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All Journal SAINSMAT Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) BAREKENG: Jurnal Ilmu Matematika dan Terapan Inferensi Jurnal Darma Agung Quantitative Economics and Management Studies Panrannuangku Jurnal Pengabdian Masyarakat Parameter: Journal of Statistics Journal of Mathematics: Theory and Applications SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research English Language, Linguistics, and Culture International Journal (ELSTIC-IJ) Ininnawa: Jurnal Pengabdian Masyarakat Prosiding Seminar Nasional Dies Natalis Universitas Negeri Makassar Jurnal Pengabdian Masyarakat Indonesia Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) JAMP
Hardianti Hafid
Universitas Negeri Makassar
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Clustering of Disaster Risk in Indonesian Regions Using Self-Organizing Maps and K-Means Hardianti Hafid; Isma Muthahharah
Journal of Mathematics: Theory and Applications Vol 7 No 2 (2025): Volume 7, Nomor 2, 2025
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v7i2.5365

Abstract

Indonesia is one of the countries with a high level of vulnerability to natural disasters, making accurate risk mapping essential to support mitigation planning. This study aims to cluster the provinces of Indonesia based on disaster occurrence characteristics using a hybrid approach of Self-Organizing Maps (SOM) and K-Means. The data were obtained from the Indonesian National Disaster Management Agency (BNPB), covering the frequency and types of disasters such as floods, extreme weather, eruptions, abrasion, earthquakes, forest/land fires, droughts, and landslides. The SOM representation results were clustered using K-Means, with the optimal number of clusters determined through the evaluation of the Davies–Bouldin index, Silhouette coefficient, and connectivity measure. The analysis revealed that two clusters provided the best separation: Cluster 1 includes most provinces with medium to low multi-hazard risk, while Cluster 2 consists of West Java, Central Java, and East Java, which have high hydrometeorological risk. This hybrid SOM and K-Means approach successfully identifies the spatial patterns of disaster risk and can serve as a reference for the government in formulating region-based mitigation strategies.
Statistical Downscaling Modeling with Time Lag Components for Forecasting Rainfall in Wet and Dry Seasons Meyliana, Sitti Masyitah; Mar'ah, Zakiyah; Hafid, Hardianti
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 03 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm180

Abstract

Climate change in Indonesia often poses a serious threat to the agricultural sector. The impacts can include reduced agricultural productivity. In this context, rainfall variables are frequently used in research related to the impacts of climate change. In this study, precipitation data from the global circulation model (GCM) outputs are used as predictor variables and rainfall data from the Indramayu station are used as response variables in statistical downscaling modeling. The cross-correlation function between these variables plays an important role in statistical downscaling modeling. The cross-correlation function can enhance the correlation between predictor variables and response variables. Therefore, this research aims to compare the rainfall prediction results using initial GCM data (GCM) and GCM data with lag components (lagged GCM) determined based on the cross-correlation function. The methods used in statistical downscaling modeling are partial least squares regression (PLSR) and principal component regression (PCR). The modeling results using data from the period 1993-2020 show that the PLSR model on lagged GCM data is the best compared to other models (PLSR on GCM data, PCR on GCM data, and PCR on lagged GCM data). This model produces the highest coefficient of determination and the smallest RMSE value. Furthermore, the PLSR model on lagged GCM data can predict the 2008 rainfall data, following the actual rainfall pattern with the smallest RMSEP value. In general, modeling using lagged GCM data provides better rainfall prediction results compared to GCM data
Akurasi Model Prediksi Menggunakan Metode Automatic Clustering Fuzzy Time Series pada Indeks Harga Konsumen di Kota Makassar Arisandi, Arwini; Hafid, Hardianti
Journal of Mathematics: Theory and Applications Vol 6 No 1 (2024): Volume 6, Nomor 1, 2024
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v6i1.3621

Abstract

Indeks Harga Konsumen (IHK) adalah sebagai alat pengukuran yang digunakan untuk memantau perubahan harga barang dan jasa yang dibeli oleh rumah tangga konsumen dalam suatu periode waktu tertentu. Informasi IHK ini merupakan alat ukur yang digunakan oleh Badan Pusat Statistik (BPS) untuk mengetahui nilai inflasi pada suatu periode tertentu sehingga memprediksikan IHK dapat mengontrol laju inflasi di suatu daerah. Oleh karena itu, penelitian ini bertujuan untuk mengetahui akurasi model prediksi menggunakan metode Automatic Clustering Fuzzy Time Series pada IHK di Kota Makassar. Akurasi model prediksi diukur melalui nilai mean square error (MSE) dan mean absolute percentage error (MAPE). Data sekunder diperoleh dari BPS dengan rentang waktu Januari 2020 hingga November 2023. Hasilnya menunjukkan bahw nilai MSE yang diperoleh adalah 0,059 dan nilai MAPE sebesar 0,154%. Hal ini menunjukkan bahwa nilai MAPE berada pada rentang <10% yang disimpulkan bahwa kemampuan metode Automatic Clustering Fuzzy Time Series sangat baik dalam memprediksikan IHK di Kota Makassar.
Klasifikasi Penggunaan Teknologi Pada Petani Milenial di Sulawesi Selatan Menggunakan Density Based Spatial Clustering Algorithm With Noise Hafid, Hardianti; Arisandi, Arwini
Journal of Mathematics: Theory and Applications Vol 6 No 1 (2024): Volume 6, Nomor 1, 2024
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v6i1.3623

Abstract

This research examines the use of agricultural technology by millennial farmers in South Sulawesi Province by applying the Density-Based Spatial Clustering Algorithm with Noise (DBSCAN) to the agricultural census data of South Sulawesi Province Phase 1 in 2023. The secondary data used includes the number of millennial farmers aged 19-39 who use or do not use digital technology, divided by district/city and gender. The analysis process begins with preprocessing to prepare the data, followed by clustering using the DBSCAN algorithm, determining the optimal values for the Eps and minPts parameters, and evaluating the quality of the formed clusters using the silhouette coefficient and elbow method. The results of the study indicate that the combination of Eps value of 1.000 and minPts value of 7 produces optimal clustering with 2 clusters formed and 92 data points clustered, while 4 other data points are considered as noise. Evaluation using the silhouette coefficient and elbow method also indicates that the optimal data grouping is k=2.
Pelatihan Pembuatan Media Pembelajaran Interaktif Bagi Guru SMA Negeri 7 Takalar Hafid, Hardianti; Nusrang, Muhammad; Fahmuddin, Muhammad; Rahmanda, Lalu Ramzy
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2025): Oktober
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/smart.v5i2.75904

Abstract

Kegiatan Pengabdian kepada Masyarakat ini dilaksanakan di SMA Negeri 7 Takalar bertujuan untuk meningkatkan kompetensi guru dalam pembuatan media pembelajaran interaktif berbasis teknologi digital. Fokus utama kegiatan adalah pelatihan penggunaan platform Wordwall, yang memungkinkan guru menciptakan media ajar berbentuk kuis dan permainan edukatif. Metode pelaksanaan meliputi sosialisasi, pelatihan interaktif, praktik langsung, serta diskusi terbuka. Kegiatan ini diikuti oleh 25 guru dari berbagai mata pelajaran, serta mendapat dukungan penuh dari kepala sekolah. Hasil kegiatan menunjukkan bahwa para peserta sangat antusias dan mulai mampu mengembangkan media ajar yang lebih menarik dan relevan dengan kebutuhan pembelajaran masa kini. Kegiatan ini diharapkan dapat menjadi langkah awal menuju transformasi digital dalam proses pembelajaran di sekolah mitra.
Nonparametric Model For Poverty Data: The Effect of Internal Factors Using Multi-Predictor Spline Regression in Indonesia Ruliana; Hidayat, Rahmat; Hardianti Hafid; Sudarmin
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60319

Abstract

Poverty, as a multidimensional issue affecting national welfare and development, is the main focus of this research. This study investigates the impact of demographic and educational factors on the percentage of the poor population in Indonesia using a nonparametric Spline regression approach. The variables studied include the average population growth rate, the availability of schools in villages, and school enrollment rates. The best model, selected based on the lowest Generalized Cross Validation (GCV) value (0.204) and a high coefficient of determination (94.67%) is a nonparametric Spline regression model with an optimal combination of knot points. The analysis shows that all three predictor variables significantly influence the poverty rate. The model also meets standard statistical assumptions. These findings highlight the vital role of education and demographic factors in addressing poverty, thus strengthening education and controlling population growth should be a priority in poverty alleviation policies in Indonesia.
KLASIFIKASI CURAH HUJAN DI KOTA MAKASSAR MENGGUNAKAN GRADIENT BOOSTING MACHINE (GBM) Hafid, Hardianti; Rais, Zulkifli; Rezky, Akhmad Rezky Ramadhana T
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 2 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm386

Abstract

Rainfall is one of the important parameters in determining the climate of an area. Makassar, as one of the largest cities in Indonesia, has varying rainfall patterns throughout the year. This research aims to classify rainfall in Makassar City using the Gradient Boosting Machine (GBM) method. The secondary data used in this study were obtained from the Meteorology, Climatology, and Geophysics Agency (BMKG), with predictor variables including wind speed, humidity, and air temperature, and the target variable being rainfall category, consisting of no rain, very light rain, light rain, moderate rain, heavy rain, and very heavy rain. To address class imbalance in the data, this study uses the Random Undersampling (RUS) technique. The GBM model with optimal hyperparameter configuration (n_estimators, learning_rate, max_depth, subsample, min_samples_leaf, max_features) achieved a classification accuracy rate of 98.46%, precision of 93%, recall of 98%, and F1-score of 95% with a training and testing data split of 80:20. The research results show that the GBM method is able to classify rainfall very well and can be used as a tool to assist in disaster mitigation planning and water resource management in Makassar City. 95% pada proporsi data pelatihan dan pengujian 80:20. Hasil penelitian menunjukkan bahwa metode GBM mampu mengklasifikasikan curah hujan dengan sangat baik dan dapat digunakan sebagai alat bantu dalam perencanaan mitigasi bencana serta pengelolaan sumber daya air di Kota Makassar.
Sosialisasi Penggunaan Media Video Animasi Powton Guru SD Inpres 3/77 Panyili Kecamatan Palakka Kabupaten Bone Abd. Hafid; Awaluddin Muin; Rosmalah; Satriani DH; Hardianti Hafid
Jurnal Abdi Masyarakat Pendidikan Vol. 2 No. 02 (2025): Jurnal Abdi Masyarakat Pendidikan
Publisher : Jurusan Pendidikan Guru Sekolah Dasar Kampus VI Bone

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this Community Service Program is to improve the pedagogical competence of teachers.. The target of the socialization on the use of Powtoon animated video media is the teachers of SD Inpres 3/77 Panyili, Palakka District, Bone Regency, as the participants. This socialization activity includes understanding the concept of Powtoon animated video media, the steps for creating Powtoon animated videos, and their use in learning. During the socialization, participants were provided with a guideline file for using Powtoon animated video media, enabling them to gain understanding and inspiration to apply it in their teaching practices. The results of the activity received positive responses from the participants because they gained knowledge about the use of animated video media and its practical application, which can help improve their pedagogical skills—particularly in designing and using Powtoon animated video media according to the learning objectives in elementary schools. This allows students to become more motivated, interested, active, and achieving. The conclusion of this activity is that participants gave positive responses regarding the practical knowledge and hands-on experience in using Powtoon animated video media, which can be utilized in learning to motivate students and enhance their interest and learning outcomes
Application of Bisecting K-Means Method in Grouping Earthquake Data (Case Study: Earthquakes in Indonesia 2023) Rais, Zulkifli; Hafid, Hardianti; Risqi, Shopia
Inferensi Vol 8, No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.23335

Abstract

Earthquakes are natural disasters that frequently occur in Indonesia, threatening the safety and resilience of its communities. This study aims to analyze the descriptive and clustering results of earthquake data in Indonesia. The data used in this study include various variables such as latitude, longitude, magnitude, and depth as the main features. The method used in this study is Bisecting K-means, and the Davies Bouldin Index test is used to determine the number of clusters. The study results indicate the formation of 3 groups, where cluster 1 falls into the deep earthquake category, cluster 3 falls into the intermediate earthquake category, and cluster 2 falls into the shallow earthquake category, with an average Davies-Bouldin Index value of 0.4758.
Co-Authors Abd. Hafid Abdul Rahman Ahmad Talib Ahmad Yasir Aras Ahmar, Ansari Saleh Arwini Arisandi Awaluddin Muin Ayu Pebriyanti Bungatang DH, Satriani Fahmuddin S., Muhammad Fahmuddin, Muhammad Fahmuddin, Muhammad Hafid, Abd. Haryono, Andri Herdawati, Herdawati Isma Muthahharah Mar'ah, Zakiyah Mar’ah, Zakiyah Meliyana R, S.Pd, M.Si, Sitti Masyitah Meliyana R, Sitti Masyitah Meyliana, Sitti Masyitah Moeh Zainal Khairul Muh. Fahmuddin Muhammad Fahmuddin S Muhammad Isbar Pratama Muhammad Nusrang Muhammad Nusrang Muhammad Yusuf Muhsin Efendi Muthahharah, Isma Muthahharah, Isma Nur Agus Salim, Nur Agus Nusrang, Muhammad Nusrang, Muhammad Rahmanda, Lalu Ramzy Rahmat H. S. Rahmat Hidayat Rais, Zulkifli Reski Wahyu Yanti Rezky Amalia Hamka Rezky, Akhmad Rezky Ramadhana T Risqi, Shopia Rosmalah Rosmalah Rosmalah Rosmalah, Rosmalah Ruliana Rustam, Sitti Nail Satriani DH Selvi Annisa Sitti Masyitah Meliyana R. Sitti Nailah Rustam Sudarmin Yati Samsyuddin Zakiyah Mar'ah Zakiyah Mar’ah Zulkifli Rais