Claim Missing Document
Check
Articles

Found 22 Documents
Search

DIGITALISASI PEMASARAN DAN REBRANDING PRODUK UMKM LEZATE JAMUR GUNUNGPATI SEMARANG MELALUI PELATIHAN, PENDAMPINGAN DAN PENERAPAN TEKNOLOGI TEPAT GUNA Herny Februariyanti; Teguh Khristianto; Esteria Priyanti
Jurnal Abdi Insani Vol 13 No 3 (2026): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v13i3.3081

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in economic development. This Community Partnership Program (CPP) aims to enhance the digital marketing capacity and brand strengthening of Lezate Jamur, an MSME located in Gunungpati, Semarang, through training, mentoring, and the application of appropriate technology. The program methods include partner needs identification, instructional material design, digital marketing training (branding, product photography, copywriting, and marketplace management), packaging and label redesign, implementation of a vacuum sealer to improve product quality, as well as operational assistance and evaluation. The evaluation was conducted using achievement checklists, pre–post understanding assessments, production logs, and digital account analytics. The results indicate that the partner was able to activate and manage digital marketing channels (Instagram, TikTok, and marketplaces), develop a more consistent brand identity (logo, color scheme, and value proposition), and improve packaging from plain plastic to informative labeled packaging. The implementation of a vacuum sealer helped maintain product cleanliness and neatness, making the products more suitable for online marketing. In terms of production, daily capacity increased from approximately 5–7 kg to 10 kg per day (an increase of about 30–40%) in line with improved workflow and rising demand. Overall, this program strengthened the MSME’s readiness to adapt to online shopping patterns and expand market reach. Future efforts should include periodic monitoring of digital channel performance and structured measurement of packaging costs, shelf life, and consumer perceptions.
Analisis Sentimen Pengguna Aplikasi Mobile JKN menggunakan Algoritma Support Vector Machine dan Naive Bayes Muhamad Bahrul Irfan; Herny Februariyanti
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4537

Abstract

The Mobile JKN application serves as the primary digital gateway developed by BPJS Kesehatan, enabling National Health Insurance participants to manage administrative needs and access health-related information remotely. Despite its widespread adoption, persistent user grievances—documented through Google Play Store reviews—signal opportunities for service refinement. This research harvested 20,000 user reviews via automated scraping (August 1–December 15, 2025) and retained 18,729 valid entries following a five-stage preprocessing pipeline encompassing cleaning, normalization, tokenization, stemming, and stopword elimination. Feature representation relied on TF-IDF vectorization, while training-set class imbalance was counteracted through SMOTE oversampling. A head-to-head evaluation pitted LinearSVC against Complement Naive Bayes across three sentiment polarities. LinearSVC emerged as the stronger classifier, registering 81.71% accuracy alongside a weighted F1-score of 0.84—surpassing its probabilistic counterpart at 79.85% accuracy and 0.83 weighted F1-score. Both architectures demonstrated robust positive-class detection (F1=0.92) yet faltered on neutral reviews, where overlapping lexical cues between praise and complaint eroded discriminative power. Wordcloud mapping further exposed recurring dissatisfaction markers ("susah", "sulit", "ribet") juxtaposed with appreciation signals ("bantu", "mudah", "bagus"), offering actionable intelligence for BPJS Kesehatan to target specific service pain points.