Analisis Teknikal Pergerakan Harga Saham Untuk Mengambil Keputusan Investasi pada Saham Sektor Telekomunikasi yang Terdaftar di Bursa Efek Indonesia: Studi Kasus Saham XL Axiata Tbk (EXCL)

Putri Kemala Dewi(1), Marsanda Hutagalung(2), Vingky Dwi Pratama(3), Zulfa Afifah(4),


(1) Universitas Negeri Medan
(2) Universitas Negeri Medan
(3) Universitas Negeri Medan
(4) Universitas Negeri Medan
Corresponding Author

Abstract


Penelitian ini menganalisis efektivitas analisis teknikal dalam memprediksi pergerakan harga saham XL Axiata Tbk (EXCL) di Bursa Efek Indonesia periode 2019–2023. Melalui pendekatan kuantitatif deskriptif-analitis, studi ini menguji akurasi indikator Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), dan Moving Average (MA) dalam menghasilkan sinyal beli/jual, serta mengidentifikasi pola grafik kritis seperti double bottom dan head and shoulders. Hasil penelitian menunjukkan bahwa kombinasi MACD (12,26,9) dan RSI (14 hari) dengan konfirmasi volume transaksi mencapai tingkat akurasi 68%, mampu mengantisipasi tren bullish maupun bearish, termasuk fluktuasi ekstrem selama pandemi COVID-19 dan pasca-akuisisi PT. Link Net (2023). Volatilitas bulanan saham EXCL tercatat sebesar 18,2%, dengan level support utama di Rp1.950–Rp2.000 dan resistance psikologis di Rp3.000. Temuan ini merekomendasikan strategi investasi hibrid yang mengintegrasikan analisis teknikal dengan evaluasi fundamental, khususnya pada sektor telekomunikasi yang sensitif terhadap perubahan regulasi dan ekspansi korporasi. Penelitian ini berkontribusi pada pengembangan metodologi analisis teknikal di pasar berkembang serta memberikan panduan praktis bagi investor dalam mengoptimalkan risk-reward ratio.


Keywords


Analisis Teknikal, Sektor Telekomunikasi, Saham EXCL, MACD, RSI, Volatilitas Harga

References


Alsubaie, Y., Hindi, K. E., & Alsalman, H. (2019). A cost-sensitive fine-tuned naive Bayesclassifier using a minimal number of technical indicators improves stock market forecasting accuracy, reduces misclassification cost, and enhances investment return compared to other classifiers. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2945907

Ardana, M. R. A., Setiyono, W., & Sriyono, S. (2024). Earnings per share, cash flow from operations, and trading volume impact stock returns in Indonesian banking companies, while price to sales ratio does not. EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis, 12(2). https://doi.org/10.37676/ekombis.v12i2.5505

Ardyanta, E. I., & Sari, H. (2021). Using sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machines in Indonesia, with currency exchange rate and foreign stock price index movement as predictors, increases the average prediction accuracy rate by 11.78%.

Bouasabah, M., & Khalaf, O. I. (2023). Our proposed stochastic model provides a more accurate estimate of short-term market trends, outperforming traditional indicators like Simple Moving Averages and Moving Average Convergence Divergence. Advances in Decision Sciences, 27(3). https://doi.org/10.47654/v27y2023i3p1-13

Hadi, K., & Ratnawati, A. T. (2023). Earnings per share and price earnings ratio significantly positively impact stock prices, while the Composite Stock Price Index and trading volume have insignificant effects. INTERNATIONAL CONFERENCE ON DIGITAL ADVANCE TOURISM, MANAGEMENT AND TECHNOLOGY, 1(1).

https://doi.org/10.56910/ictmt.v1i1.117

Kouatli, I., & Yunis, M. (2021). This paper reviews various technical indicators and suggests a strategy to identify and adopt the right indicator based on data behavior, aiding in stock-trading decision-making. 2021 International Conference on Decision Aid Sciences and Application (DASA). https://doi.org/10.1109/DASA53625.2021.9682337

Kusviana, F., & Yanthi, M. D. (2024). Profitability, liquidity, and solvency all influence stock prices in telecommunications subsector companies listed on the IDX, with the exception of Return On Assets and Return On Equity. JRAK (Jurnal Riset Akuntansi dan Bisnis),

(1). https://doi.org/10.38204/jrak.v10i1.1428

Kurniawan, V. (2010). Telecommunication companies in BEI have good financial performance, with PT. Telekomunikasi Indonesia Tbk showing the best performance from 2004 to 2008.

Lestari, A. W. (2019). Return on investment (ROI) is the most significant factor influencing stock prices in Indonesian telecommunication companies listed on the BEI, with all independent variables having a significant effect on stock prices. JUMANJI (Jurnal Manajemen Jambi), 2(1). https://doi.org/10.35141/JMJ.V2I1.460

Mahajan, Y. (2015). Optimized MACD and RSI indicators are more profitable for investment decisions in the Indian equity market than standard MACD and RSI indicators, defying the Efficient Market Hypotheses. Emerging Markets: Finance eJournal. https://doi.org/10.5958/2249-7323.2015.00140.6

Mandasari, D., Budihardjo, B., Kusumah, A., Yudhawati, D., & Rizkyllah, R. (2023).

Telecommunication companies listed on the BEI show positive financial performance, with PT. Telekomunikasi Indonesia and PT. XL Axiata showing positive net operating profit after tax, while PT. Indosat shows negative net operating profit after tax. Journal

of International Trade, 2(2). https://doi.org/10.32832/jit.v2i2.750

Martia, D., & Yasmine, N. I. (2021). Simple Moving Average and Relative Strength Index indicators accurately determine buy and sell signals for infrastructure sector stocks on the Indonesia Stock Exchange. Journal of Physics: Mathematics and Business, 3(1). https://doi.org/10.37194/JPMB.V3I1.67

Prasetyaningsih, I., & Stefia, C. M. (2022). The acquisition of Pt. Axis Telekom Indonesia by Pt. Xl Axiata significantly decreased the stock market value of PT. XL axiata tbk.

Journal of World Science, 1(5). https://doi.org/10.36418/jws.v1i5.45

Ryketeng, M., Junillah, A. L., Ariqah, N. I., Nuraeni, S., & Putri, A. (2024). The acquisition of PT XL Axiata by PT Link Net significantly impacted PT Link Net's stock price, affecting market sentiment. Jurnal Ilmiah Akuntansi Peradaban, 10(1). https://doi.org/10.24252/jiap.v10i1.47002

Sami, H. M., Ayman, K., Niloy, A. P., & Ashrafi, N. (2022). MACD and RSI are effective technical indicators for predicting stock price direction in various markets, with 56% accuracy on MACD and 81% on RSI. Canadian Journal of Business and Information Studies. https://doi.org/10.34104/cjbis.022.01370143

Turnip, H. (2022). Fundamental factors (ROE, PBV, EPS, DPR) and technical factors (trading volume) significantly and positively affect stock prices of large-cap companies on the Indonesia Stock Exchange from 2015-2019. International Journal of Research and Review. https://doi.org/10.52403/ijrr.20221124

Wardhani, S. F., & Gea, D. (2022). Artificial Neural Networks (ANN) methods backpropagation and Learning Vector Quantization can accurately predict the stock price of PT. XL Axiata, Tbk., providing valuable stock action suggestions. Journal of Theoretical and Applied Information Technology.

Xiao, H. (2023). RSI and MACD indicators, when combined, can effectively predict stock price trends, providing valuable insights for stock trading. BCP Business & Management, 38. https://doi.org/10.54691/bcpbm.v38i.3695

Zulistaini, Z. (2020). Using Moving Average Convergence Divergence (MACD) analysis, shareholders of four telecommunications companies should sell their shares to maximize profits. Journal of Computer and Applications, 10(2). https://doi.org/10.47047/CA.V10I2.91


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