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All Journal AMMA : Jurnal Pengabdian Masyarakat Jurnal Kecerdasan Buatan dan Teknologi Informasi
Nining Rahaningsih
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Humanities Chemistry Computer Science & IT Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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PKM Pengembangan Sistem Informasi Akuntansi Untuk Usaha Kecil Dan Menengah (UKM) Nining Rahaningsih; Fathurrohman; Mulyawan; Maria Dewanty Rafu; Hari Sutrisno
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 05 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Small and Medium Enterprises (SMEs) play a crucial role in the national economy, yet they often face challenges in efficiently managing accounting processes. The mismatch between human resource capacity and the needs of modern accounting systems is a significant issue hindering SME performance. Therefore, the development of an easy-to-use accounting information system tailored to the needs of SMEs is essential. This study aims to design and implement a digital-based accounting information system that can improve financial management efficiency in SMEs. The methods used include needs analysis, system design using the Agile methodology, and trials in several SMEs within specific regions. The results indicate that the developed system enhances the accuracy of financial record-keeping and simplifies the reporting process. Thus, this system is expected to be an effective solution for increasing the competitiveness of SMEs in the digital era.
PKM Pelatihan Aplikasi Zahir Accounting Laporan Keuangan Nining Rahaningsih; Gifthera Dwilestari; Rudi Kurniawan; Ahmad Rizki Fauzi; Fazri Muzaki
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 5 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Accurate and timely financial reporting is key to the success of business operations, especially for Small and Medium Enterprises (SMEs). However, many SMEs still face difficulties in preparing financial reports that comply with applicable accounting standards. Limited understanding of accounting and the use of technology are the main barriers. To address this issue, this program aims to provide training on the use of Zahir Accounting software as a solution for preparing financial reports. The methods used include intensive training, case studies, and direct simulations of using the Zahir Accounting application. The results of this program are expected to enhance participants' abilities to prepare accurate and standardized financial reports, thereby supporting better decision-making in their businesses. Additionally, this program is expected to improve the efficiency and effectiveness of financial management within SMEs.
PKM Pelatihan Pemasaran Dan Akuntansi Sederhana Bagi Pelaku UMKM Kecamatan Tarikolot Nining Rahaningsih; Ade Rizki Rinaldi; Bani Nurhakim; Ahmad Rizki Fauzi; Kautsar Zidan Soleh
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 5 : Juni (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The Tarikolot Subdistrict holds significant economic potential through micro, small, and medium enterprises (MSMEs). However, many MSME operators face challenges in managing simple marketing and accounting, which hinders their business growth. This issue arises from a lack of knowledge and skills in these areas. This Community Service Program (PKM) aims to enhance MSME operators' abilities to independently manage their marketing and accounting tasks. The methods employed include face-to-face training, group discussions, and intensive mentoring over a three-month period. The outcomes of this program are expected to improve participants' understanding of effective marketing strategies and the application of simple accounting in their business operations. The training will also enable participants to implement the acquired knowledge in their daily practices to boost efficiency and profitability.
DATA-DRIVEN CONSUMER SEGMENTATION APPROACH FOR JEANS RETAIL SALES USING FUZZY C-MEANS CLUSTERING Nana Suarna; Nining Rahaningsih; Annisa Annastia Suarna
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.479

Abstract

The fashion retail industry generates large volumes of sales transaction data containing valuable information regarding consumer purchasing behavior and preferences. However, extracting meaningful insights from heterogeneous retail data remains challenging when using conventional analytical approaches. This study aims to analyze jeans sales transaction data and identify consumer purchasing patterns using the Fuzzy C-Means (FCM) clustering algorithm. The proposed approach adopts the Knowledge Discovery in Databases (KDD) framework, consisting of data selection, preprocessing, transformation, data mining, and evaluation stages to ensure systematic analysis. The dataset used in this study consists of 799 jeans sales transaction records collected in 2024 from Shakila Collection, involving four attributes: product name, payment method, price, and purchase quantity. To improve clustering effectiveness, only price and purchase quantity were selected as the primary variables due to their relevance in representing consumer purchasing behavior. Clustering performance was evaluated using the Davies-Bouldin Index (DBI) to determine the optimal number of clusters. Experimental results show that the best clustering configuration was achieved at , producing three consumer segments consisting of 175 items in Cluster 0, 590 items in Cluster 1, and 34 items in Cluster 2. The findings indicate that medium-priced products tend to have higher purchasing intensity and more flexible purchase quantities, whereas premium-priced products exhibit relatively lower demand. The novelty of this study lies in integrating Fuzzy C-Means clustering with consumer preference analysis to generate practical business insights for pricing strategies, inventory optimization, and targeted marketing, thereby supporting more effective data-driven decision-making in fashion retail businesses.
Co-Authors Ade Rizki Rinaldi Ahmad Rizki Fauzi Annisa Annastia Suarna Bani Nurhakim Fathurrohman Fazri Muzaki Gifthera Dwilestari Hari Sutrisno Kautsar Zidan Soleh Maria Dewanty Rafu Mulyawan Nana Suarna Rudi Kurniawan