Judul: Peramalan Harga Saham TLKM Menggunakan Model Hybrid Regresi Deret Waktu dan ARIMA
Abstrak: Investor saham di Indonesia meningkat pasca pandemik Covid-19. Saham diminati masyarakat Indonesia karena memberikan return yang cukup besar. Namun return yang tinggi sebanding dengan risiko tinggi yang harus dihadapi oleh investor. Untuk mengurangi risiko yang terjadi, maka diperlukan peramalan harga saham. Harga saham merupakan data deret waktu maka harga saham dapat dimodelkan dengan regresi deret waktu. Namun hasil yang diperoleh untuk harga saham TLKM melanggar asumsi autokorelasi sehingga penelitian dilanjutkan dengan memodelkan sisaan menggunakan model ARIMA. Model ARIMA(2,1,1) merupakan model terbaik untuk memodelkan sisaan karena memenuhi semua asumsi dan memiliki nilai AIC terkecil. Jadi, harga saham TLKM dimodelkan dengan menggabungkan regresi deret waktu dan model ARIMA (ARIMA Hybrid). Hasil peramalan harga saham TLKM untuk sembilan periode berikutnya menghasilkan nilai MAPE 2.97%., Investor in Indonesia increased after the Covid-19 pandemic. Stocks are in demand by the Indonesian because they provide big return. However, the high return is proportional to the high risk that must be faced by investors. To reduce the risk that occurs, it is necessary to forecast stock prices. Stock prices are time series data, so stock price can be modeled with time series regression. However, the results obtained for TLKM stock price violated the assumption of autocorrelation so that the research is continued by modeling the residuals using the ARIMA model. ARIMA(2,1,1) model is the best model to the residuals because it fulfills all assumptions and has the smallest AIC value. Therefore, the stock price of TLKM is modeled by combining the time series regression and ARIMA model (ARIMA Hybrid). Forecasting results for the next nine periods of the TLKM stock price produce a MAPE value of 2.97%.
Keyword: ARIMA Hybrid, Harga Saham, Peramalan, Regresi Deret Waktu

Judul: Comparison of Handling Violations of Assumptions of Linear Regression Models Using Linear Time Series Regression and the Cochrane-Orcutt Method
Abstrak: Seorang investor memiliki keinginan untuk mendapatkan keuntungan dari hasil berinvestasi dengan cara membeli saham dari suatu perusahaan. Selain memberikan imbal hasil yang tinggi, berinvestasi pada saham juga memiliki risiko yang tinggi. Oleh karena itu, untuk mengurangi risiko dilakukan peramalan harga saham di masa depan. Adapun metode yang digunakan yaitu melalui model regresi linear. Model tersebut memiliki asumsi-asumsi yang harus dipenuhi. Dalam penelitian ini dilakukan studi kasus pada harga saham BMRI yang diregresikan terhadap IHSG. Terdapat pelanggaran asumsi kebebasan galat yang ditangani dengan metode Cochrane-Orcutt dan regresi linear time series. Dari dua metode tersebut dibandingkan dan didapatkan bahwa metode Cochrane-Orcutt lebih baik dengan MAPE sebesar 0,886% daripada metode regresi time series dengan MAPE sebesar 5,178%., An investor has a desire to benefit from investment results by buying shares of a company. Apart from providing high returns, investing in stocks carries a high risk. Therefore, to reduce risk, stock price forecasting is carried out in the future. The method used is a linear regression model. The model has assumptions that must be met. This research, conducted a case study on BMRI's stock price which was regressed against the IDX Composite. There is a violation of the assumption of freedom of error which is handled by the Cochrane-Orcutt method and linear time series regression. The two methods were compared and it was found that the Cochrane-Orcutt method was better, with a MAPE of 0.886% than the time series regression method, with a MAPE of 5.178%.
Keyword: ARIMA, Cochrane-Orcutt, Harga Saham, Regresi Time Series

Judul: Morfologi Organ Reproduksi Betina Walet Linchi (Collocalia linchi)
Abstrak: This research is aimed to describe the morphology of the female reproductive organs of the cave swiftlets (C. linchi ) macroscopic and microscopically. Four female reproduction organs were used in this study. Microscopic observation was done using Hematoxilin – eosin (HE), alcian blue (AB) pH 2.5 and periodic acid Schiff (PAS) staining methods. The reproductive organs were consisted of ovarium and oviduct. The oviduct has five parts: infundibulum, magnum, isthmus, uterus and vagina. The mucosa of oviduct has mucosal folds and lined with columnar ciliated epithelial cells. Glandular glands were found in the lamina propria of oviduct, except in the vagina. The thick muscle of sphincter uterovagina was found in the border between uterus and vagina. Using AB-PAS staining methods, it was detected that oviduct contained neutral and acid carbohydrate, especially in the secrete glands of oviduct.
Keyword: oviduct., ovarium, Collocalia linchi