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All Journal Jurnal Gamma EKSAKTA: Journal of Sciences and Data Analysis Jurnal Ekonomi : Journal of Economic Paradigma Pro Bisnis Jurnal Dinamika Pengabdian (JDP) JOIV : International Journal on Informatics Visualization Knowledge Engineering and Data Science BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) JSiI (Jurnal Sistem Informasi) JSAI (Journal Scientific and Applied Informatics) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Enthusiastic : International Journal of Applied Statistics and Data Science Proceedings Series on Physical & Formal Sciences Healthy Tadulako Journal (Jurnal Kesehatan Tadulako) Blend Sains Jurnal Teknik Jurnal Informatika dan Teknologi Pendidikan Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) KOLONI Ahsana: Jurnal Penelitian dan Pengabdian kepada Masyarakat STATISTIKA Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) Medic Nutricia : Jurnal Ilmu Kesehatan Jurnal Ilmu Komunikasi dan Sosial Politik Jurnal Kajian Islam dan Sosial Keagamaan Indonesian Journal of Islamic Law (IJIL) IERA, Islamic Education and Research Academy Emerging Statistics and Data Science Journal Jurnal Hukum dan Ekonomi Syariah

Achmad Fauzan, Achmad

brawijaya university

Author-ID : 484613

Religion Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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IMPLEMENTATION OF THE STEP FUNCTION INTERVENTION AND EXTREME LEARNING MACHINE FOR FORECASTING THE PASSENGER’S AIRPORT IN SORONG Faizin, Nur; Fauzan, Achmad; Primandari, Arum Handini
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

This study aims to forecast the number of passengers departing at the domestic departure terminal at Domine Eduard Osok Sorong Airport in 2022 using the Autoregressive Integrated Moving Average (ARIMA) method, ARIMA with Step Function Intervention, and Extreme Learning Machine (ELM). The knowledge of the number of passengers can help the airport prepare facilities. The residual ARIMA model (0,1,0) has no serial correlation (random walk) based on the Ljung-Box test. The MAPE value of the ARIMA model (0,1,0) is 65.47% which means poorly fitted. Because of it, the researchers propose an intervention in the ARIMA model. The RMSE and MAPE ARIMA Intervention (1,0,0) (0,1,0) [12] were 9,027.671 and 35.86%, respectively. Besides, this study also employed the ELM method, which has a MAPE error measurement value of 30.64%. The ELM method has the lowest error measurement results among the three methods. Therefore, the ELM method is suitable for forecasting the number of passengers with predicted values from June to September 2022 as follows: 47985, 37821, 31247, and 33578. On the other hand, intervention in ARIMA can reduce MAPE by 45%.

IMPLEMENTATION OF THE DBSCAN METHOD FOR CLUSTER MAPPING OF EARTHQUAKE SPREAD LOCATION Bariklana, Muhammad; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0867-0878

West Java area is located on the Pacific Circum and Mediterranean Circum routes, this causes West Java area to be an unstable area that is characterized by many active working volcanoes and frequent earthquakes. An analysis of the grouping of earthquake data in West Java Province area is urgently needed. The purpose of this study was to classify areas based on the density of earthquake occurrence areas in West Java using Density-Based Spatial Clustering of Application with Noise (DBSCAN). The population in this study are all earthquake events occurred in 2021. While the sample used in this study is data on the location of the distribution of earthquakes in West Java Province in 2021 taken from the BMKG online data website at dataonline.bmkg.go.id. This research began with nearest-neighbor analysis to see patterns of data distribution. If the data distribution pattern is grouped, then DBSCAN analysis can be continued. The DBSCAN algorithm uses a combination of parameters, namely minimum points (MinPts) and epsilon (Eps). Cluster results are evaluated using the silhouette coefficient. Then, in this study, deeper data exploration was carried out in three ways, namely: (1) Clustering based on the highest silhouette value, (2) clustering by lowering the MinPts value, and (3) clustering based on the smallest upper limit (supremum) value of the silhouette coefficient. The data exploration here aimed to form more clusters while still considering the silhouette coefficient value limits so that there are more areas prone to earthquakes but also maintaining the validity of the results obtained. Next, determine the best cluster results by comparing the cluster results obtained. The best cluster results were obtained at Eps=10000 and MinPts=3 which formed 12 clusters with a silhouette coefficient value of 0.713, which means that the clusters have a strong structure. It is hoped that the information regarding the grouping of areas where earthquakes frequently occur can be used as a form of earthquake disaster mitigation and minimize the impact of losses due to the earthquake.

PROVINCIAL CLUSTERING BASED ON EDUCATION INDICATORS: K-MEDOIDS APPLICATION AND K-MEDOIDS OUTLIER HANDLING Rahmawati, Octavia; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1167-1178

K-Medoids is a clustering algorithm that is often used because of its robustness against outliers. In this research, the focus is to cluster provinces based on educational level through several assessment indicators. This is in line with improving the quality of education in point 4 of the National Sustainable Development Goals (SDGs), namely "Quality Education". One of the points of the National Sustainable Development Goals (SDGs) that will still be improved is "Quality Education" which is the 4th point. This is because the success of a country is determined by the quality of good education. The condition of education in Indonesia still overlaps, so it is necessary to do equal distribution of education through clustering. The purpose of this research is to provide the best cluster results according to the Silhouette Index, which then the results of the clustering can be used as a consideration for advancing education in areas that still need attention, through policies or programs that can be developed by educational observers. This research was conducted in 34 provinces in Indonesia. The data source is from Statistical Publications by BPS RI. The method used is K-Medoids, because in this study there were outliers found. In addition to natural K-Medoids, the researcher also wants to compare methods by implementing K-Medoids with outlier handling in the form of imputed mean values and K-Medoids with imputed min-max values. The Silhouette Index results and cluster formation for the three comparators were 0.24 with 2 clusters, 0.26 with 8 clusters and 0.25 with 9 clusters, respectively. What differentiates this research from previous research is the type of outlier handling. Generally, K-Medoids are very indifferent to the existence of outliers. K-medoids is a widely recognized and straightforward clustering approach. Nevertheless, the algorithm's effectiveness might occasionally decline as a result of local outliers and the random selection of beginning medoids

SPATIAL INSIGHTS INTO EARTHQUAKE STRENGTH: A SULAWESI CASE STUDY USING ORDINARY AND ROBUST KRIGING METHODS Humairah, Nanda Lailatul; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1283-1296

The data from the Meteorology, Climatology and Geophysics Agency (BMKG) in the last 22 years shows that there have been 230 destructive earthquakes in Indonesia with the highest incidence in 2021. One of the islands frequently hit by earthquakes is Sulawesi Island. According to the 2020 Disaster Risk Index Book (IRBI), 63 of the 81 regencies/cities on Sulawesi Island have a high category earthquake risk index. Based on this, information is needed as a first step in disaster mitigation so that the government can take preventive and anticipatory actions to reduce risks associated with earthquakes and ensure the safety of people on the island of Sulawesi, one of which is obtained through spatial interpolation. In this study, the Kriging methods of interpolation, Ordinary Kriging (OK) and Robust Kriging (RK) were used. From the analysis with OK and RK, the best theoretical semivariogram model is the Exponential model with nugget, sill and range values of respectively 0.40, 0.70, and 6.50 for OK and 0.35, 0.90 and 9.50 for RK. Both methods produced the results that most areas of Sulawesi Island have the potential for shallow earthquakes with a magnitude of around 3.2 to 4.0 on the Richter scale. The potential for earthquakes with high strength is more common around the seas to the east and north of Central Sulawesi Province. The highest estimation results are at the coordinates of 120,029° East Longitude, 1.159° North Latitude, namely in the sea north of South Dampal. According to the results of K-Fold Cross Validation and Leave One Out Cross Validation, the more accurate method for estimating earthquake strength on Sulawesi Island is the RK method because the RMSE and MAPE values in the RK method are smaller than the OK method.

SPATIALLY INFORMED INSIGHTS: MODELING PERCENTAGE POVERTY IN EAST JAVA PROVINCE USING SEM WITH SPATIAL WEIGHT VARIATIONS Maulana, Ashabul Akbar; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1317-1332

The East Java Province stands as one of Indonesia's regions grappling with a notably elevated poverty rate, accounting for 11.32% of the populace. A strategic approach employed to comprehend and redress this issue involves the application of spatial analysis, wherein spatial factors are intricately integrated into the modeling and cartographic representation of poverty data. The primary objective of this research is to discern the principal determinants influencing the incidence of poverty in East Java Province, employing data reflective of the population's poverty percentages within the province for the year 2021. The study incorporates six pivotal variables, namely: the population poverty rate, open unemployment rate, labor force participation rate, average years of schooling, adjusted per capita expenditure, and the gross regional domestic product (GRDP), predicated on adjusted expenditure. Diverse weighting schemes are applied based on both distance (1) and contiguity (2). The optimal predictive model utilized is the Spatial Error Model (SEM) incorporating a Distance Band Weighing (DBW) mechanism with a designated maximum distance ( ) of 75000 meters. Outcomes indicate that the variable wielding the most substantial influence on the poverty percentage in East Java Province is the average years of schooling. Specifically, an increase in the pursuit of formal education manifests as a negative correlate to the poverty percentage, implying an inverse relationship. Moreover, the SEM model adheres to the requisite assumptions, encompassing (1) the normality of residuals, (2) homogeneity of residuals, and (3) non-spatial autocorrelation of residuals. Comparative analyses reveal that the SEM model utilizing DBW yields diminished values for MAE, MSE, RMSE, AIC, and MAPE in comparison to its linear regression counterpart. Furthermore, the pseudo- values obtained from the SEM surpass those derived from the linear regression model. Rigorous likelihood ratio tests underscore substantial disparities between the SEM and linear regression models, with the former proving more efficient and markedly enhancing the model's explanatory prowess concerning variations in the dataset.

SPATIAL MODELING OF MATERNAL HEALTH: GEOGRAPHICALLY WEIGHTED POISSON REGRESSION ON MATERNAL MORTALITY FACTORS Yuliana, Alfa; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp557-570

Data from the 2021 West Java Provincial Health Profile Report, accessed from the official website of the West Java Provincial Health Office, reveals a significant surge in maternal mortality cases, rising from 165 in 2020 to 460 in 2021. In support of efforts to reduce maternal mortality rates, this study investigates the contributing factors to this phenomenon across various districts in West Java Province. The data used is from the year 2021. This study aims to evaluate the effectiveness of Poisson regression, negative binomial regression, and Geographically Weighted Poisson Regression (GWPR) models in capturing the variability of maternal deaths in the study area for that year. A comprehensive analysis revealed that the distribution of maternal mortality fits the Poisson model, displaying significant spatial heterogeneity. Acknowledging this variability, the GWPR approach using an Adaptive Kernel Bisquare weighting was selected due to its capability to produce localized parameter estimates, which more accurately reflect the specific conditions of each location. The analyzed independent variables include the number of community health centers, coverage of antenatal services at the first (K1) and fourth (K4) visits, management of obstetric complications, and coverage of iron supplementation for pregnant women. Of the five variables, only three showed statistically significant effects; therefore, the study proceeded using these three variables. The results indicate that GWPR provides the best explanation for the variability in maternal mortality rates, with an adjusted R² value of 63.17% and a MAPE of 37.70%.

Spatial Pattern Analysis and Determinants of Stunting Prevalence in Central Sulawesi, Indonesia: Using Linear Regression, Local Moran’s I, and Random Forest Approaches Arifuddin, Adhar; Fauzan, Achmad; Hakim, Raden Bagus Fajriya; Nur, A Fahira
Healthy Tadulako Journal (Jurnal Kesehatan Tadulako) Vol. 11 No. 3 (2025)
Publisher : Faculty of Medicine, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/htj.v11i3.1863

Background: Stunting remains a significant public health issue in Indonesia, particularly in Central Sulawesi, where socio-economic and environmental factors contribute to its prevalence. Understanding these determinants is crucial for effective intervention strategies. Objective: This study aims to analyze the spatial distribution and predictors of stunting prevalence in Central Sulawesi, focusing on socio-economic and environmental factors. Methods: An observational design was employed, utilizing secondary data from the Central Sulawesi Provincial Health Department. Spatial analysis, including Moran’s I and Local Moran’s I, assessed spatial autocorrelation and identified outliers. Regression analysis and Random Forest modeling examined predictors of stunting prevalence. Results: The study found significant spatial clustering in stunting prevalence. Key socio-economic factors identified were maternal education and household income, with poverty being the most influential predictor. Random Forest analysis highlighted sanitation and access to health facilities as important, although access to clean water did not show a significant effect. Conclusion: The findings provide valuable insights into the socio-economic determinants of stunting and emphasize the need for targeted, comprehensive intervention strategies focusing on improving maternal education and addressing poverty, along with enhancing healthcare access in Central Sulawesi

Sistem Informasi Monitoring Hafalan Al-Qur'an Pondok Pesantren Al-Madina Banjarnegara Berbasis Android Nugraha, Agasta Pratama; Muktiadi, Ridho; Badharudin, Abid Yanuar; Fauzan, Achmad
Jurnal Sistem Informasi Vol. 12 No. 2 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i2.11060

Pondok Pesantren Al-Madina Banjarnegara merupakan lembaga pendidikan Islam yang menyelenggarakan program hafalan Al-Qur'an secara intensif bagi santri. Namun, proses pencatatan hafalan yang masih dilakukan secara manual menimbulkan berbagai kendala, seperti lambatnya pendistribusian informasi, potensi kehilangan data, serta kesulitan wali santri dalam menghubungkan perkembangan anak secara rutin dan real-time . Hal ini berdampak pada rendahnya efisiensi serta transparansi dalam proses evaluasi pembelajaran hafalan. Untuk menjawab tantangan tersebut, dikembangkan sebuah sistem informasi monitoring hafalan berbasis Android dengan menggunakan pendekatan Rapid Application Development (RAD). Pendekatan RAD dipilih karena mampu mempercepat proses pengembangan sistem melalui iterasi prototipe dan keterlibatan langsung pengguna. Sistem yang dibangun dilengkapi dengan fitur pencatatan hafalan digital oleh ustaz, pengiriman notifikasi otomatis kepada wali santri melalui Firebase Cloud Messaging (FCM), serta laporan perkembangan hafalan berupa e-Rapor yang dapat diakses dan diunduh melalui aplikasi. Sistem ini juga mengintegrasikan halaman Al-Qur'an digital yang bersumber dari API EQuran.id. Dengan adanya sistem ini, proses pencatatan hafalan menjadi lebih sistematis, informasi dapat tersampaikan secara cepat dan akurat, serta komunikasi antara pesantren dan wali santri menjadi lebih efektif. Pengembangan sistem ini diharapkan tidak hanya menyelesaikan permasalahan administratif, tetapi juga menjadi langkah awal transformasi digital dalam pengelolaan pendidikan pesantren.

An ST-DBSCAN Approach to Spatio-Temporal Clustering of Earthquake Events in West Java, Indonesia Widyawati, Dwi Kartika; Fauzan, Achmad
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.33079

Earthquakes are among the most frequent and damaging natural disasters in Indonesia, particularly in West Java Province, where their unpredictable occurrence often causes casualties and severe infrastructure damage. This study aims to identify spatial and temporal patterns of earthquakes to support disaster risk mitigation efforts. A quantitative exploratory approach was applied using the Spatio-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN) method, which groups earthquake events based on their proximity in space and time while distinguishing random noise. The analysis utilized secondary earthquake data from the Meteorology, Climatology, and Geophysics Agency (BMKG) covering the period January 2022 to December 2023. The results revealed eight distinct clusters and several high-risk zones with strong internal similarity (silhouette coefficient = 0.721), indicating stable and stationary patterns over the observed period. These findings demonstrate that ST-DBSCAN is effective in detecting consistent earthquake-prone areas. More importantly, the study provides practical implications for disaster mitigation, including the development of targeted early warning systems, prioritization of high-risk areas such as Cianjur Regency, and more efficient allocation of resources to strengthen preparedness and community safety.

A Machine Learning Approach to Spatial Analysis of Paddy Field Conversion Using Multispectral Sentinel-2A Imagery Fauzan, Achmad; Kurnia, Anang
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3617

The expanse of rice fields is a critical metric as it is intimately linked to agricultural productivity in a given locale. This study investigates the application of satellite imagery to quantify trice fields' acreage and temporal variations. The data utilized was acquired by the Sentinel-2A multispectral satellite. The variables employed are the image's baseband and spectral index. The research area encompasses the Sukamakmur sub-district in Bogor Regency, Indonesia. The types of machine learning models include Extreme Gradient Boosting (XGBoost), Multi-Layer Perceptron (MLP), and k-Nearest Neighbor (kNN). The simulation of class numbers is conducted to achieve the most stable and precise evaluation metric values. The XGBoost algorithm is used for the overall classification process of the region based on the optimal metric score. The model's accuracy, precision, recall, and F1-score are 92.37%, 92.3%, 92.38%, and 92.33%, respectively, indicating a very good performance. The model successfully captures a decline in rice field area between 2020 and 2023. Using the Modified Moran’s Index (MMI), the study reveals a positive spatial autocorrelation, indicating a clustered pattern in land-use change. Regions that experience either substantial or minor changes in land use are commonly situated near areas exhibiting similar characteristics. This study presents a spatially aware machine learning framework that enables the effective monitoring of agricultural land-use dynamics. In the future, this framework can be enhanced by integrating time-series forecasting and socio-economic data, supporting more informed decision-making in food security planning and agricultural policy development.

Co-Authors Abid Yanuar Badharudin Adhar Arifuddin Agung Dwi Ramadhan, Agung Ahmad, A. Sri Sartika Sufiina Amalina, Nur Dina Anang Kurnia Andreas Wahyu Gunawan Annisa Dwi Risqi Ariyadi, Fandy Akhmad Ashari Ashari Ayu Wulandari Bariklana, Muhammad Buana, Arya Galih Cahyani, Laras Niken Dwi Christopher Yudha Erlangga Dafrian, Rafli Danang Bagus Wibowo Daryono Daryono, Daryono Diana, Diana Apriyanti Dwitra Gusti Alriscki Efi Miftah Faridli, Efi Miftah Faza Izzatul Muttaqin Fazira, Nabila Dwi Febrianti, Nur Qadri Feri Wibowo Fitri Amalia Fitri Yanti Ghefira Nurhaliza, Celine Hafidz, Syauqi Jauzza Hakim, Raden Bagus Fajriya Humairah, Nanda Lailatul Maulana, Ashabul Akbar Maziyah Mazza Basya Mohamad Irkham Mamungkas Nabilah, Muna Faizatun Najlah Nugraha, Agasta Pratama Nur Faizin Oktaviani, Nabila Pradana, Wahyu Aji Pratama, Arizqi Ihsan Primandari, Arum Handini Purwanto, Kalis Purwanto, Muhammad Idris Putri, Sabrina Marta Rahmawati, Octavia Ramadhan, Muhammad Rizal Ramadhan, Rizki Fauzian Ridho Muktiadi Rinaldi Sjahril, Rinaldi Roza Azizah Primatika, Roza Azizah Sadat, Fauzan Safira, Nuzulia Nur Saini, Mukhamat Santoso, Alfian Sirojudin, Didin Supriyono Supriyono Suria, Muh. Yunus Sutisna, Irwan Syifa Fauziyah Tito Pinandita Wahyudin, M. Abyan Widyastuti, Galuh Widyawati, Dwi Kartika Wiranti, Ridha Yanasari, Herlinda Yuliana, Alfa Zakariyah Zakariyah

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