunakan PHP dan MySQL dan perancangan UML (United Modelling Language) meliputi Use Case Diagram, Activity Diagram, dan Class Diagram. Website ini terdapat informasi tentang promo, informasi kontak dan juga lokasi dari Hari Hari Pasar Swalayan melalui fitur yang tersedia di navigasi web. Berdasarkan uji coba maka diperoleh hasil bahwa dengan menggunakan web browser Google Chrome, website beserta fiturnya dapat berjalan dengan baik sesuai fungsinya tanpa kendala.
Penerapan Metode Weighted Aggregated Sum Product Assessment (WASPAS) dalam Pemilihan Kasir Swalayan Terbaik Yeni Setiani; Witari Aryunani
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 2 (2023): RESOLUSI November 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i1.1431

Abstract

In a supermarket, cashier guards or cashier security have an important role in maintaining the security and comfort of the cashier area. As a retail company, the company gives awards every month to the cashier division as a motivation for them. However, problems arise in performance appraisal because it is too subjective and can be influenced by personal opinion. Therefore, the authors conducted research to create a decision support system (DSS) that can assist in selecting the best cashier with the criteria of appearance, service, discipline, honesty, and responsibility. The method used in this research is Weighted Aggregated Sum Product Assessment (WASPAS), which can solve complex problems effectively by speeding up the decision-making process. With the WASPAS method, problems are grouped based on criteria and weight so that the value of each criterion can be calculated. The results showed that Rozi (A4) was the best alternative with a value of 0.452 and deserved to be the best cashier at a supermarket.