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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

Perancangan Sistem Pendukung Keputusan Untuk Pemilihan Lokasi Dalam Perluasan Usaha Kafe menggunakan Analytical Hierarchy Process Wowon Priatna; Suryadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (759.864 KB) | DOI: 10.29207/resti.v3i3.1263

Abstract

vanilla. The Milk Café was founded in 2015 which currently has 3 branches and 5 franchises in various cities in Central Java and D.I. Yogyakarta and many more. the milk café owner has plans to open a new café branch. The milk café owner does not yet have the right method for determining location selection recommendations. Currently, café owners only conduct surveys and then choose locations that they think are appropriate based on several criteria so that café owners are often hesitant in determining the right location. Choosing an improper business location can cause bankruptcy or failure to run a business. This study aims to find out how the AHP method is able to provide problem solving solutions in the selection of locations in the expansion of the café business. And how to build a decision support system application AHP method. The data used are location data to conduct a feasibility survey based on criteria data to locations that have been determined by the team leader, where the criteria for determining new cafes are strategic locations, market share, competitors, rental prices and area size ... results from AHP calculations for expansion of the café is that it can be concluded that the alternative location of Jl. Sultan Syahrir Surakarta was stated as the most suitable location to be chosen as the location of the new branch of The Milk Café with the highest weighting value of 0.235. While the least recommended alternative locations are Jl. Adi Soemarmo with the least total weight is 0.153.
Optimizing Multilayer Perceptron with Cost-Sensitive Learning for Addressing Class Imbalance in Credit Card Fraud Detection Wowon Priatna; Hindriyanto Dwi Purnomo; Ade Iriani; Irwan Sembiring; Theophilus Wellem
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5917

Abstract

The increasing use of credit cards in global financial transactions offers significant convenience for consumers and businesses. However, credit card fraud remains a major challenge due to its potential to cause substantial financial losses. Detecting credit card fraud is a top priority, but the primary challenge lies in class imbalance, where fraudulent transactions are significantly fewer than non-fraudulent ones. This imbalance often leads to machine learning algorithms overlooking fraudulent transactions, resulting in suboptimal performance. This study aims to enhance the performance of Multilayer Perceptron (MLP) in addressing class imbalance by employing cost-sensitive learning strategies. The research utilizes a credit card transaction dataset obtained from Kaggle, with additional validation using an e-commerce transaction dataset to strengthen the robustness of the findings. The dataset undergoes preprocessing with RUS and SMOTE techniques to balance the data before comparing the performance of baseline MLP models to those optimized with cost-sensitive learning. Evaluation metrics such as accuracy, recall, F1 score, and AUC indicate that the optimized MLP model significantly outperforms the baseline, achieving an AUC of 0.99 and a recall of 0.6. The model's superior performance is further validated through statistical tests, including Friedman and T-tests. These results underscore the practical implications of implementing cost-sensitive learning in MLPs, highlighting its potential to significantly enhance fraud detection accuracy and offer substantial benefits to financial institutions.
Co-Authors -, Rasim Ade Iriani Agung Nugroho Agung Nugroho Agus Hidayat Aida Fitriyani, Aida Ajif Yunizar Pratama Yusuf Alexander, Allan D Alhillah, Yumaris Alfi Andi Lawrence Hutahaean, Johanes Andri Fajriya Andry Fadjriya Annisa Oktavianti Hermadi Asep R. Hamdani Asep Ramdhani M Asep Ramdhani Mahbub Atika , Prima Dina Dhea Putri Aprilyana Dwi Budi Srisulistiowati Dwipa Handayani Eka Nur A’ini Endang Retnoningsih Enggar Putera, dkk, Diaz Faisal Adi Saputra Fajar Mukharom Fathurrazi, Ahmad Febry Sandrian Sagala Fefbiansyah Hasibuan Galih Apriansha Pradana Hadi Kusmara Hendarman Lubis Herlawati Herlawati Hindriyanto Dwi Purnomo Ikhsan Romli Ilham Rizky Widianto Intan Safira Irwan Sembiring Ismaniah Ismaniah Joni Warta Joni Warta Joniwarta Joniwarta, Joniwarta Jumi Saroh Hidayat Kapriadi, Engkap Karyaningsih, Dentik Khoirunnisaa, Nabiilah Kustanto , Prio Lubis, Hendarman M. Fadhli Nursal Mayadi Mayadi Meutia, Kardinah Indrianna Mugiarso Mugiarso, Mugiarso Muhammad Khaerudin Noe’man,, Achmad Nurjeli Nurjeli Pradana , Galih Apriansha Prima Dina Atika Purnomo , Rakhmat Purnomo, Rakhmat Putra , Tri Dharma Rahmadya Trias Handayanto Rakhmat Purnomo Rasim Ratna Salkiawati Rejeki , Sri Retnoningsih , Endang Rinaldi Tunnisia Ritzkal, Ritzkal Rofiah , Syahbaniar Sagala, Febry Sandrian Saputra , Faisal Adi Silvi - Siti Setiawati Siti Setiawati Siti Setiawati Siti Setiawati, Andika Yusuf Hidayat Sri Lestari, Tyastuti Sri Rejeki Sudiantini, Dian Sulistiyo, Dwi Suryadi Syahbaniar Rofiah Tb Ai Munandar, Tb Ai Theopillus J. H. Wellem Tri Dharma Putra Tri Dharma Putra Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Widianto, Ilham Rizky Wiyanto Wiyanto