Claim Missing Document
Check
Articles

Found 2 Documents
Search

Keanekaragaman, Kerapatan, dan Tutupan Lamun Di Pulau Pari, Kepulauan Seribu Baga, Sisean; Taufiqurahman, Taufiqurahman; Aqil, Deden Ibnu; Florensia, Aurora; Pratiwi, Lidya
Biosel Biology Science and Education Vol. 11 No. 2 (2022): BIOSEL (Biology Science and Education: Jurnal Penelitian Science dan Pendidika
Publisher : INSTITUT AGAMA ISLAM NEGERI AMBON

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.035 KB) | DOI: 10.33477/bs.v11i2.3373

Abstract

Pari Island is located in Thousand Islands Administrative District, DKI Jakarta Province, with its status as a tourist area, research, and coastal ecosystem conservation. This research is aimed to determine the diversity, abundance, and the seagrass cover located in Pari Island. The method used is a survey with straight transects and quadrants in three different stations, which consist of Pantai Bintang (station 1), Perawan (station 2), and Rengge (station 3). The data analysis towards seagrass diversity uses Shannon-Wiener’s Diversity Index, the seagrass density uses Di calculation, and the seagrass cover uses the seagrass cover index (C). Based on the research conducted, there were 3 seagrass species, which were Enhalus acoroides, Thalassia hemprichii, and Cymodocea rotundata. The highest H’ Index with the value of 2.0 is station 1, which is categorized as mid diversity criteria and the lowest with the value of  0.8 is station 2, which is categorized as low diversity. The highest seagrass density is Enhalus acoroides located in station 1 with the value of 165 (ind/m2) and the lowest which is Cymodocea rotundata located in station 3 with the value of 18 (ind/m2). The best seagrass cover value is in station 1 with the value of 55%, which is categorized as less healthy and the worst cover is station 2 with the value of 21%, which is categorized as poor. Keywords: Diversity, Density, Pari Island, Seagrass Cover
Exploring School Enrollment Trends in Indonesia Through Time Series Analysis to Inform Counselling and Communication Strategies Yollanda, Mutia; Weisha, Ghea; Pratiwi, Lidya; Putra, Ade Herdian; Putra, Robi Jaya; Yaser, Mishbah El
Counseling and Humanities Review Vol 5, No 1 (2025): Counseling and Humanities Review
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/0001299chr2025

Abstract

A time series analysis of School Enrollment Rates across different age groups in Indonesia from 2003 to 2024 was conducted using ARIMA modelling. Data were segmented into four age groups: 7 to 12, 13 to 15, 16 to 18, and 19 to 24 years. Stationarity testing required first-order differencing, and ARIMA models were selected based on autocorrelation and partial autocorrelation structures. The ARIMA(1,1,0) model showed the best fit for the younger groups, capturing the gradual and predictable participation trends influenced by long-term education policies and stable school enrollment patterns. Forecast accuracy was evaluated using Mean Absolute Percentage Error (MAPE) and Mean Squared Error (MSE), revealing excellent accuracy for ages 7 to 12 with MAPE 0.036 percent and MSE 0.001, and for ages 13 to 15 with MAPE 0.089 percent and MSE 0.008. Forecasts for ages 16 to 18 showed moderate accuracy, while results for 19 to 24 indicated greater variability. These findings inform the development of age-specific guidance counselling and public communication strategies to address distinct educational challenges. The study underscores the utility of interpretable forecasting models in supporting evidence-based education policy and planning.