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All Journal Epsilon: Jurnal Matematika Murni dan Terapan AKSIOMA: Jurnal Program Studi Pendidikan Matematika Jurnal Fisika FLUX Info-Teknik Jurnal Agro Industri Perkebunan Desimal: Jurnal Matematika Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat Anterior Jurnal Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Pendidikan Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Pengabdian Masyarakat Aufa (JPMA) Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) VARIANSI: Journal of Statistics and Its Application on Teaching and Research Proceeding National Conference Business, Management, and Accounting (NCBMA) Jurnal Sistem Informasi, Akuntansi dan Manajemen RAGAM: Journal of Statistics and Its Application
Dewi Sri Susanti
Department Of Statistics, Lambung Mangkurat University, Banjarbaru
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) PADA DATA INDEKS HARGA KONSUMEN (IHK) 5 IBUKOTA PROVINSI DI PULAU KALIMANTAN Muhammad Aldi Relawanto; Yuana Sukmawaty; Dewi Sri Susanti
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.11427

Abstract

Generalized Space Time Autoregressive (GSTAR) model is a development model from the generalized STAR (Space Time Autoregressive) model. GSTAR model have autoregressive order to see the effect of the time element and location weighting matrix to see the effect of the location element. Unlike the STAR model, it can assume that each location research has different characteristics. The purpose of this research is to apply the Generalized Space Time Autoregressive (GSTAR) model to the Consumer Price Index (CPI) data in Kalimantan Island, especially in the capital city of each province in Kalimantan Island to find out the best estimation model with the best location weight. The location weights used the distance inverse location weights and the normalized cross-correlation location weights by estimating the parameters of the GSTAR model using the Ordinary Least Square (OLS) method. The best estimated model can be seen from the smallest Akaikae’s Information Criterion (AIC) and Root Mean Square Error (RMSE) value. From the research results, it was found that the best GSTAR prediction model for CPI data for 5 cities in Kalimantan Island was the GSTAR(1,1)-I(1). These results are based on the GSTAR prediction model with the smallest AIC value and the data is differencing 1 time. The best location weight based on the smallest RMSE value for the GSTAR(1,1)-I(1) model is the normalized cross-correlation location weight.
SPATIAL ANALYSIS OF THE RELATIONSHIP BETWEEN HUMAN DEVELOPMENT INDEXES AND ITS DETERMINANT FACTORS IN SOUTH KALIMANTAN PROVINCE: COMPARISON OF SPATIAL REGRESSION MODELING Juhar Latifah; Dewi Sri Susanti
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.11608

Abstract

Indeks Pembangunan Manusia (IPM) berfungsi sebagai metrik penting yang mencerminkan tingkat kesejahteraan suatu wilayah melalui dimensi kesehatan, pendidikan, dan pendapatan. Dalam upaya untuk memahami lebih lanjut mengenai faktor-faktor yang mempengaruhi IPM, penelitian ini fokus pada Keparahan Tingkat Kemiskinan (X1), Kepadatan Manusia Penduduk (X2), dan Angka Partisipasi Kasar (X3) sebagai variabel kunci yang mungkin berdampak pada pembangunan, khususnya di provinsi Kalimantan Selatan. Metode yang digunakan meliputi regresi klasik, gabungan regresi spasial, dan model kesalahan spasial. Model ketiga ini akan dibandingkan dan ditentukan model dengan kinerja terbaik. Berdasarkan temuan penelitian, Structural Equation Model (SEM) muncul sebagai model yang paling efektif dalam menganalisis faktor-faktor yang mempengaruhi IPM di Kalimantan Selatan. Nilai R-square yang diperoleh sebesar 0,8946 menunjukkan tingkat daya penjelas yang tinggi, melampaui nilai R-square model lainnya.
ANALISIS MODEL LOGIT KUMULATIF UNTUK MENENTUKAN DETERMINAN USIA KAWIN PERTAMA WANITA DI KABUPATEN BALANGAN Aulia Syifa Annisa; Dewi Sri Susanti
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.10518

Abstract

The Province of South Kalimantan is one of the five provinces in Indonesia with the highest teenage marriage rate from 2017 to 2020.  Based on 13 South Kalimantan regencies/cities, it is known that Balangan Regency has the greatest percentage of women's age at first marriage under 19 years compared to other regencies/cities, which is 55.58%. The purpose of this study is to identify the factors that influence women's age at first marriage in Balangan Regency in 2020. In this investigation, ordinal logistic regression with the cumulative logit model was used.  The findings revealed that the highest education ever/currently obtained by a woman (X1), parents' age at first marriage (X2), the highest diploma of the head of the household (X3), employment status of the head of the family (X4), location of place of residence (X5), poverty status (X6), and migration (X7) had no significant effect.  Furthermore, using the Spearman rank correlation coefficient, it was discovered that the highest education ever/currently obtained by a woman  (X1) has a substantial correlation/closeness of link with women's age at first marriage by 28%.  Women with a higher degree of education are less likely to marry at a young age, whereas women with a lower level of education are more likely.
PEMODELAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION (GWNBR) PADA KEJADIAN STUNTING DIiKABUPATEN BARITO KUALA TAHUN 2022 Azkia Azkia; Dewi Sri Susanti
RAGAM: Journal of Statistics & Its Application Vol 3, No 1 (2024): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v3i1.12796

Abstract

Stunting is a condition of malnutrition in toddlers that causes their height to be lower than other children their age. In 2022, South Kalimantan Province has a stunting prevalence of 24.6% and ranks fifteenth in Indonesia. Barito Kuala Regency, one of the regions in South Kalimantan Province, has the highest stunting rate at 33.6% which is included in the Chronic- Acute category (≥ 20%). This study uses the GWNBR model to characterize the factors that cause stunting in Barito Kuala Regency. The GWNBR model will make it easier for researchers to find out the factors that affect stunting in each sub-district. The weight matrix used is a fixed kernel function and an adaptive kernel function. The predictor variables used were the percentage of infant history of complete basic immunization, history of exclusive breastfeeding in infants <6 months, history of low birth weight babies, new visits to pregnant women (K1), sixth antenatal care (ANC) visit (K6), history of pregnant women who received blood supplement tablets, history of infants 6-11 months who received vitamin A, active posyandu and households with access to appropate sanitary facilities.(healthy latrines). The best model results obtained with adaptive gaussian weighting with an AIC value of 167.25. Keywords: Stunting Cases, GWNBR model.
PEMODELAN REGRESI SPASIAL PADA ANGKA PARTISIPASI MURNI JENJANG PENDIDIKAN SMA SEDERAJAT DI PROVINSI KALIMANTAN SELATAN Suci Anshari; Dewi Sri Susanti; Fuad Muhajirin Farid
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7318

Abstract

This research is done for modeling of the Pure Enrolment Rate (PER) at the senior high school level in South Kalimantan Province that uses analysis of spatial regression. The purpose of this analysis is to construct the modeling of spatial regression of the Pure Enrolment Rate (PER) at the senior high school level in South Kalimantan Province and to identify the significant factors that influent the pure enrollment rate (PER). The result of this research shows that the modeling of spasial regression is suitable for use in the Pure Enrolment Rate (PER) at the senior high school level in South Kalimantan Province in 2017 – 2019 is the Spatial Autoregressive Model (SAR). The model form can be seen that in 2017 there is no significant influence factors to the PER, in 2018 the ratio of the student number to the school number (X5) and the ratio of the student number to the teacher number (X6) that are the influence factors significantly to the Pure Enrollment Rate (PER), while in 2019 only the factor of the ratio of the students number to the schools number (X5 ) that influents significantly to the PER.Keywords:   PER, Education, and Spatial Regression Analysis
PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) MENGGUNAKAN PEMBOBOT KERNEL PADA KASUS TINGKAT PENGANGGURAN TERBUKA DI KALIMANTAN Viona Oktafiani; Dewi Sri Susanti; Yeni Rahkmawati
RAGAM: Journal of Statistics & Its Application Vol 3, No 1 (2024): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v3i1.12822

Abstract

AbstractUnemployment is one of the serious problems in Indonesia's economic development. This unemployment describes human resources that have not been utilized optimally, as a result of which people's productivity and income have not been maximized, this can also be one of the causes of poverty and other social problems. This study aims to find out the general picture of the open unemployment rate in the Kalimantan region, get the best model and factors that influence the open unemployment rate and illustrate it through thematic maps. The study began with testing assumptions and spatial effects then continued with testing global regression modeling and Geographically Weighted Regression. The weighting function used in this study is adaptive gaussian kernel. The variable that has a positive effect on the open unemployment rate in the Kalimantan region is population density. While the variable that negatively affects the open unemployment rate is the Labor Force Participation Rate. Keywords:   Open Unemployment Rate, Kalimantan Island, Spatial, GWR
Peningkatan Kesadaran Masyarakat dalam Pencegahan Stunting melalui Program Skalting (Lokasi: Posyandu Kelurahan Palam Banjarbaru) Salam, Nur; Dewi Sri Susanti; Dewi Anggraini; Selvi Annisa; Maisarah; Rifqi Aulia Rahman; A. Fahmi Indra Yani; Ahmad Helmi Yasir; Nayla Aisha Saydina; Aulia Naylan Muna; Dina Musyarafah
Jurnal Pengabdian Masyarakat Aufa (JPMA) Vol. 8 No. 1 (2026): Vol 8 No. 1 April 2026
Publisher : Universitas Aufa Royhan Di Kota Padangsidipuan

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Abstract

ABSTRAK Kondisi stunting pada balita merupakan terjadinya kegagalan pertumbuhan akibat akumulasi minimnya nutrisi. Program Pusat Pelayanan Terpadu (Posyandu) merupakan salah satu program pemerintah untuk meningkatkan partisipasi masyarakat dalam menjaga kesehatan khususnya ibu dan balita. Program pengabdian masyarakat ini dilaksanakan di Posyandu Teratai, Kelurahan Palam, yang selama ini rutin melakukan pemeriksaan kesehatan balita sebatas pengukuran antropometri dan imunisasi. Inisiatif ini bertujuan untuk meningkatkan kesadaran dan kewaspadaan ibu terkait masalah gizi buruk pada anak. Kegiatan pengabdian ini dilaksanakan untuk peningkatan kesadaran masyarakat dalam mencegah stunting melalui program SKALTing (sosialisasi, konseling dan aksi lapangan untuk stunting). Kegiatan pengabdian masyarakat ini meliputi penyuluhan gizi mengenai stunting serta pelaksanaan pengukuran antropometri (tinggi/panjang dan berat badan) bayi dan balita di Posyandu. Target audiens dari inisiatif ini adalah para ibu yang memiliki bayi dan balita di wilayah Kelurahan Palam. Berdasarkan hasil kegiatan, evaluasi dan observasi kegiatan ini berhasil mencapai indikator keberhasilan yang ditetapkan, terlihat dari tingkat partisipasi yang sesuai target dan antusiasme peserta yang signifikan selama pelaksanaan kegiatan, serta adanya peningkatan pemahaman peserta terkait stunting.
NAVIGATING GREY ZONES: INTEGRITY VULNERABILITIES IN REGIONAL GOVERNANCE Rifqi Novriyandana; Iwan Alfanie; Sunardi; Reja Fahlevi; Dewi Sri Susanti; Arif Rahman Hakim; Muhammad Baqir; Muhamad Rafli
Proceeding National Conference Business, Management, and Accounting (NCBMA) 9th National Conference Business, Management, and Accounting
Publisher : Faculty of Economics and Business Universitas Pelita Harapan

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Abstract

Formal integrity systems often fail to produce ethical outcomes in decentralized bureaucracies, giving rise to what this study conceptualizes as an "integrity paradox." This research investigates the structural and cultural vulnerabilities within Indonesian local governments that contribute to internal control failures. Using a qualitative case study approach, the study analyzes data from the Integrity Assessment Survey (SPI) and conducted in-depth interviews with internal and external stakeholders in South Kalimantan. The findings indicate that although formal anti-corruption instruments are technically in place, they are systematically undermined by "grey zone" practices, including normalized informal interventions and a pervasive culture of silence driven by fear of retaliation. The study further demonstrates that internal oversight functions, such as the Inspectorate, tend to be reactive rather than proactive. These findings suggest that strengthening public sector integrity requires moving beyond administrative compliance toward the institutionalization of whistleblower protection mechanism and audit-based early warning systems.
Waste Identification Using a Hybrid Convolutional Neural Network and Vision Transformer on Visually Heterogeneous Images Muhammad Fauzan Adzim; Dewi Sri Susanti; Sigit Dwi Prabowo
Indonesian Journal of Artificial Intelligence and Data Mining Vol. 9 No. 2 (2026): July 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

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Abstract

In image classification, convolutional neural networks (CNNs) focus on local patterns, whereas vision Transformers (ViTs) emphasize global context. Combining the two in a hybrid CNN-ViT model may yield a more comprehensive image representation. Waste image classification with visually heterogeneous characteristics can be used to effectively evaluate the performance of the hybrid CNN-ViT model. In addition, such classification supports the crucial need for accurate waste-type identification to enable effective waste management systems. This study investigates a hybrid CNN-ViT model for classifying 24705 organic and recyclable waste images. The workflow involves resizing, an 80:10:10 split, and data augmentation, with models trained for 50 epochs using BCE loss and the Adam optimizer. Evaluation is conducted at the best epoch, defined as the epoch with the highest validation accuracy. For comparison, CNN and ViT models are also trained and evaluated separately. On the test set, the hybrid CNN-ViT model achieves an accuracy of 91.54%, the CNN achieves 91.78%, and the ViT achieves 87.17%. These findings show that CNNs provide an effective and efficient baseline, while the hybrid CNN-ViT model delivers performance competitive with CNNs and is worth considering as a robust alternative for image-based waste classification tasks.
PREDIKSI INDEKS HARGA KONSUMEN KELOMPOK BAHAN MAKANAN DI PROVINSI KALIMANTAN SELATAN Rahma Dina Nur Azizah; Dewi Sri Susanti; Selvi Annisa
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 18, No 1 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i1.9814

Abstract

Inflation is a phenomenon that shows a continuous increase in the price of goods, which can cause a decline in the economic condition of a country. One of the indicators used to measure the inflation rate is the Consumer Price Index (CPI). By knowing the CPI value earlier, food prices can be controlled to be more stable. One method that can be used to predict CPI is Support Vector Regression (SVR), where this method is able to overcome linear and non-linear data conditions. This research aims to get the best prediction for CPI in South Kalimantan Province using CPI data for food groups in Tanjung, Banjarmasin, and Kotabaru in the 2014-2022 range. The best prediction results are obtained through the SVR method with Linear Kernel. The prediction error value measured through the MAPE value for Tanjung, Banjarmasin and Kotabaru is 0.77%,  and . While the size of the meaning of the model measured through the coefficient of determination, respectively 0.8826,  and . Based on these values, it is concluded that the prediction model formed is very good and feasible. The prediction results for the next 12 months show an increase, so that the government and related parties can formulate policies such as market operations and subsidy programs for the community.
Co-Authors A. Fahmi Indra Yani Adzim, Muhammad Fauzan Ahmad Helmi Yasir Ahmad Yusuf Akbar, Arief Rahmad Maulana Al Hujjah Asianingrum Anggraini, Dewi Arfan Eko Fahrudin Arfan Ikhsan, Arfan Arif Rahman Hakim Arifin, Samsul Aulia Naylan Muna Aulia Syifa Annisa Az Zahra, Aisyah Nur Azkia Azkia Badruzsaufari Badruzsaufari Bizaini Bizaini Budi Kristanto Chairil Fachrurazie Challen, Auliffi Ermian Dewi Anggraini DEWI ANGGRAINI Dewi Anggraini Dian Handiana Dian Handiana Dina Musyarafah Dini Hidayati Eko Suhartono Elmanizar, Elmanizar Etza Budiarti Febriani, Arika Fitriadi Fitriadi Fuad Muhajirin Farid Fuad Muhajirin Farid Genardi, Angelina Ivanna Geofani Setiawan Geofani Setiawan Hijriati, Naimah Hindarto, Imam Iwan Alfanie Izafera, Anis Huzaimanor Jainal Jainal Juhar Latifah Karim Karim Krisdianto Krisdianto Krisdianto Sugiyanto Lalu Rudyat Telly Savalas Lestia, Aprida Siska Maisarah Maisarah Maisarah, Maisarah Manik, Tetti Novalina Muchamad Arief Soendjoto Muhamad Rafli Muhammad Ahsar Karim Muhammad Aldi Relawanto Muhammad Baqir Muhammad Fauzan Adzim Muhammad Meidy Maulana Muhammad Reza Faisal, Muhammad Reza Muhammad Saufi Mustika Khadijah Nayla Aisha Saydina Nila Cahya Noor Baitirahmah Noordyanti, Erna Nooriman, Raihan Nur Salam Nur Salam Nur Salam Nurul huda NURUL QOMARIYAH Oktaviani, Viona Oni Soesanto oni Soesanto Pamona Dwi Rahayu Prabowo, Sigit Dwi Rahma Dina Nur Azizah Rahman, Rifqi Aulia Rahmat Yunus Rahmi Hidayati Raihan Nooriman Raihan Nooriman Randy Toleka Ririhena Rasjava, Achmad Ramadhanna'il Reja Fahlevi Rifqi Novriyandana Riza, Yusi Rizki Fatriasi Rizqi Elmuna Hidayah Salsabilla, Rania Selvi Annisa Selvi Annisa Setiawan, Geofani Sigit Dwi Prabowo Sila Rizqina Silvi Risaria Dewi Siti Nur Hamidah Soesanto, Oni Sri Cahyo Wahjono Sri Cahyo Wahyono Sri Mulyanie Hardiyanthy Suci Anshari Sunardi Susilo, Tanto Budi Sutomo Sutomo Syamsiar, Syamsiar Thaibatun Nissa Thresye Thresye Thresye,, Thresye, Tiara Aninditha Tiara Elma Uthami, Mariza Viona Oktafiani Yeni Rahkmawati Yuana Sukmawaty Yulian Firmana Arifin Yulianti, Irma Sari Yuni Yulida Yuyun Hidayat