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All Journal Jurnal Ilmu Komputer dan Informasi JAM : Jurnal Aplikasi Manajemen JOIV : International Journal on Informatics Visualization Journal of Informatics and Advanced Computing JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Dyah Sulistyowati Rahayu
University Of Pancasila
Computer Science & IT Decision Sciences, Operations Research & Management

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 1 
AN EVALUATION OF VALIDATION CRITERIA ON INTELLIGENT SYSTEM VALIDATION PROCESS Dyah Sulistyowati Rahayu; Siti Rochimah
Jurnal Ilmu Komputer dan Informasi Vol 6, No 1 (2013): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (844.457 KB) | DOI: 10.21609/jiki.v6i1.213

Abstract

In the software development cycle, validation is the important stage which is held in final stage especially in intelligent system. Validation obtains the validity, credibility and trustworthy of the system. It is needed to ensure that the intelligent system has same manner as human experts’. Whilst with the importance of validation stage, determining the validation criteria is also important. This paper presents the evaluation of validation criteria which is commonly used in intelligent system validation process. The evaluation is carried out by reviewing the literature of intelligent system validation process. The result shows that the validation criteria have its own characteristic so it requires for understanding the validation criteria characteristics, purposes of validation and also the intelligent system itself to hold validation process.
Sistem Pakar Terapi Herbal Menggunakan Metode Certainty Factor Putri Nurwahyuni; Dyah Sulistyowati Rahayu
Journal of Informatics and Advanced Computing (JIAC) Vol 1 No 1 (2020): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Teknik Informatika Universitas Pancasila

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Abstract

Indonesia memiliki potensi tanaman herbal yang beragam. Potensi yang sangat melimpah tersebut belum dimanfaatkan secara maksimal salah satunya disebabkan oleh kurangnya pakar di bidang tanaman herbal tersebut. Masyarakat umumpun sulit memperoleh informasi yang kredibel tentang manfaat penggunaan tanaman herbal tertentu. Pada penelitan ini telah dibuat Sistem Pakar Terapi Herbal Menggunakan Metode Certainty Factor. Metode ini menentukan saran terapi dengan cara mendiagnosa gejala-gejala yang dirasakan berdasarkan rule dan nilai kepercayaan. Sistem dengan metode certainty factor memberikan output hasil diagnosa gejala yang dirasakan oleh pengguna dengan memberikan saran terapi berupa obat herbal beserta cara penggunannya. Tingkat akurasi yang mencapai 90% pada sistem ini dapat dilihat dari jumlah skenario pengujian akurasinya. Namun, jika dilihat dari jumlah herbal pada saran terapi sistem output, akurasinya adalah 97%. Hal tersebut menandakan bahwa sistem pakar terapi herbal dengan menggunakan metode certainty factor ini memiliki tingkat keakuratan yang baik.
Sistem Informasi Akuntansi untuk Usaha Mikro, Kecil, dan Menengah (UMKM) Bidang Jasa di Indonesia Dyah Sulistyowati Rahayu
Jurnal Teknik Informatika dan Sistem Informasi Vol 3 No 3 (2017): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v3i3.691

Abstract

Micro, small, and medium enterprises (MSMEs) is a form of business which is stipulated in Law No.20 of 2008 where the amount is very dominant in Indonesia. One of the obstacles in developing MSMEs is the limited access to funds. One of which is caused by the absence of financial statements based on the Accounting Standards for Entities Without Public Accountability (SAK-ETAP). MSMEs also experienced a shortage of human resources, especially in technology and accounting. To overcome this and to lead a good corporate governance, we need an accounting information system for MSMEs. This research resulted the accounting information system for MSMEs based on SAK-ETAP and has a general nature so that it can be applied to business in service sector with minor adjustments. This research resulted the complete information system as well as the UML design. The study also attached the complete mapping of each type of transactions to the financial statements. By using this information system, the MSME’s especially in service sector could generate the financial statement, order, invoice, and other report automatically
Sistem Pakar Terapi Herbal Menggunakan Metode Certainty Factor Putri Nurwahyuni; Dyah Sulistyowati Rahayu
Journal of Informatics and Advanced Computing (JIAC) Vol 1 No 1 (2020): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v1i1.1399

Abstract

Indonesia memiliki potensi tanaman herbal yang beragam. Potensi yang sangat melimpah tersebut belum dimanfaatkan secara maksimal salah satunya disebabkan oleh kurangnya pakar di bidang tanaman herbal tersebut. Masyarakat umumpun sulit memperoleh informasi yang kredibel tentang manfaat penggunaan tanaman herbal tertentu. Pada penelitan ini telah dibuat Sistem Pakar Terapi Herbal Menggunakan Metode Certainty Factor. Metode ini menentukan saran terapi dengan cara mendiagnosa gejala-gejala yang dirasakan berdasarkan rule dan nilai kepercayaan. Sistem dengan metode certainty factor memberikan output hasil diagnosa gejala yang dirasakan oleh pengguna dengan memberikan saran terapi berupa obat herbal beserta cara penggunannya. Tingkat akurasi yang mencapai 90% pada sistem ini dapat dilihat dari jumlah skenario pengujian akurasinya. Namun, jika dilihat dari jumlah herbal pada saran terapi sistem output, akurasinya adalah 97%. Hal tersebut menandakan bahwa sistem pakar terapi herbal dengan menggunakan metode certainty factor ini memiliki tingkat keakuratan yang baik.
GENDER STEREOTYPES IN INDONESIAN PUBLIC COMPANIES’ PERFORMANCE Rahayu, Sri Mangesti; Ramadhanti, Wita; Rahayu, Dyah Sulistyowati; Osada, Hiroshi; Indrayanto, Adi
Jurnal Aplikasi Manajemen Vol. 17 No. 1 (2019)
Publisher : Universitas Brawijaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jam.2019.017.01.01

Abstract

Gender equality is one important item from the United Nation’s Sustainable Development Goals (SDGs). It makes a gender gap in companies’ top management becomes valuable to be studied because people still have a stereotype that leadership is a masculine job. This research will test the effect of performance, payment, bankruptcy risk, and earnings management. Data is taken from Indonesian public companies in 2016 using means different statistical test. The result shows that 30.9% or minority corporation have a female director. Hence, while women were given the opportunity to lead, the companies will have better performance and compensation than their male only board of director counterparts. It is proof that gender stereotypes happen in Indonesian Public Companies Leadership.
Assessing Data Imbalance in Financial Distress Prediction: A Comparative Approach of Machine Learning and Economic Models Rahayu, Dyah Sulistyowati; Suhartanto, Heru; Husodo, Zaäfri Ananto
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3397

Abstract

This study aims to compare the effectiveness of machine learning models and economic models in predicting corporate bankruptcy, with a focus on addressing the issue of data imbalance. In this context, the number of companies experiencing financial difficulties is significantly smaller than that of healthy companies, which can lead to bias in predictions. The method used is an experiment with various data handling techniques and involves several classification models, namely Decision Tree, Neural Network (NN), K-Nearest Neighbors (KNN), Case-Based Reasoning (CBR), Support Vector Machine (SVM), and Merton Structural Model, which are tested on several data scenarios with resampling techniques, including Random Oversampling (ROS), Random Undersampling (RUS), and a combination of both. The evaluation results show that the Decision Tree, excluding ROA variables, and the Neural Network provide the best performance, with the Decision Tree achieving 86% accuracy and an AUC of 77.75, and the Neural Network achieving 86.76% accuracy and an AUC of 90.5. Other models, such as KNN and SVM, exhibit lower performance, achieving around 80% accuracy and a lower AUC. Based on these results, Decision Tree without ROA and Neural Networks are the best choices for predicting corporate bankruptcy. This study also demonstrates that financial models, such as the Merton Structural Model, are not significantly affected by data imbalance. The ultimate goal of this study is to provide recommendations for more reliable prediction models that enable financial institutions, investors, and companies to make more informed strategic decisions, as well as reduce financial risks through the early detection of companies at risk of failure.
Co-Authors Adi Indrayanto Amongsaufa, Azka Zulham Heru Suhartanto Hiroshi Osada Husodo, Zaafri Ananto Koloay, Bheli Isya Kurniawan Putri Nurwahyuni Siti Rochimah Sri Mangesti Rahayu Suryapratama, Arie Wita Ramadhanti