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All Journal Bulletin of Community Engagement Ebisnis Manajemen
Naufalia Alfi Fuadah
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Religion Arts Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences Other

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Pengelompokkan Kabupaten/Kota di Provinsi Jawa Timur berdasarkan Indikator Ketenagakerjaan Naufalia Alfi Fuadah; Zahra Afifah Nafisah; Sri Pingit Wulandari
Ebisnis Manajemen Vol. 2 No. 4 (2024): December : Ebisnis Manajemen
Publisher : Fakultas Ekonomi & Bisnis, Universitas Nusa Nipa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59603/ebisman.v2i4.589

Abstract

Labor is one of the drivers of the regional economy because it can increase productivity and community welfare. Employment indicators are often used to assess the condition and dynamics of the labor market in a region, one of which is in East Java Province. To measure the condition and dynamics of the workforce in East Java Province, a grouping of districts/cities in East Java Province was carried out using the cluster analysis method. This method is used to group objects or data into groups that have similar characteristics in the observed data. This method is used by analyzing data starting from data collection, testing cluster analysis assumptions, determining methods and conducting hierarchical and non-hierarchical cluster analysis, interpreting the results of the analysis and drawing conclusions and suggestions. So the analysis that can be obtained from this study is the best hierarchical cluster method for classifying districts/cities in East Java Province is the complete linkage method with an optimum number of clusters of 4 clusters while for the non-hierarchical cluster method with the K-Means method with the best clusters of 4 clusters while for the non-hierarchical cluster method with the K-Means method with the best clusters of 3 clusters.
Analisis Fundamental dan Teknikal terhadap Faktor-Faktor yang Memengaruhi Harga Saham Emiten dalam Indeks IDX-MES BUMN 17 Tahun 2023 Sindy Ayu Porwitasari; Muhammad Fairuz Ahnaf; Arum Antika; Farhan Muhammad Rizki; Mochammad Bimo Aitya Fahreza; Naufalia Alfi Fuadah; Serly Diah Puspitasari
Bulletin of Community Engagement Vol. 4 No. 3 (2024): Bulletin of Community Engagement
Publisher : CV. Creative Tugu Pena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51278/bce.v4i3.1618

Abstract

Global economic developments and regional market dynamics significantly affect the performance of State-Owned Enterprises (BUMN). As an index that operates in the natural resources and energy sector, IDX-MES BUMN 17 is vulnerable to changes in global commodity prices. To address this challenge, two main approaches are used, namely fundamental analysis and technical analysis. In this study, the method used is Moving Average (MA) with lag MA(2) and MA(3), which was chosen to capture short-term price movement patterns. In addition, the simple exponential smoothing (SES) method with parameters 0.2 and 0.7 is also used to provide forecasts that are more responsive to changes in the latest data. Trend models such as linear, quadratic, exponential, and S-curve trends are applied to identify long-term trends of the macro and sectoral variables being analyzed. Seasonal forecasting methods such as Double Exponential Smoothing (DES) and the Winter method are used to model seasonal fluctuations that occur consistently. The results of the analysis conducted are IDX-MES BUMN 17 is divided into 2 clusters, cluster 1 selected ANTM and ELSA issuers, then in class 2 selected PTBA issuer. Of the three selected issuers, the highest return value is in the ANTM issuer, so the ANTM issuer is analyzed further. The best forecasting method for the three stocks is Double Exponential Smoothing. The results of the ANTM stock analysis show that the ANTM stock data is stationary, the ANTM stock also has cointegration in the short-term model to the long-term model and the three short-term models have met the IIDN assumptions
Co-Authors Arum Antika Mochammad Bimo Aitya Fahreza Muhammad Fairuz Ahnaf Rizki, Muhammad Farhan Serly Diah Puspitasari Sindy Ayu Porwitasari Sri Pingit Wulandari Zahra Afifah Nafisah