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ANALISIS IMPLEMENTASI STANDAR AKUNTANSI KEUANGAN ENTITAS TANPA AKUNTABILITAS PUBLIK (SAK ETAP) PADA UMKM (STUDI KASUS USAHA LADU ARAI PINANG “RANI”) Salfina, Lili; Febriani, Ayu; Oktaviani, Nichy
Ensiklopedia Sosial Review Vol 1, No 3 (2019): Volume 1 No 3 Oktober 2019
Publisher : Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33559/esr.v1i3.344

Abstract

This research aimed to know the implementation about Financial Accounting Standards Entities Without Public Accountability (SAK ETAP) of Keripik Ladu Arai Pinang “RANI” SMEs in Pariaman City. The method used in this study is qualitative approach. This research uses primary data source and secondary data source. The primary data source in the form of information and data supplied by the owner SMEs, while secondary data source are from website, and documents that support. Data collection techniques using triangulation techniques, namely the interview, documentation and observation. Data analysis techniques with data reduction, data display and conclusion. Based on the research in mind that Business Ladu Arai Pinang “RANI” SMEs have not record based SAK ETAP. Therefore, researchers have drafted of the financial statement based SAK ETAP, include balance sheet, income statement, capital statement, cash flow statement and notes of financial statement. Financial statement SMEs made the researcher based on information obtained during the research, then processed into financial statement based SAK ETAP.
Implementation of Support Vector Machine for Classifying User Reviews on the Sentuh Tanahku Application Febriani, Ayu; Khotibul Umam; Mokhammad Iklil Mustofa
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9832

Abstract

User reviews play a crucial role in the development of digital public service applications, as they reflect user satisfaction and service quality. This study aims to classify user reviews of the Sentuh Tanahku application into two sentiment categories, namely positive and negative, by applying the Support Vector Machine (SVM) algorithm. A total of 13,231 reviews obtained from Kaggle were processed through text preprocessing stages including case folding, tokenizing, stopword removal, and stemming. The TF-IDF technique was employed to convert text data into numerical vectors, followed by classification using SVM with hyperparameter tuning via RandomizedSearchCV. The evaluation results showed that the SVM model achieved an accuracy of 91% on training data and 84% on testing data. To assess its performance, the study compared SVM with baseline algorithms, namely Naïve Bayes and Logistic Regression. The comparison revealed that Logistic Regression and Naïve Bayes outperformed SVM with accuracy scores of 88.84% and 88.68%, respectively. Despite this, SVM remained competitive in maintaining balanced metrics across both classes. These findings highlight that algorithm performance in sentiment classification is highly influenced by the nature of the dataset. This study is expected to contribute as a reference for improving user opinion analysis methods in Indonesian-language public service applications.
Immunomodulatory Effects of Synbiotic Lactic Acid Bacteria from Dangke and Inulin from Dahlia Tubers Febriani, Ayu; Hafsan, Hafsan; Nur, Fatmawati; Muthiadin, Cut; Khudaer, Faten
Al Jahiz Vol 6 No 2 (2025): Al-Jahiz: Journal of Biology Education Research, July-December 2025
Publisher : Fakultas Tarbiyah dan Ilmu Keguruan UIN Jurai Siwo, Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32332/al-jahiz.v6i2.10393

Abstract

Synbiotics, the synergistic combination of probiotics and prebiotics, have attracted growing scientific interest due to their potential to modulate immune responses. However, the immunomodulatory effects of synbiotics derived from traditional foods remain underexplored. This study aimed to evaluate the immune-enhancing potential of synbiotics formulated from Lactobacillus fermentum isolated from Dangke (a traditional South Sulawesi cheese) and inulin extracted from Dahlia tubers. The novelty of this work lies in the utilization of culturally unique, locally sourced microbial and prebiotic components that have not previously been tested for immunological impact. A total of 28 mice were randomly divided into four groups: one negative control group (P0) and three treatment groups (P1, P2, P3) receiving different doses of synbiotics over a 20-day treatment period. Parameters observed included changes in body weight, macrophage phagocytosis activity, and organ indices (liver and spleen). Results showed that mice in P1 and P2 groups exhibited significant increases in body weight (P1: +12.5%, P2: +15.3%, p < 0.05) compared to the control. Moreover, macrophage phagocytic activity was markedly improved in the treatment groups (p < 0.01). Liver and spleen indices were also significantly elevated (p < 0.05), indicating enhanced organ function. These findings suggest that synbiotics containing L. fermentum and Dahlia inulin have promising immunomodulatory effects, highlighting their potential for development as novel functional food ingredients with health-promoting benefits.