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All Journal Journal of Economics, Business, & Accountancy Ventura Husnayain Business Review
M. Yusuf
Sriwijaya State Polytechnic
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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The analysis of labor force participation in rubber smallholding sector in Banyuasin Regency, South Sumatera, Indonesia M. Yusuf; Jamalludin Sulaiman
Journal of Economics, Business, and Accountancy Ventura Vol. 18 No. 1 (2015): April - July 2015
Publisher : Universitas Hayam Wuruk Perbanas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14414/jebav.v18i1.380

Abstract

The fact is that natural rubber has a strategic role as it is one of the commodities industry tropical crops. In addition, it also has important and strategic role in sup-porting the national economy, primarily as a source of livelihood of millions of rub-ber farmers in rural areas. This study analyzed the potential of using family labor in rubber smallholding sector in Banyuasin Regency, South Sumatra Province, Indo-nesia. The total sample used for the study was 280 respondents of households. Data was analyzed using multiple regression analyses. The multiple regression analysis used to identify the determinants of labor force participation decision regarding work in the rubber smallholding in the study area such as rubber production (kg per year per hectare), number of family workers, age of family head, location of dwelling, education of family head, and average years of schooling of family workers. Based on the analysis, only two factors affected significantly family labor force participation outside their smallholdings, namely number of family labor and education of family head.
Analysis of Optimal Stock Returns in the Banking Sector Using Stochastic RSI, MACD, and Bollinger Bands Indicators Ahmad Abrori Zulfa; M. Yusuf; Claudya Nurcahaya
Husnayain Business Review Vol. 6 No. 2 (2026)
Publisher : Asosiasi Dosen Peneliti Ilmu Ekonomi dan Bisnis Indonesia (ADPEBI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/hbr.v6i2.1956

Abstract

Purpose – This study aims to examine the differences in stock returns generated by the Stochastic Relative Strength Index (Stochastic RSI), Moving Average Convergence Divergence (MACD), and Bollinger Bands indicators and to determine the optimal return for banking sector stocks included in the LQ45 Index during the period from March 2023 to February 2026 using the Geometric Mean method. Methodology/Approach – This study employed a descriptive quantitative research design. Secondary data consisting of daily closing prices of five banking sector stocks listed in the LQ45 Index were collected from the Stockbit platform. Buy and sell signals were generated using the Stochastic RSI, MACD, and Bollinger Bands indicators. The resulting stock returns were analyzed using descriptive statistics, normality and homogeneity tests, and the Kruskal–Wallis nonparametric test. The Geometric Mean method was subsequently applied to determine the optimal investment return. Findings – The results revealed a statistically significant difference in stock returns among the three technical indicators (Asymp. Sig. = 0.000; p < 0.05). Based on the Mean Rank values, the Stochastic RSI demonstrated the highest effectiveness in generating stock returns, followed by Bollinger Bands and MACD. The Geometric Mean analysis indicated that the Bollinger Bands–BBTN combination produced the highest optimal return of 7.31%, while BBNI generated the highest return under the Stochastic RSI indicator at 6.34%. Overall, BBTN and BBNI exhibited superior investment performance compared with the other banking stocks included in the analysis. Novelty/Value – This study contributes to the technical analysis literature by simultaneously comparing the performance of three widely used technical indicators and evaluating their optimal returns using the Geometric Mean method. The findings provide empirical evidence that may assist investors in selecting the most appropriate technical indicator based on the characteristics of banking sector stocks, thereby supporting more effective investment decision making.
Co-Authors Ahmad Abrori Zulfa Claudya Nurcahaya Jamalludin Sulaiman