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All Journal JMPM: Jurnal Matematika dan Pendidikan Matematika Jambura Journal of Mathematics JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Al-Mulk: Jurnal Pengabdian Masyarakat
Akolo, Ingka Rizkyani
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Mathematics Social Sciences Other

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PENGGUNAAN METODE PERMAINAN KARTESIUS DALAM MENINGKATKAN PENGETAHUAN DASAR IPA SISWA MADRASAH IBTIDAIYAH AL-FALAH KABUPATEN GORONTALO Napu, Dewi Darmiyani; Mohamad, Sabrina Nadjib; Akolo, Ingka Rizkyani; Sarif, Suharia
Al-Mulk: Jurnal Pengabdian Masyarakat Vol 2, No 1 (2024)
Publisher : Institut Agama Islam Negeri Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46339/al-mulk.v2i1.1335

Abstract

One of the method that can be used for science learning in elementary schools is educational game. Through games we can create ideal conditions for learning and improve the quality of learning. This service activity uses Cartesian games as a learning medium. This activity was carried out at Madrasah Al-Falah, Gorontalo district. The results of the service activities show that the use of the Cartesian game method is very effective in increasing children's basic science knowledge and they can have an enjoyable learning experience.Keywords: Game Methode; Cartesius ; Sains.
Proyeksi Indeks Pembangunan Berwawasan Kependudukan (IPBK) Menggunakan Single Dan Double Exponential Smoothing (Studi Di Kabupaten Gorontalo 2024 – 2026) Akolo, Ingka Rizkyani; Umar, Razak; Yasin, Indri Afriani
Jambura Journal of Probability and Statistics Vol 5, No 2 (2024): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v5i2.24854

Abstract

The Population-Oriented Development Index (IPBK) is an important indicator for measuring regional development success, focusing on human resource quality. This study aims to project the IPBK for 2024–2026 and identify the best method for projecting the IPBK in Gorontalo Regency. The projection methods used are single and double exponential smoothing. The IPBK data for Gorontalo Regency was obtained from the 2024 BKKBN Central Publication. The variables include participation (X1), sustainability (X2), inclusiveness (X3), holistic integration (X4), equality (X5), and IPBK (X6). The data was analyzed using Minitab 16 software. The results indicate that the double exponential smoothing method outperforms the single exponential smoothing method for projecting the IPBK and its dimensions in Gorontalo Regency, achieving a MAPE value of less than 10\%. The IPBK projections and its dimensions for 2024–2026 using the double exponential smoothing method show an annual upward trend, predicting that by 2025–2026, Gorontalo Regency’s IPBK status will rise from category 3 (upper-middle status) to category 4 (high status). This high status indicates that Gorontalo Regency has achieved significant progress in key indicators reflecting the welfare and quality of life of its residents. 
Perbandingan Propensity Score Stratification dan Propensity Score Matching dengan Pendekatan Multivariate Adaptive Regression Spline Akolo, Ingka Rizkyani; Ningsih, Setia; Dukalang, Hendra
Jambura Journal of Mathematics Vol 6, No 2: August 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v6i2.26137

Abstract

Research on complications of Diabetes Mellitus (DM) is multifactorial, where the risk factors causing DM complications are interrelated, leading to confounding bias, which results in inaccurate research findings. Confounding bias can be reduced using the propensity score method. This study aims to compare the performance of the Propensity Score Stratification (PSS) and Propensity Score Matching (PSM) methods with the Multivariate Adaptive Regression Spline (MARS) approach in estimating treatment effects on DM complication cases. The data used is the medical records of type-2 DM patients at Hospital X. The results showed that the PSS method with the MARS approach is not suitable for small data sets, as it can lead to treatment or control groups lacking members, making it impossible to calculate the p-value in balance testing or the Percent Bias Reduction (PBR). The estimated Average Treatment Effect (ATE) using the PSS method was 0.487 with a PBR of 35.1%, whereas the estimated Average Treatment for Treated (ATT) using the PSM method was 0.531 with a PBR of 99.46%. These PBR values indicate that the best method for estimating treatment effects and the one that can reduce the most bias in this case is the PSM method with MARS. The analysis also showed that serum uric acid levels significantly affect the peripheral diabetic neuropathy (PDN) status of DM patients.
Comparison Between Neural Network and Grey System Models for Cooking Oil Price Fastha Aulia Pradhani; Susila, Muktar Redy; Akolo, Ingka Rizkyani
JMPM: Jurnal Matematika dan Pendidikan Matematika Vol 10 No 1 (2025): March - August 2025
Publisher : Prodi Pendidikan Matematika Universitas Pesantren Tinggi Darul Ulum Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/jmpm.v10i1.3395

Abstract

Cooking oil is one of the primary raw materials used in Indonesia. In this study, a comparison of the two forecasting models from the two methods, namely Neural Network and Grey System, was carried out. Forecasting is carried out on cooking oil raw materials, namely CPO production volume and demand for related products, namely biodiesel, to analyze changes in cooking oil prices. The appropriate forecasting model is expected to be able to describe the pattern of cooking oil price fluctuations for the following few periods. The criteria for selecting the best model use the minimum MAPE testing value. The results show that the Grey System method produces the best forecasting model for biodiesel demand data with a small amount of data, while for the CPO variable, which has a larger amount of data, the best model is obtained using the Neural Network model, with the MLP (3-3-1) architecture.
Co-Authors Dukalang, Hendra Fastha Aulia Pradhani Mohamad, Sabrina Nadjib Napu, Dewi Darmiyani Ningsih, Setia Razak Umar Sarif, Suharia Susila, Muktar Redy Yasin, Indri Afriani