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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Maridjan, Maula Muhammad
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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EVALUASI PEMETAAN WILAYAH DESA DAWUNGSARI DENGAN MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS (SIG) Fatimah, Dini Destiani Siti; Muhtadin, Fauzan Azmi; R, Alvarizky Putra Kurniawan; Febrian, Rivan; Husaeni, Fachri Ahmad Al; Saputra, Muhamad Dzaki; Maridjan, Maula Muhammad; Fitriyani, Dila; Mustofa, Muhamad Zaenal; Diniyaturobiah, Hanipah; Muzaky, Rifky Khoerul; Resita, Rasty; Mujahid, Wildan; Mulyana, Abdurrahman; Rafiqi, Putri Aufa; Maulana, Rifki Ilham; Noviansyah, Ikhwan; Adawiyah, Alya; Khaerurijal, Fajar; Baasith, Azry Abdul; Ardhillah, Zian Zaky
Jurnal PkM MIFTEK Vol 6 No 1 (2025): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.6-1.1972

Abstract

Amidst the rapid development of urbanization and increasing population, the challenges in regional planning and management are increasingly complex, especially in rural areas such as Dawungsari Village. This study aims to map the distribution of small businesses and public facilities, such as places of worship, sports facilities, educational facilities, and other village infrastructure. Data were collected through direct observation and local sources, then visualized in the form of a regional map. This mapping provides a comprehensive representation of the distribution of public facilities and services in the village, and provides a basis for supporting more effective development planning. The evaluation shows that the mapping method used is able to produce relevant information for regional management, although there are constraints related to data accuracy and limited local resources.
Sentiment Analysis of Indonesian-Language Plantix Application Reviews for Plant Disease Diagnosis Using Naive Bayes Methods Rahmaliyadi, Virzza; Maridjan, Maula Muhammad
Journal of Intelligent Systems Technology and Informatics Vol 1 No 2 (2025): JISTICS, July 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i2.12

Abstract

The Plantix app is one of the digital solutions widely utilized by farmers to diagnose plant diseases through image recognition technology and support from the user community. The large amount of Indonesian-language customer feedback on Google's application can be a valuable source of information for assessing the effectiveness and user satisfaction of this application. This study uses naive Bayes algorithms to classify sentiments based on the Plantix application's customer feedback. The dataset was obtained by implementing web scraping techniques with the Google Play scraper library, resulting in more than 354 reviews. Data preprocessing stages include case folding, text cleaning, tokenization, stemming using the Sastrawi library, and text transformation into numerical form using the Term Frequency-Inverse Document Frequency (TF-IDF) method. Sentiment labels are determined based on user star ratings, which are divided into three categories: positive, neutral, and negative. The Multinomial Naive Bayes algorithm performs the classification process and is assessed through the K-fold Cross Validation technique (K=10). The assessment results show that the model achieves the highest accuracy of 75.10% and F1-score of 72.35% with the shuffle sampling method, which falls into the category of fairly good classification. This study demonstrates that naive Bayes methodology is effectively used in sentiment analysis of text-based agricultural application reviews in Bahasa Indonesia.
Co-Authors Adawiyah, Alya Ardhillah, Zian Zaky Baasith, Azry Abdul Dini Destiani Siti Fatimah Diniyaturobiah, Hanipah Febrian, Rivan Fitriyani, Dila Husaeni, Fachri Ahmad Al Khaerurijal, Fajar Maulana, Rifki Ilham Muhtadin, Fauzan Azmi Mujahid, Wildan Mulyana, Abdurrahman Mustofa, Muhamad Zaenal Muzaky, Rifky Khoerul Noviansyah, Ikhwan R, Alvarizky Putra Kurniawan Rafiqi, Putri Aufa Rahmaliyadi, Virzza Resita, Rasty Saputra, Muhamad Dzaki