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All Journal Jurnal Pendidikan Ekonomi (JURKAMI) Balance : Media Informasi Akuntansi dan Keuangan
Mahar, Alicia Christina
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Economics, Econometrics & Finance Education Social Sciences

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Prediksi Harga Saham PT. Unilever Indonesia TBK Dengan Metode Regresi Linier Sederhana Wilda, Robiatul Witari; Sukmarini, Mita Akbar; Mahar, Alicia Christina
Balance: Media Informasi Akuntansi dan Keuangan Vol. 16 No. 2 (2024): Jurnal BALANCE: Media Informasi Akuntansi dan Keuangan
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52300/blnc.v16i2.14249

Abstract

The world of investment is a dynamic market characterized by its fluctuations, including changes in stock values. This research is motivated by the need to predict stock prices with high accuracy to support more precise investment decision-making. PT. Unilever Indonesia Tbk is one of the leading companies in Indonesia, and thus, forecasting its stock prices holds strategic value for investors. However, predicting stock prices is a complex task influenced by various economic and company-specific factors. This study aims to analyze the effectiveness of the simple linear regression method in forecasting the stock prices of PT. Unilever Indonesia Tbk. The results show that this method can produce accurate predictions, with a forecasted value of Rp 2,707 and a Mean Absolute Percentage Error (MAPE) of 2.65%. The application of this method has significant contributions in the investment world, where accurate stock price predictions can assist investors in determining the optimal timing for investment transactions.
KINERJA UMKM DI KOTA PALANGKA RAYA: TINJAUAN KEUANGAN, PENJUALAN, DAN STRATEGI PEMASARAN Giovanni, Jonathan; Subianto, Pratiwi; Mahar, Alicia Christina; Apriananda, Fricella
Jurnal Pendidikan Ekonomi (JURKAMI) Vol 10, No 2 (2025): JURKAMI
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jpe.v10i2.4092

Abstract

Micro, Small, and Medium Enterprises (MSMEs) in Palangka Raya City face significant challenges in enhancing competitiveness and operational efficiency, despite the continuous growth in the number of business units. One of the main issues lies in the lack of data-driven development strategies and the limited integration of information among MSME actors. This study applies a descriptive quantitative approach using the K-Means Clustering method to classify 100 MSME units based on three key aspects: financial performance, product sales, and marketing strategies. Data were collected via online questionnaires from August to October 2024. The analysis was conducted using the KNIME software to visualize and manage data effectively. The findings reveal homogeneous MSME clusters, with groups demonstrating high financial efficiency and a combination of online and offline marketing strategies showing the best performance. This study recommends that local governments develop more targeted and evidence-based strategies for MSME development. The main limitation of this research is the sample's scope, which may not fully represent the diversity of MSMEs in Palangka Raya. Future studies are encouraged to expand the geographical coverage and apply mixed-method approaches.
Co-Authors Apriananda, Fricella Jonathan Giovanni Subianto, Pratiwi Sukmarini, Mita Akbar Wilda, Robiatul Witari