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All Journal Diakoneo: Jurnal Pengabdian kepada Masyarakat Theta: Journal of Statistics
Ferdian Bangkit Wijaya
Universitas Sultan Ageng Tirtayasa
Humanities Environmental Science Social Sciences Other

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Journal : theta journal of statistics

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Robust Quality Control Implementation for Nickel Pig Iron Using Median Absolute Deviation Estimators Aditya Rahadian Fachrur; Chyntia Devi Octaviany; Wiwien Suzanti; Midia Rahma; Mariana Feronica Damanik; Ferdian Bangkit Wijaya
Theta: Journal of Statistics Vol 1, No 1 (2025): Available Online in March 2025
Publisher : Faculty of Engineering, Univesitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/tjs.v1i1.31481

Abstract

Nickel Pig Iron (NPI) is one of the main products of Indonesia's nickel-based industry, which is still expanding. Reducing production costs and guaranteeing product quality depends on maintaining a constant nickel content. The Median Absolute Deviation (MAD) estimator, which is resistant to outliers and non-normal distributions, is used in this study's control charts and process capability analysis. After 15 days of production, data was gathered and examined using capability indices and control charts based on MAD. According to the results, the process mean is not statistically in control since many points exceed the control borders, even while process variation stays within the control limits. Acceptable process precision was indicated by the process capability index CpMAD being above 1. However, the CpkMAD value below 1 suggests that the mean process output does not consistently meet the target specifications. These findings highlight the need for further investigation and process improvement to enhance quality consistency in NPI production.
Forecasting the Open Unemployment Rate in Banten Province Using the FB Prophet Method in Python Programming Language Ferdian Bangkit Wijaya; Deananta Pramudia Putra; Mahsa Azzahra; Faula Arina; Fajri Ikhsan
Theta: Journal of Statistics Vol 1, No 1 (2025): Available Online in March 2025
Publisher : Faculty of Engineering, Univesitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/tjs.v1i1.31309

Abstract

The Open Unemployment Rate is a key indicator in measuring labor market imbalances, reflecting the economic dynamics of a region. Banten Province has consistently ranked among the top three provinces with the highest Open Unemployment Rate in Indonesia over the past decade, indicating structural challenges in employment. To address this issue, a forecasting model is needed to provide accurate predictions that support more effective labor policy planning. This study uses the Prophet method, an additive regression approach developed by Facebook, to forecast the Open Unemployment Rate in Banten Province over the next 10 semesters (February 2025-August 2029). The data used is sourced from the Statistics Indonesia (BPS) for the period 2005-2024, collected every semester (February and August). The model's performance is evaluated using the Mean Absolute Percentage Error (MAPE) as the primary evaluation metric. The results show that the Prophet model effectively captures trend and seasonal patterns. With a MAPE value of 5.3910%, the model demonstrates very good accuracy (MAPE < 10%), making it suitable for medium-term forecasting. The predictions indicate a downward trend in the Open Unemployment Rate in Banten over the next five years. The conclusion of this study suggests that the Prophet model can be a reliable tool for projecting the Open Unemployment Rate and supporting labor policy planning in Banten. Future research is expected to incorporate external factors or use hybrid modeling approaches to improve prediction accuracy.
Co-Authors Aditya Rahadian Fachrur Akhmad Arif Prasojo Chyntia Devi Octaviany Deananta Pramudia Putra Destari Rahman Fajri Ikhsan Faula Arina Ike Juliana Putri Pangaribuan Mahsa Azzahra Mariana Feronica Damanik Midia Rahma Muhammad Tabina Zachari Wiwien Suzanti