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Optimizing the Accuracy of Financial Reporting of Retail MSMEs Through the Development of a Web-Based Inventory Accounting Information System: A Case Study of Toserba Indah Kendal
Pratiwi, Hana
; Aqham, Ahmad Ashifuddin
; Sudirman, Bagus
; Munifah, Munifah
; Pratiwi, Hana
; Aqham, Ahmad Ashifuddin
; Sudirman, Bagus
; Munifah, Munifah
JUISI : Jurnal Ilmiah Sistem Informasi
Vol 4
, No 2
(2026)
Perkembangan teknologi informasi telah mendorong transformasi digital pada berbagai sektor usaha, termasuk usaha mikro dan menengah. Pengelolaan persediaan barang yang tidak didukung sistem informasi yang baik berpotensi menimbulkan kesalahan pencatatan, keterlambatan pelaporan, serta ketidaksesuaian data yang berdampak pada pengambilan keputusan manajerial. Toserba Indah Kendal sebagai usaha dagang masih menerapkan pencatatan persediaan dan laporan keuangan secara manual menggunakan buku tulis,...
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Pelatihan Koding dan Kecerdasan Artifisial bagi Guru SD di Sukoharjo sebagai Upaya Peningkatan Literasi Digital di Era Society 5.0
Buletin KKN Pendidikan
Vol 8
, No 1
(2026)
Era Society 5.0 menuntut penguatan literasi digital dan computational thinking sejak pendidikan dasar, namun kesenjangan kompetensi guru di daerah pedesaan masih menjadi tantangan utama dalam implementasinya. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kapasitas guru sekolah dasar dalam mengintegrasikan koding dan kecerdasan artifisial (AI) ke dalam pembelajaran sebagai upaya mendukung peningkatan literasi digital siswa. Kegiatan dilaksanakan di SDN 03 Mulur, Sukoharjo...
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Immersive Commerce: Implementasi Augmented Reality untuk Meningkatkan Kepercayaan Konsumen dalam Transaksi E-Commerce
DHARMA EKONOMI
(2026)
This study aims to describe the concept of Immersive Commerce based on Augmented Reality (AR) in increasing consumer confidence in E-Commerce transactions and to design a conceptual prototype design framework for an AR E-Commerce system with a clear technical flow. The research method uses a literature study through a comprehensive review of AR-based E-Commerce implementations and needs analysis from the perspective of consumer problems and business opportunities. The main problem identified is...
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Ekosistem Bisnis Digital: Analisis Faktor Kesuksesan UMKM Generasi Z di Indonesia
DHARMA EKONOMI
(2026)
Digital transformation has reshaped the landscape of MSMEs in Indonesia, particularly those managed by Generation Z. This study aims to analyze key success factors of Generation Z MSMEs in building sustainable digital business ecosystems. The research employs a systematic literature review methodology by analyzing various academic sources, industry reports, and related publications from 2019-2024. Findings reveal five primary success factors: adaptive digital technology adoption, high digital li...
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Attention-Augmented GRU for Stock Forecasting: A Trade-Off Between Directional Accuracy and Price Prediction Error
R. Daniel Hartanto
; Guruh Fajar Shidik
; Farrikh Alzami
; Ahmad Zainul Fanani
; Aris Marjuni
; Abdul Syukur
Journal of Computing Theories and Applications
Vol 3
, No 4
(2026)
Attention mechanisms have been widely incorporated into recurrent neural network architectures for financial time series forecasting, with most prior work reporting improvements in price-level error metrics. This study revisits that claim through a controlled empirical comparison of four deep learning architectures on nearly two decades of Telkom Indonesia (TLKM) closing price data from the Indonesia Stock Exchange (IDX). The models evaluated are a three-layer Gated Recurrent Unit (GRU) baseline...
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Behavioral Malware Detection via API Call Sequences: A Comparative Study of LSTM and Transformer Architectures Using NLP-Inspired Representations
Journal of Computing Theories and Applications
Vol 3
, No 4
(2026)
The increasing sophistication of malware has rendered traditional signature-based detection methods insufficient, necessitating behavior-driven and adaptive analytical frameworks. This study presents a sequential deep learning framework that models system-level API call sequences as structured linguistic representations for behavioral malware detection. Unlike conventional comparative studies, this work systematically evaluates recurrent and attention-based architectures under controlled experim...
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HUBUNGAN PEMBERIAN ASI EKSKLUSIF DAN MAKANAN PENDAMPING ASI DENGAN KEJADIAN STUNTING DI PERKOTAAN
Masitoh, Siti
; Syam, Heriza
; Jehanara, Jehanara
; Kusumastuti, Ani
; Debbiyantina, Debbiyantina
; Aulani, Fitria
Jurnal Kesehatan Masyarakat Indonesia
Vol 21
, No 1
(2026)
Latar Belakang: Masalah kesehatan gizi yang signifikan di Kota Serang adalah prevalensi stunting. Asupan gizi, khususnya ASI eksklusif dan makanan tambahan, berdampak signifikan terhadap pertumbuhan balita dan merupakan faktor penyebab stunting. Tujuan: Untuk menguji korelasi antara ASI eksklusif dan makanan pendamping, bersama dengan usia ibu, pendidikan, pekerjaan, dan paritas, dengan prevalensi stunting di wilayah Puskesmas Singandaru, Kota Serang. Metode: Penelitian ini menggunakan pendekata...
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Antagonistic activity of phyllosphere fungi isolated from medicinal plants against Colletotrichum sp. causing anthracnose in chilli (Capsicum annuum L.)
Anthracnose disease caused by the fungus Colletotrichum sp. is one of the main problems in chili cultivation (Capsicum annuum L.) and can cause significant yield losses. The intensive use of chemical pesticides in controlling this disease has a negative impact on the environment and health. This study aimed to evaluate the antagonistic potential of phyllosphere fungi isolated from five medicinal plants, namely Phaleria macrocarpa, Curcuma domestica, Kleinhovia hospita, Hibiscus rosa-sinensis, an...
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Evaluating Civil Servant Selection through Machine Learning Analysis of National Insight, General Intelligence, and Personal Characteristics Test Scores
This study analyzes the score distribution of 2,490 candidates in the 2024 Ministry of Finance Public sector recruitment, focusing on the CNI, GIT, and PCT sections using machine learning classification. Models used include Logistic Regression (accuracy 0.7897), Random Forest (0.9779), and XGBoost (0.9809), all trained with default parameters (n_estimators=100, max_depth=None) and evaluated using accuracy, precision, recall, and F1-score. While ensemble models outperformed Logistic Regression, t...
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Viscosity Modeling of MES and SLS Using Machine Learning Method
Fathaddin, Muhammad Taufiq
; Setiati, Rini
; Akbar, Fahrurrozi
; Sumirat, Iwan
; Bharoto
; Ramadhan, Ranggi Sahmura
; Onnie Ridaliani Prapansya
; Ristawati, Arinda
Viscosity is crucial to improve the efficiency of injected fluids for oil displacement in reservoirs. Traditionally, research has focused on polymers that help reduce the mobility of injected fluids, while surfactant viscosity has received less consideration. This research investigated the viscosity behavior of methyl ester sulfonate (MES) and sodium lauryl sulfate (SLS) surfactant solutions using a machine learning method—adaptive neurofuzzy inference system (ANFIS). This study aimed to predict...
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