cover
Contact Name
Dr. Muhammad Ahsan
Contact Email
muh.ahsan@its.ac.id
Phone
+6281331551312
Journal Mail Official
inferensi.statistika@its.ac.id
Editorial Address
Department of Statistics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember (ITS) Kampus ITS Keputih Sukolilo Surabaya Indonesia 60111
Location
Kota surabaya,
Jawa timur
INDONESIA
Inferensi
ISSN : 0216308X     EISSN : 27213862     DOI : http://dx.doi.org/10.12962/j27213862
The aim of Inferensi is to publish original articles concerning statistical theories and novel applications in diverse research fields related to statistics and data science. The objective of papers should be to contribute to the understanding of the statistical methodology and/or to develop and improve statistical methods; any mathematical theory should be directed towards these aims; and any approach in data science. The kinds of contribution considered include descriptions of new methods of collecting or analysing data, with the underlying theory, an indication of the scope of application and preferably a real example. Also considered are comparisons, critical evaluations and new applications of existing methods, contributions to probability theory which have a clear practical bearing (including the formulation and analysis of stochastic models), statistical computation or simulation where the original methodology is involved and original contributions to the foundations of statistical science. It also sometimes publishes review and expository articles on specific topics, which are expected to bring valuable information for researchers interested in the fields selected. The journal contributes to broadening the coverage of statistics and data analysis in publishing articles based on innovative ideas. The journal is also unique in combining traditional statistical science and relatively new data science. All articles are refereed by experts.
Articles 183 Documents
Multivariate Forecasting of GAU/IDR Gold Prices Using a Hybrid Prophet-LSTM Model Based on Macroeconomic Indicators Safira Khoirulanisa Salsabila; Nur Achmey Selgi Harwanti
Inferensi Vol 9 No 2 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i2.10072

Abstract

Forecasting gold prices in the Indonesian domestic market (GAU/IDR) presents its own unique challenges, as its volatility is simultaneously driven by global gold price fluctuations and the dynamics of the Rupiah exchange rate against the US dollar. This study proposes a multivariate Hybrid Prophet-LSTM model that integrates seven macroeconomic indicators (GAU/USD, USD/IDR, DXY, Federal Funds Rate, BI Rate, Indonesia's domestic inflation, and crude oil prices) as exogenous variables to forecast daily GAU/IDR gold prices for the 2021-2026 period. The hybrid architecture uses a residual learning approach: Prophet captures the long-term trend and seasonal decomposition, while LSTM corrects the remaining nonlinear residuals. A forecast continuity mechanism is also implemented to prevent unrealistic vertical jumps during the transition from historical data to future projections. A 90-day out-of-sample evaluation (January 2026-April 2026) shows that the Hybrid Prophet-LSTM achieves a MAPE of 0.8525%, RMSE of IDR 28,605/gram, MAE of IDR 22,398/gram, and an of 0.9429, outperforming Prophet (MAPE 1.0655%) and a univariate LSTM (MAPE 22.7450%). A 30-day projection for May 2026 estimates the GAU/IDR price to be in the range of IDR 2,431,453 to IDR 2,651,542 per gram
Indeks Aksesibilitas Spasial dan Kesesuaian Lokasi Fasilitas Kesehatan Berdasarkan POI dan Pembelajaran Mesin di Provinsi DIY. Fat'hul Mubin Gufron; Setia Pramana
Inferensi Vol 9 No 2 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i2.10083

Abstract

The unequal distribution of health facilities is a major cause of inequality in accessibility, especially in hard-to-reach rural areas. Therefore, equitable development of health facilities is needed, targeting both access and location suitability. This study aims to measure spatial accessibility and identify suitable locations for health facility development to support efficient, equitable, and targeted planning. The method used includes calculating the accessibility index using Enhanced Two Step Floating Catchment Area (E2SFCA) and location suitability modeling with machine learning algorithms, as well as analysis of the relationship between the two using scatterplots. Random forest demonstrated the best performance with an accuracy of 85.71%. Identification of the relationship between accessibility measurements and suitability modeling successfully identified 85 villages with low access but high suitability, which are recommended as priority locations for health facility development. These findings are expected to form the basis for evidence-based planning to achieve equitable distribution of health services in the Special Region of Yogyakarta Province.
Regresi Data Panel dengan Feasible Generalized Least Squares untuk Menganalisis Angka Partisipasi Sekolah Remaja di Indonesia Retno Mayapada; Andi Harismahyanti; A. Muthiah Nur Angriany
Inferensi Vol 9 No 2 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i2.10102

Abstract

School participation among adolescents aged 16-18 years varies across provinces in Indonesia, reflecting disparities in educational access. This study examines the associations of the Unemployment Rate (UR), Average Hourly Earnings of Employees (AHE), Mean Years of Schooling (MYS), and Percentage of Poor Population (PPP) with the School Participation Rate (SPR) with a panel dataset comprising 34 provinces observed from 2018 to 2023. Selection between the panel specifications was based on the Chow and Hausman tests, with the results favoring the Fixed Effects Model (FEM). Diagnostic examination identified heteroskedasticity, serial correlation, and cross-sectional dependence. The model was therefore re-estimated using the modified Feasible Generalized Least Squares (FGLS) estimator proposed by Bai, Choi, and Liao, which accounts for these error dependencies. Results show that AHE, MYS, and PPP were positively associated with SPR, with significant relationships at the 5% level, whereas UR was positively but not significantly associated with SPR. These findings indicate that household economic capacity, educational attainment, and poverty levels are significantly associated with differences in school participation across provinces, while provincial unemployment conditions do not show a statistically significant association. The findings provide evidence on socioeconomic factors associated with school participation among adolescents aged 16-18 years in Indonesia.