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All Journal Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika Madani : Indonesian Journal of Civil Society Edu Komputika Journal
Zanuar Rifa’i
Universitas Amikom Purwokerto
Humanities Computer Science & IT Education

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Rancang Bangun Aplikasi Perpustakaan Berbasis Android Menggunakan Mit App Inventor Indra Kusuma Wardani; Zanuar Rifa’i
Infoman's : Jurnal Ilmu-ilmu Manajemen dan Informatika Vol. 15 No. 1 (2021): Infoman's
Publisher : STMIK Sumedang

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

Abstract

An Android-based library information system is something that is no wonder anymore in the world of education or the workforce.Android itself is a very popular platform in the current century.In the advancement of a technology, therefore the library as a window of the world requires Android to improve a performance of its operation to get the results achieved.Similarly, the village of Klaces in the operation of the library is still a lot of problems arising to require a settlement process, because the library is obliged to present accurate information precisely and can provide its own satisfaction for workers and visitors.Klaces Village is one of the government in Kampung Laut Sub-district and is located in Cilacap Regency.Currently the government of Klaces village already has a library that has been utilized by various school communities and other institutions that are located adjacent to Klaces Village office which is still in the form of manual, so it needs an Android-based library information system that can later help in the operation of the software.The result of this research is to produce a library application with several other features, book stock, List of visitors, book borrowing, book returns and stock procurement of books.In designing the library system using app inventor application and using System method Extreme Programming
Pelatihan Digital Marketing dan Optimasi SEO Pada Marketplace Pada Sentra Umkm Banyumas Untuk Memaksimalkan Pemasaran Produk Secara Online Zanuar Rifa’i; Luzi Dwi Oktaviana
Madani : Indonesian Journal of Civil Society Vol. 2 No. 1 (2020): Madani, Februari 2020
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v2i1.99

Abstract

Micro, Small and Medium Enterprises (MSMEs) have an important and strategic role in national economic development. In addition to playing a role in economic growth and employment, MSMEs also play a role in distributing development results. Banyumas SME Centers are the center of sales of Banyumas SME products. At present sales at the Banyumas MSME center are mostly using manual promotions. For online promotion, the Banyumas UMKM center has used Instagram and marketplace media, but the promotion is not yet maximal. For this reason, it is necessary to carry out activities in the form of Digital Marketing Training and Seo Optimization in the Marketplace at the Banyumas Umkm Center to Maximize Online Product Marketing. The method used in this activity is the method of seminars, discussions and questions and answers. The result of this activity is that MSMEs can maximize sales through online media.
Weakly Supervised Sentiment Analysis of Indonesian Rural Tourism Reviews: A TF-IDF Baseline for Melung Tourism Village Zanuar Rifa’i; Bayu Priya Mukti
Edu Komputika Journal Vol. 12 No. 1 (2025): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v12i1.31893

Abstract

This study investigates sentiment classification of Indonesian-language tourist reviews from the rural destination of Melung Tourism Village. A total of 724 user-generated reviews from 546 unique users are preprocessed using Indonesian-specific text cleaning, stopword filtering, and stemming, then weakly labeled through a stemmed positive–negative lexicon. TF-IDF unigram–bigram features are extracted from the preprocessed texts and used to train three classical classifiers: Naive Bayes, linear Support Vector Machine (SVM), and Logistic Regression. To address class imbalance, RandomOverSampler is applied only to the training data, and model evaluation combines stratified 5-fold cross-validation with a held-out test set, using weighted F1-score as the primary metric. Logistic Regression achieves the best performance on the test set (weighted F1 = 0.8799, accuracy = 0.8828), closely followed by SVM, while Naive Bayes lags behind. The results show that, even with a modest, weakly supervised dataset, a carefully designed classical pipeline can yield reliable sentiment indicators to support data-driven management of rural tourism destinations.
Co-Authors Bayu Priya Mukti Indra Kusuma Wardani Luzi Dwi Oktaviana