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All Journal AJAD : Jurnal Pengabdian kepada Masyarakat Kohesi: Jurnal Sains dan Teknologi Neraca Manajemen, Akuntansi, dan Ekonomi Khidmatuna: Jurnal Pengabdian Masyarakat
Putri, Ferdiana
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Sosialisasi dan Pendampingan UMKM melalui Pembukuan Keuangan secara Digital menggunakan Aplikasi Teman Bisnis Fitri, Lailatul Hidayah; Pramudya, Nanda Hari; Fatihah, Nazilatul; Pramudita, Dwi Anggi; Izzulhaq, Mohammad; Putri, Ferdiana; Priyanto, Moh. Wahyudi
AJAD : Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/ajad.v4i1.299

Abstract

Financial bookkeeping plays an important role in the management of micro, small and medium enterprises (MSMEs). Many MSMEs in West Klompang Village are not yet fully aware of the benefits and procedures for proper financial bookkeeping. Therefore, this community service aims to provide socialization and assistance with digital financial bookkeeping. The method involves observation, planning, implementation, and evaluation, with activities including interviews, outreach about the importance of bookkeeping, and introduction to the Business Friends application. As a result, there were 10 people who took part in this activity and showed high interest among MSME players in digital bookkeeping, with the Teman Bisnis application recognized as a practical tool for recording and analyzing financial transactions. The duration of this activity is 120 minutes with the hope that this service can improve the performance and welfare of MSMEs in West Klompang Village through regular and transparent financial bookkeeping.
IMPLEMENTASI MACD DALAM MEMPREDIKSI HARGA SAHAM MENGGUNAKAN MACHINE LEARNING Putri, Ferdiana; Ahmadi, Mirzam Arqy
Musytari : Jurnal Manajemen, Akuntansi, dan Ekonomi Vol. 13 No. 7 (2025): Musytari : Jurnal Manajemen, Akuntansi, dan Ekonomi
Publisher : Cahaya Ilmu Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.8734/musytari.v13i7.9779

Abstract

The difficult to predict fluctuations in stock prices demand precise analytical methods for investors to minimize risks. This study aims to evaluate the effectiveness of the MACD technical indicator and the SVR algorithm in forecasting stock prices. Monthly historical data of Adaro Energy Indonesia's stock prices (ADRO.JK) from January 2021 to December 2022 was used as the research sample. This method employs MACD to identify trends and SVR as a Machine Learning model. The results show that MACD is more accurate than SVR in predicting price trends, with MAPE values of 4,39% and 9,81%, respectively. The evaluation indicates that combining MACD with hybrid models can improve prediction accuracy, particularly in dynamic market conditions. However, this study is limited by the data scope, which only covers a single stock and a specific time range, thus limiting the generalizability of the results to the broader stock market. Fluktuasi harga saham yang sulit diprediksi menuntut metode analisis yang tepat bagi investor untuk meminimalkan risiko. Penelitian ini bertujuan untuk menguji efektivitas indikator teknikal MACD dan SVR dalam memprediksi harga saham. Data historis harga saham bulanan Adaro Energy Indonesia (ADRO.JK) dari Januari 2021 hingga Desember 2022 digunakan sebagai sampel penelitian. Metode ini memanfaatkan MACD untuk identifikasi tren dan SVR sebagai model Machine Learning. Hasil penelitian menunjukkan bahwa MACD lebih akurat dibandingkan SVR dalam memprediksi tren harga, dengan nilai MAPE masing-masing sebesar 4,39% dan 9,81%. Evaluasi mengindikasikan bahwa kombinasi MACD dan model hybrid dapat meningkatkan akurasi prediksi, terutama pada kondisi pasar yang dinamis. Penelitian ini memiliki keterbatasan pada ruang lingkup data yang hanya mencakup satu saham dan rentang waktu terbatas, sehingga hasilnya tidak dapat digeneralisasi untuk seluruh pasar saham.
PERBANDINGAN PERFORMA RANDOM FOREST DAN GRADIENT BOOSTING DALAM PREDIKSI PADA DATASET CUSTOMER SHOPPING TRENDS Putri, Ferdiana; Arianto, Dede Brahma
Kohesi: Jurnal Sains dan Teknologi Vol. 5 No. 11 (2024): Kohesi: Jurnal Sains dan Teknologi
Publisher : CV SWA Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3785/kohesi.v5i11.9030

Abstract

This study compares the performance of two machine learning algorithms, Random Forest and Gradient Boosting, in predicting product categories using the Customer Shopping Trends dataset. The dataset exhibits an imbalanced class distribution, prompting the use of oversampling techniques to improve the representation of minority classes. The analysis process involves data exploration, preprocessing, and model evaluation based on metrics such as accuracy, precision, recall, and F1-score. The results indicate that Random Forest provides more consistent and superior performance compared to Gradient Boosting, particularly in handling minority classes. The Random Forest model achieved higher accuracy and more balanced evaluation metrics across all classes. This study offers insights into the effectiveness of ensemble algorithms in addressing data imbalance and their relevance for practical applications in industries such as e-commerce and customer data analysis. Penelitian ini membandingkan performa dua algoritma pembelajaran mesin, yaitu Random Forest dan Gradient Boosting, dalam memprediksi kategori produk pada dataset Customer Shopping Trends. Dataset ini memiliki distribusi kelas yang tidak merata, sehingga teknik oversampling digunakan untuk meningkatkan representasi kelas minoritas. Proses analisis melibatkan eksplorasi data, pra-pemrosesan, dan evaluasi model berdasarkan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa Random Forest memberikan performa yang lebih konsisten dan unggul dibandingkan Gradient Boosting, terutama dalam menangani kelas minoritas. Model Random Forest berhasil mencapai akurasi yang lebih tinggi dan nilai metrik evaluasi yang lebih seimbang pada seluruh kelas. Penelitian ini memberikan wawasan tentang efektivitas algoritma ensemble dalam menghadapi ketidakseimbangan data, serta relevansinya untuk aplikasi praktis di industri, seperti e-commerce dan analisis data pelanggan.
DIGITALIZATION AND BRANDING OF WEST KLOMPANG VILLAGE, PAKONG DISTRICT, PAMEKASAN REGENCY IN THE DIGITAL ERA: DIGITALISASI DAN BRANDING DESA KLOMPANG BARAT KECAMATAN PAKONG KABUPATEN PAMEKASAN DI ERA DIGITAL Izzulhaq, Mohammad; Fitri, Lailatul Hidayah; Pramudya, Nanda Hari; Fatihah, Nazilatul; Pramudita, Dwi Anggi; Putri, Ferdiana; Priyanto, Moh. Wahyudi
Khidmatuna: Jurnal Pengabdian Masyarakat Vol. 3 No. 1 (2024): Juni
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat STAI Al Fithrah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36781/khidmatuna.v3i01.576

Abstract

The development of a village can be affected by the effective implementation of village digitalization. Village digitalization refers to efforts to develop digital infrastructure across sectors. Village digitalization has the potential to improve the village economy and make it easier to access information about the village. Therefore, we provide services that focus on developing digitalization and branding of West Klompang Village. Service begins on September 4-30 2023 using the observation, planning, implementation and evaluation approach. In this activity, it was seen that the people of West Klompang Village were very enthusiastic and actively participated. They participated with great enthusiasm. Village officials also appear to always be ready to help, provide proper facilities, and provide support to the West Klompang Village MBKM Internship Team. The Head of West Klompang Village was also actively involved in this outreach activity, providing full support. Apart from that, the potential in West Klompang Village looks very promising and worthy of further development. Apart from that, the results of the service include making a Bumdes logo, video documentation of the profile of West Klompang Village, and making labels for MSMEs. Collaboration is needed to increase community involvement in the creation of digitally connected villages. It is necessary to form a creative team to produce quality content, as well as provide training for village staff so they can innovate in the digital era.
Co-Authors Fatihah, Nazilatul Fitri, Lailatul Hidayah Izzulhaq, Mohammad Mirzam Arqy Ahmadi Moh. Wahyudi Priyanto Pramudita, Dwi Anggi Pramudya, Nanda Hari Priyanto, Moh. Wahyudi