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All Journal EKSAKTA: Journal of Sciences and Data Analysis Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika
Pramesti Melyna Mustofa
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Religion Agriculture, Biological Sciences & Forestry Arts Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Education Materials Science & Nanotechnology Mathematics Social Sciences

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Analisis Harga Saham dengan Berdasarkan Rentang Waktu Sebagai Dasar dalam Penentuan Metode Peramalan yang Optimal Muhammad, Hubbi; Pramesti Melyna Mustofa
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 2, October 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss2.art1

Abstract

The modeling of stock prices for telecommunications companies in Indonesia (TBIG.JK, TLKM.JK, XL.JK, ISAT.JK, TOWR.JK) is examined in this study by considering three time periods: 1 year, 5 years, and 10 years. The analysis results indicate that the distribution of stock prices for each company and time period varies, with some stocks exhibiting a distribution close to normal while others show high kurtosis. These findings suggest that the assumption of normal distribution may not be appropriate for all cases, making it essential to select a stock price prediction model that takes into account the specific distribution characteristics for each company and time period
Marketing Counseling for Handicraft Business from Plastic Waste through TikTok Digital Platform for Community Empowerment of Nusantara Tourism Village (Puspamukti Village) Nurherawati; Pramesti Melyna Mustofa; Ardiansyah; Alfin Nur Arifah; Della Apriani
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 8 No. 1 (2025): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35568/abdimas.v8i1.5681

Abstract

Puspamukti Village is a Tourism Village that has various potentials in various fields, both agriculture and plantations. Puspamukti villagers are housewives who have free time besides farming and gardening. This counseling aims to empower the Puspamukti Village community through the development of a handicraft business from unused plastic waste that has been converted into goods that have selling power by making Profitable Trash, namely ceramics from garbage that has aesthetic value and marketable functions by utilizing the TikTok digital platform. The method used is a method with counseling activities including product manufacturing training, digital marketing techniques, and branding strategies. The results showed an increase in community knowledge and skills in managing plastic waste into value-added products, as well as an increase in community interest in marketing their products through TikTok. In addition, this counseling also succeeded in building a network between handicraft business actors in Puspamukti Village with a wider potential buyer. It can be concluded that the activities for community empowerment in Puspamukti Village have achieved a number of successes, including: 1) Increased awareness and skills: Puspamukti villagers have a better understanding of plastic waste management and are able to produce value-added handicraft products; 2) Behavior change: There have been positive behavioral changes in the community, namely an increased interest in processing plastic waste into useful products; 3) Economic development: The plastic waste handicraft business has the potential to increase community income and contribute to the village economy; 4) Effectiveness of TikTok utilization: The TikTok platform has proven effective as a promotional and marketing medium for handicraft products.
A Perbandingan Algoritma Support Vector Machine dan Random Forest dalam Klasifikasi Kelayakan Pemberian Pinjaman pada BPR Nusumma Jawa Barat Salsa Sabila, Tami; Fithri Sri Mulyani; Pramesti Melyna Mustofa
Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Vol. 9 No. 1 (2026): Volume 9 Nomor 1 Tahun 2026
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/proximal.v9i1.7977

Abstract

Pesatnya peningkatan pengajuan kredit pada lembaga keuangan menuntut adanya sistem evaluasi kelayakan pinjaman yang mampu bekerja secara cepat, akurat, dan objektif guna meminimalkan risiko kredit bermasalah. Oleh karena itu, penelitian ini bertujuan untuk membandingkan kinerja dua algoritma machine learning, yaitu Support Vector Machine (SVM) dan Random Forest (RF), dalam mengklasifikasikan kelayakan pemberian pinjaman pada BPR Nusumma Jawa Barat. Penelitian ini menggunakan data primer sebanyak 753 observasi dengan enam variabel prediktor dan satu variabel target berupa status pinjaman. Metode penelitian yang digunakan adalah eksperimen kuantitatif melalui beberapa tahapan, meliputi pembersihan data, penyeimbangan kelas menggunakan metode ROSE, transformasi data, pembangunan model SVM dan Random Forest, serta evaluasi kinerja model menggunakan confusion matrix, accuracy, precision, recall, F1-score, dan Area Under Curve (AUC). Hasil penelitian menunjukkan bahwa algoritma SVM menghasilkan nilai AUC sebesar 0,9748, sedangkan algoritma Random Forest memperoleh nilai AUC sebesar 0,9953. Berdasarkan hasil tersebut, Random Forest menunjukkan performa klasifikasi yang lebih unggul dibandingkan SVM. Temuan ini mengindikasikan bahwa Random Forest berpotensi menjadi algoritma yang lebih optimal untuk diterapkan sebagai sistem pendukung keputusan dalam evaluasi kelayakan kredit, sehingga dapat membantu lembaga keuangan dalam meningkatkan efektivitas dan kualitas pengambilan keputusan kredit.
Co-Authors Alfin Nur Arifah Alfin Ardiansyah Della Apriani Fithri Sri Mulyani Muhammad, Hubbi Nurherawati Salsa Sabila, Tami