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All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN JI-KES (Jurnal Ilmu Kesehatan) Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat Jurnal Aplikasi Sains Data
Dinda Galuh Guminta
Universitas Negeri Surabaya
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Mathematics Public Health Social Sciences

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Pemodelan Spasial Kasus Kematian Akibat Covid-19 di Provinsi Jawa Timur Tahun 2020 Herti Maryani; Lusi Kristiana; Dinda Galuh Guminta
JI-KES (Jurnal Ilmu Kesehatan) Vol. 6 No. 1 (2022): JI-KES (Jurnal Ilmu Kesehatan)
Publisher : STIKes Hafshawaty Pesantren Zainul Hasan Probolinggo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33006/ji-kes.v6i1.412

Abstract

AbstrakProvinsi Jawa Timur merupakan provinsi yang mempunyai jumlah kasus kematian yang tinggi dibanding dengan provinsi lain di Indonesia. Tujuan penelitian adalah melakukan pemodelan kematian akibat Covid-19 di Provinsi Jawa Timur pada tahun 2020, menggunakan analisis Geographically Weighted Regression (GWR). Analisis GWR merupakan pengembangan dari regresi linier dengan parameter model yang berbeda di setiap pengamatan (wilayah).  Data yang dianalisis adalah data sekunder dari Dinas Kesehatan Provinsi Jawa Timur dan Badan Pusat Statistik (BPS) Provinsi Jawa Timur. Jumlah kematian akibat covid-19 di Jawa Timur mencapai 84.152 jiwa sampai dengan bulan Desember 2020. Hasil analisis menunjukkan bahwa faktor yang mempengaruhi kematian akibat Covid-19 di sebagian besar wilayah Provinsi Jawa Timur adalah jumlah dokter umum di Rumah Sakit dan jumlah pelayanan kesehatan penyakit Diabetes Melitus, sedangkan variable lainnya yang berpengaruh signifikan adalah pelayanan kesehatan penderita Hipertensi dan  jumlah Rumah Sakit Umum. Analisis GWR menghasilkan  pemodelan jumlah  kematian akibat Covid-19 di Jawa Timur  dengan koefisien determinasi yang lebih tinggi dibanding pemodelan secara global. Pemodelan secara geografis menghasilkan 5 kelompok kabupaten/kota, dengan variabel jumlah dokter umum di Rumah Sakit dan pelayanan kesehatan Diabetes Melitus yang cukup berpengaruh di sebagian besar kabupaten/kota di Jawa Timur.Kata kunci: Covid-19, Jawa Timur, Geographically Weighted RegressionAbstractEast Java Province was a province that had a high number of deaths compared to other provinces in Indonesia. Using Geographically Weighted Regression (GWR) analysis, the study's goal was to predict the number of deaths caused by COVID-19 in the East Java Province in 2020. With various model parameters in each observation, GWR analysis was a progression of linear regression (region). Secondary data from the East Java Province's Statistics Agency and Health Agency were used in the analysis. As of December 2020, 84.152 individuals had perished in East Java as a result of COVID-19. The analysis's findings indicate that the number of public hospitals and the availability of healthcare for people with diabetes mellitus were the two health factors that had the greatest impact on Covid-19 deaths in the majority of East Java Province. Other factors that had a significant impact included the number of public hospitals and the availability of healthcare for people with hypertension.The analysis of the GWR model on the number of deaths due to Covid-19 in East Java resulted in a higher coefficient of determination than linear regression modeling. Geographical modeling resulted in 5 groups of districts/cities, with the variable number of general doctors in hospitals and diabetes mellitus health services being quite influential in most districts/cities in East Java.Keyword: Covid-19, East Java Provinces, Geographically Weighted Regression
Comparison of ARIMA and SARIMA Methods for Non-Oil and Gas Export Forecasting in East Java Dinda Galuh Guminta
Jurnal Aplikasi Sains Data Vol. 1 No. 1 (2025): Journal of Data Science Applications.
Publisher : Program Studi Sains Data UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jasid.v1i1.2

Abstract

Forecasting plays a pivotal role in economic planning, particularly in aligning supply with demand and informing production decisions. This study aims to compare the performance of the Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) models in forecasting the non-oil and gas export values of East Java, a region known for its dynamic trade activity. Using monthly time series data spanning from January 2007 to January 2024, sourced from the Central Statistics Agency (BPS) of East Java Province, this research conducts an in-depth analysis of forecasting accuracy and model suitability. Before model implementation, the dataset underwent several preprocessing steps to ensure its quality, including the handling of missing values and outlier adjustments. Both ARIMA and SARIMA models were developed, calibrated, and evaluated using standard forecasting performance metrics, namely Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The ARIMA model exhibited consistently lower error rates across all three metrics, indicating its robustness in capturing the underlying patterns within the export data. In contrast, while the SARIMA model incorporated seasonal components, its performance did not surpass that of ARIMA in this specific case. The comparative findings suggest that, despite the seasonal nature of trade, the ARIMA model is more suitable for short-term forecasting of East Java’s non-oil and gas exports. This research contributes to the broader literature on economic forecasting by emphasizing the importance of selecting appropriate models based on data characteristics. Furthermore, the results provide valuable insights for policymakers and stakeholders engaged in export planning and regional trade development In this result the ARIMA model overcome the SARIMA with MAPE 0.116 to 0.983.
Higher-order SEM-PLS Modeling of School Readiness Among Indonesian Senior High School Students Dinda Galuh Guminta; Hasanuddin Al-Habib; Ulfa Siti Nuraini; Kartika Chandra Dewi
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 23 No. 1 (2026)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2026.v23.i1.18060

Abstract

Improving the quality of secondary education is a strategic priority in Indonesia due to its impact on human wellbeing. Secondary education faces challenges in improving the quality of learning and students' psychological readiness. School preparation is widely acknowledged as a multifaceted concept that highlights the significance of social-emotional engagement, self-regulation, and cognitive-motivational engagement. Therefore, this study aims to examine the construct of school readiness in Indonesia senior high school students using higher-order SEM-PLS. Results indicate that behavioral regulation is the strongest predictor of academic achievement (0.385) and functions as the central mechanism transmitting social-emotional engagement into academic outcomes. However, cognitive-motivational factors exert a competitive mediating effect, indicating that academic grades do not always improve among students who show strong cognitive-motivational engagement (-0.130). The results of this study highlight the important role of behavioral regulation in academic achievement and indicate that social-emotional engagement exerts the strongest overall influence on cognitive-motivational engagement, thereby supporting a multidimensional integrated model of school readiness.
Digital Literacy Mentoring and Basic Visual Programming for Indonesian Diaspora Children at Sanggar Belajar PERMAI, Penang, Malaysia Danang Ariyanto; Yuliani Puji Astuti; Affiati Oktaviarina; Riskyana Dewi Intan Puspitasari; Dinda Galuh Guminta; Yuni Rosita Dewi; Dimas Avian Maulana
KENDURI : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 6 No. 2 (2026): May-August
Publisher : Yayasan Darussalam Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62159/kenduri.v6i2.2472

Abstract

Digital literacy and basic programming skills are important competencies that need to be introduced from an early age, particularly for children who are increasingly exposed to digital technology and online learning environments. This community service activity aimed to provide digital literacy mentoring and introduce basic visual programming to Indonesian diaspora children at Sanggar Belajar PERMAI, Penang, Malaysia. The program was conducted online through Zoom Meeting on December 23, 2025, by a team from the Faculty of Mathematics and Natural Sciences, Universitas Negeri Surabaya, in collaboration with Sanggar Belajar PERMAI. The activity was implemented using a participatory mentoring approach supported by a learning module prepared by the team. The materials covered digital literacy, computational thinking, basic programming logic, sequence, loops, and debugging through visual block-based activities using studio.code.org as a supporting learning platform. The evaluation was conducted qualitatively through observation of participant engagement, interaction, ability to follow instructions, and completion of visual programming challenges. The results showed that participants were able to understand basic programming logic through daily life analogies and visual activities. Participant engagement also increased gradually during the session, especially when they worked on game-based programming challenges. Although the online format limited individual monitoring and direct interaction, the activity remained interactive and was supported by facilitators and parents. This program contributed to expanding access to child-friendly technology learning and strengthening participants’ digital awareness, logical thinking, confidence, and problem-solving skills.
Co-Authors AFFIATI OKTAVIARINA Danang Ariyanto Hasanuddin Al-Habib Herti Maryani Kartika Chandra Dewi Lusi Kristiana Maulana, Dimas Avian Riskyana Dewi Intan Puspitasari Ulfa Siti Nuraini Yuliani Puji Astuti Yuni Rosita Dewi