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All Journal Jurnal Manajemen dan Organisasi Jurnal Gaussian Epsilon: Jurnal Matematika Murni dan Terapan CAUCHY: Jurnal Matematika Murni dan Aplikasi 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 Jurnal Kajian Ilmiah 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 International Journal of Multidisciplinary Sciences and Arts RAGAM: Journal of Statistics and Its Application
Selvi Annisa
Department Of Statistics, Faculty Of Mathematics And Natural Science, Universitas Lambung Mangkurat, Indonesia
Religion 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 Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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IMPLEMENTATION OF K-MEDOIDS AND K-PROTOTYPES CLUSTERING FOR EARLY DETECTION OF HYPERTENSION DISEASE Hafid, Hardianti; Annisa, Selvi
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/barekengvol19iss1pp465-476

Abstract

Hypertension is a serious concern because of its significant impact on public health, especially in the context of lifestyle changes and specific health conditions. One method for grouping patients based on complex clinical data is the Clustering method. This research type is quantitative, namely taking or collecting the necessary data and then analyzing it using the K-Medoids and K-Prototypes methods. The K-Medoids method is more resistant to outliers and noise than the K-Means method, which is more suitable for this research. The K-Prototypes method can handle mixed numerical and categorical data, effectively grouping hypertensive patients based on different variable categories. This research used the K-Medoids and K-Prototypes grouping methods to categorize patients into risk categories based on gender, age, family history of hypertension, smoking status, pulse rate, and increased systolic and diastolic blood pressure. The Elbow and Silhouette Coefficient methods were applied to evaluate the data and determine the optimal number of clusters for dividing patients into low-risk and high-risk hypertension groups. The analysis revealed that two clusters are the optimal solution. The clustering results show K-Medoids' superiority in grouping data with higher Silhouette Coefficient values ​​compared to K-Prototypes. Overall, the K-Medoids and K-Prototypes algorithms can detect early hypertension risk by dividing patients into different risk groups. Although the clustering results are still weak, these two methods show potential in helping health institutions identify and treat hypertension risk in Indonesia.
Studi Komparasi Sektor E-commerce pada Awal dan Akhir Pandemi Covid-19 Utami, Radias Kartika; Perdana, Muhammad Akmal; Hamda, Tazkiratul; Rahmah, Siti; Anggraini, Dewi; Annisa, Selvi
Jurnal Kajian Ilmiah Vol. 25 No. 3 (2025): September 2025
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ycm3za75

Abstract

This study examines the impact of the COVID-19 pandemic on the e-commerce sector in Indonesia by comparing its growth at the beginning and end of the pandemic. COVID-19 was first detected in Wuhan, China in December 2019 and became a global pandemic in March 2020. The pandemic affected various sectors, including the economy and business, with some sectors like e-commerce experiencing growth. This study uses a quantitative method with secondary data from "E-commerce Statistics 2020" and "E-commerce Statistics 2022" published by BPS. Data shows a significant increase in the number of e-commerce businesses, from 2,361,423 in 2020 to 2,995,986 in 2022. Correlation analysis and t-tests indicate a strong positive relationship and a significant difference in the number of e-commerce businesses between these periods. This study provides insights into the development of the e-commerce sector during the pandemic and aids stakeholders in making decisions in the post-pandemic era.
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.
HYBRID METHOD IMPLEMENTATION: FUZZY DECISION TREE IN THE CLASSIFICATION OF GENDER INEQUALITY Irawan, Siti Fatimah Marliany; Anggraini, Dewi; Annisa, Selvi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0509-0522

Abstract

The classification of continuous data using the C4.5 decision tree algorithm requires prior discretization based on the calculation of cut points, a process that can be time-consuming and potentially introduce bias. These limitations may negatively impact both the computational efficiency and the classification accuracy of the decision tree model. This study proposes a hybrid method that integrates fuzzy logic with decision tree techniques in the classification process of continuous data types. Fuzzy logic is utilized to manage uncertainty in data variables and enhance flexibility in processing continuous values, while the decision tree plays a role in providing a structured and rule-based framework for decision-making. This proposed method is applied to gender inequality data, encompassing aspects of reproductive health, education and empowerment, and employment across 166 countries worldwide. The results demonstrate that the fuzzy decision tree method, which was constructed using the C4.5 algorithm, achieved a classification accuracy of 91%, while the C4.5 decision tree method without fuzzy only achieved a classification accuracy of 77%. The fuzzy decision tree method successfully improved the classification accuracy by 14%. Additionally, the fuzzy decision tree exhibited more stable and balanced performance in classifying data into four target categories. Therefore, this approach offers an effective and comprehensive alternative for classifying gender inequality, with the potential to support data-driven and targeted policy-making.
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
Role of Motivational Content on Instagram in Enhancing Generation Z’s Self-Esteem: An Empirical Analysis Rahkmawati, Yeni; Anggraini, Dewi; Sukmawaty, Yuana; Annisa, Selvi; Al Fajrin, Muhammad Agha Putra; Putri, Dwi Cahyaning; Ananda, Saira Aulia; Nabilah, Dwi Anisatun
International Journal of Multidisciplinary Sciences and Arts Vol. 5 No. 1 (2026): International Journal of Multidisciplinary Sciences and Arts, Article January 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v5i1.7810

Abstract

Generation Z (Gen Z) is a generation that grew up in the digital era with intensive use of social media, including Instagram. As the largest user group, Gen Z consumes a wide range of influencer-generated content, including motivational content that may affect psychological well-being, particularly self-esteem. However, empirical studies specifically examining the influence of motivational content from Instagram influencers on Gen Z’s self-esteem remain limited. This study aims to analyze Gen Z’s interest in motivational content on Instagram and to examine changes in self-esteem before and after exposure to such content. A quantitative approach using a quasi-experimental one-group pretest–posttest design was employed. The sample consisted of 150 university students in Banjarbaru City selected through purposive sampling. Data were collected using the Rosenberg Self-Esteem Scale (RSES) administered via questionnaires. The Wilcoxon Signed-Rank Test was used to analyze differences in self-esteem scores before and after treatment. The results indicate a significant increase in self-esteem following exposure to motivational content on Instagram. The average post-treatment self-esteem score was higher than the pre-treatment score, confirming the positive impact of motivational content. In addition, although most respondents reported only occasional exposure to motivational content, the majority expressed liking and interest in such content. These findings suggest that motivational content on Instagram contributes positively to enhancing Gen Z’s self-esteem and may serve as an effective medium for psychological empowerment.
Comparison of ARIMA, Random Forest, and Hybrid ARIMA-Random Forest Models in Forecasting Indonesian Crude Oil Prices Rahkmawati, Yeni; Annisa, Selvi; Hafid, Hardianti; Nuramaliyah, Nuramaliyah; Safitri, Emeylia
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.36540

Abstract

The price of Indonesian crude oil is highly volatile due to global demand fluctuations, energy policies, and geopolitical tensions, making accurate forecasting challenging. This study compares three forecasting models: ARIMA, Random Forest, and Hybrid ARIMA--Random Forest, to identify the most accurate approach. Model performance was evaluated using Time-Series Cross-Validation (TSCV) and metrics including Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). The results indicate that the Random Forest model, tuned with \texttt{mtry = 1} and \texttt{ntree = 200}, outperformed both ARIMA and Hybrid ARIMA--Random Forest, achieving the lowest MAPE, MAE, and RMSE values. This suggests that Indonesian crude oil prices during the study period are predominantly non-linear, and Random Forest alone effectively captures these dynamics. Forecasts based on this model indicate a short-term increase in prices from 61.10 USD/Barrel in December 2025 to 64.29 USD/Barrel in March 2026, followed by a slight decline and modest recovery by June 2026. Overall, Random Forest provides a reliable and accurate tool for forecasting Indonesian crude oil prices, offering valuable insights for policymakers, investors, and market participants navigating volatile oil markets.
Application of Categorical Boosting Model in Classifying Diseases of Tomato Leaves Rahmah, Fitria; Annisa, Selvi; Anggraini, Dewi
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 | DOI: 10.24014/ijaidm.v9i1.38869

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.
Co-Authors Adzim, Muhammad Fauzan Al Fajrin, Muhammad Agha Putra Ananda, Saira Aulia Anwaril Hamidy Azizah, Rahma Dina Nur Dewi Anggraini Dewi Anggraini Dewi Sri Susanti Fuad Muhajirin Farid Fuad Muhajirin Farid Genardi, Angelina Ivanna Halisa, Novia Nour Hamda, Tazkiratul Hardianti Hafid Irawan, Siti Fatimah Marliany Jonathan Adi Winata Khairani, Diva Ghefira Mahardika Ma’rifa, Aulia Ma’rifah, Nurul Muhammad Azhar Nabilah, Dwi Anisatun Norhidayati, Annisa Novia Nour Halisa Nur Salam Nuramaliyah, Nuramaliyah Oktaviani, Viona Perdana, Muhammad Akmal Putri, Dwi Cahyaning Rahmah, Fitria Safitri, Emeylia Sembiring, Rinawati Sukmawaty, Yuana Suwindi, Akhmad Tanjung, Winda Adinda Utami, Radias Kartika Widawati Annisa Putri Yeni Rahkmawati Yuana Sukmawaty