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All Journal Jurnal Manajemen dan Organisasi Jurnal Gaussian Epsilon: Jurnal Matematika Murni dan Terapan IJIBE (International Journal of Islamic Business Ethics) Jurnal Al-Qardh Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat Inferensi Jurnal Abdimas Ekonomi dan Bisnis TIERS Information Technology Journal Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) VARIANSI: Journal of Statistics and Its Application on Teaching and Research RAGAM: Journal of Statistics and Its Application
Selvi Annisa
Department Of Statistics, Faculty Of Mathematics And Natural Science, Universitas Lambung Mangkurat, Indonesia
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Formulir Dinamis Pengusulan Standar Harga Satuan (SHS) Kabupaten Hulu Sungai Selatan Annisa, Selvi; Rahkmawati, Yeni
Jurnal Abdimas Ekonomi dan Bisnis Vol. 5 No. 1 (2025): Jurnal Abdimas Ekonomi dan Bisnis
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abdiekbis.v5i1.7297

Abstract

Badan Pengelolaan Keuangan dan Pendapatan Daerah Kabupaten Hulu Sungai Selatan mengalami kendala dalam menyusun Standar Harga Satuan karena data usulan dari Satuan Kerja Perangkat Daerah tidak disajikan secara detail. Hal ini muncul karena banyaknya data yang harus dimasukkan dan disesuaikan dengan uraian barang, kelompok barang, dan kelompok belanja. Selain itu, karena penginputan dilakukan secara manual, banyak terjadi kesalahan pengetikan. Oleh karena itu, tujuan dari kegiatan pengabdian ini adalah membuat formulir dinamis pengusulan Standar Harga Satuan di Kabupaten Hulu Sungai Selatan serta tutorial penggunaanya untuk tahun 2025. Metode pelaksanaan kegiatan adalah penerapan perangkat lunak yang dimulai dari membuat lima formulir dinamis pengisian beserta video tutorial cara pengisiannya dan diunggah ke Youtube. Formulir dinamis dan tautan youtube tersebut kemudian disebar ke seluruh Satuan Kerja Perangkat Daerah di Kabupaten Hulu Sungai Selatan. Selanjutnya Satuan Kerja Perangkat Daerah memiliki waktu satu bulan untuk mengisi usulan pada formulir yang telah dibuat secara offline (Ms. Excel) atau online (Spreadsheet). Hasil kegiatan ini menunjukkan bahwa kelima formulir tersebut dapat membantu Satuan Kerja Perangkat Daerah dalam mengusulkan Standar Harga Satuan. Sebagian besar dari mereka (95%) merasa formulir tersebut secara efektif membantu mereka dalam menyelesaikan tugas-tugas mereka. Namun, beberapa diantaranya (8.8%) menyebutkan bahwa mereka tidak mendapatkan informasi yang cukup mengenai video tutorial karena tautan video tidak sampai kepada mereka, sehingga mereka merasa video tutorial tidak membantu proses pengisian Standar Harga Satuan.
Product Development and Marketing Quality Improvement Training for Craftswomen of Purun Woven: Pelatihan Pengembangan Produk dan Peningkatan Kualitas Pemasaran bagi Pengrajin Anyaman Purun Susanti, Dewi Sri; Annisa, Selvi; Rahkmawati, Yeni; Adzim, Muhammad Fauzan; Genardi, Angelina Ivanna; Oktaviani, Viona
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 3 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i3.17063

Abstract

One of the villages in Banjarbaru has a unique handicraft product because it is made from Purun plants, a type of shrub that grows wild in swamp areas. The products made by the community around Palam Village are bags and accessories woven from Purun rat plant materials. So far, the handicraft is enough to provide additional income for housewives but has not provided optimal results because it has yet to implement a digital marketing strategy. The bag products produced are also relatively simple and have yet to be modified to gain more value in sales. This community service project aimed to train housewives in product development so they could produce Purun bag items more skillfully. Furthermore, instruction was provided on creating poster designs using the Canva software as a digital marketing tool. During the training, the artisans had the chance to try creating Purun bags by hand and creating advertising posters using their phones. The end training outcomes demonstrated that the artisans could incorporate the instruction into their creations. The assessment form revealed that the artisans were highly motivated to participate in the training and expressed hopes that conducting more of this kind of instruction in the future would be possible.
ANALISIS PENGARUH INDUSTRI MIKRO DAN KECIL TERHADAP PERTUMBUHAN EKONOMI DI INDONESIA DENGAN PENDEKATAN EKONOMETRIKA REGRESI SPASIAL DATA PANEL Jonathan Adi Winata; Fuad Muhajirin Farid; Selvi Annisa
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.v3i1.12799

Abstract

AbstractOne indicator to assess the economic condition of a country is Gross Domestic Product (GDP) at the national level or Gross Regional Domestic Product (GRDP) at the regional level. The sector that contributes the most to Indonesia's GDP is the manufacturing industry. One of the most crucial components within the manufacturing sector is the micro and small-scale industry (MSI). The presence of MSIs significantly contributes to economic development, closely tied to the geographical location among regions, thereby exerting spatial influence on the GRDP of a region. Hence, an analysis of GRDP considering spatial aspects is necessary, investigating the impact of the Micro and Small-scale Industry (MSI) sector on economic growth in Indonesia using spatial panel data regression. The spatial models constructed in this study include the Spatial Autoregressive Model (SAR) and Spatial Error Model (SEM) involving fixed-effect influence. This research aims to describe and identify the factors within MSIs that influence economic growth in each province of Indonesia. The results indicate that the appropriate model used is the Spatial Autoregressive Model Fixed Effect (SAR-FE). Overall, there are two independent variables significantly affecting economic growth, namely the number of micro and small-scale industries (X1) and inflation (X6). The results show that an increase in the percentage of these two variables will decrease the economic growth rate. Keywords:   Gross Regional Domestic Product, Economic Growth, Micro and Small Industries, Spatial Autoregressive Model Fixed Effect 
ANALISIS REGRESI ROBUST M ESTIMATOR UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI LAMA STUDI MAHASISWA S1 STATISTIKA FMIPA UNIVERSITAS LAMBUNG MANGKURAT Widawati Annisa Putri; Fuad Muhajirin Farid; Selvi Annisa
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.v3i1.12798

Abstract

Robust regression is a statistical technique commonly used to model relationships between variables by minimizing the impact of outlier data. The use of robust regression M Estimator works well when there are outliers in the data. In this study, robust regression M estimator analysis will be applied to student study period data. The aim of this research is to determine the significant factors influencing the study period of Statistics undergraduate students at the Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. The results of the research show that the residual data characteristics are not normal and there are outliers in the data. Using the Robust Regression M Estimator, the F test results show that F calculated 6.2492 > F table 2.173112, which means rejecting H0, indicating that the independent variables collectively have a significant effect on the dependent variable. From the t-test, it is known that the Guidance Process for students while working on their final project, the Employment Status of students, and the GPA of students significantly affect the Study Period of students. Keywords:   Robust Regression M Estimator, Study Period of Students, ULM
Application of Categorical Boosting Model in Classifying Diseases of Tomato Leaves Fitria Rahmah; Selvi Annisa; Dewi Anggraini
Indonesian Journal of Artificial Intelligence and Data Mining Vol. 9 No. 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

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

Abstract

Tomatoes are a strategic horticultural commodity whose productivity is often hampered by leaf diseases, particularly early blight and late blight. Manual identification through visual inspection is often inaccurate due to the similarity of symptoms between diseases. This study aims to improve the performance of tomato leaf disease classification using machine learning by overcoming the limitations of previous research by Ningsih et al., which focused solely on disease classes and did not include healthy leaf samples, thereby risking the model failing to recognize normal plant conditions. The proposed methodology integrates the VGG16 architecture as a feature extractor with the Categorical Boosting (CatBoost) algorithm as a classifier. The dataset sourced from Kaggle was cleaned and resized to 224x224 pixels, resulting in 3,285 images. The experimental results show that integrating VGG16 with CatBoost achieves good performance. The accuracy score achieved is 93.1%, while the F1 scores achieved are 90.2% (healthy leaves), 90.3% (early blight), and 98.6% (late blight). Compared to the research by Ningsih et al., this approach not only expands the scope of classification by including the healthy leaf class, but also shows better accuracy in identifying the health conditions of tomato plants.
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.
Modeling with Robust Kernel Nonparametric Regression on Childhood Stunting in Kalimantan Samsul Arifin; Selvi Annisa; Siswanto
Inferensi Vol 9 No 2 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i2.9914

Abstract

This study models stunting prevalence across 56 regencies/cities in Kalimantan using robust kernel nonparametric regression. This approach addresses the nonlinear relationship between stunting and four predictors: access to improved sanitation, low birth weight, population density, and poverty rate. An examination of influential observations using DFFITS identified five regencies as outliers; thus, the robust MM-estimator approach was applied to mitigate the influence of these extreme observations on the estimation results. Optimal bandwidth selection was performed using the Cross-Validation (CV) method across several kernel functions, namely Epanechnikov, Gaussian, and Uniform. The results demonstrated that the Uniform kernel function yielded the smallest CV value with a bandwidth combination of h1=0.6, h2=0.2, h3=0.6, and h4=0.2. The Robust Uniform Kernel model delivered the best performance, with an MSE of 2.0556, RMSE of 1.4337, MAE of 0.6581, and of 0.9510. This study indicates that robust MM-estimator kernel nonparametric regression can produce stunting prevalence estimates that are more accurate, flexible, and stable in the presence of outliers.
Co-Authors Adzim, Muhammad Fauzan Anwaril Hamidy Arifin, Samsul Dewi Anggraini Dewi Anggraini Dewi Sri Susanti Fitria Rahmah Fuad Muhajirin Farid Fuad Muhajirin Farid Genardi, Angelina Ivanna Halisa, Novia Nour Hardianti Hafid Jonathan Adi Winata Khairani, Diva Ghefira Mahardika Ma’rifa, Aulia Ma’rifah, Nurul Muhammad Azhar Norhidayati, Annisa Novia Nour Halisa Nur Salam Oktaviani, Viona Rahma Dina Nur Azizah Siswanto Siswanto Suwindi, Akhmad Tanjung, Winda Adinda Widawati Annisa Putri Yeni Rahkmawati Yuana Sukmawaty