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All Journal JURNAL TEKNIK INFORMATIKA DAN KOMPUTER JPMB : Jurnal Pengabdian Masyarakat Berkelanjutan
Faldy Irwiensyah
Universitas Muhammadiyah Prof. Dr. Hamka
Humanities Computer Science & IT Education Environmental Science Library & Information Science Social Sciences

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Perbandingan Akurasi Metode Naïve Bayes Classifier dan Lexicon Based Pada Analisis Sentimen Respon Masyarakat Tentang Kebijakan Kenaikan Harga Minyak Goreng Faldy Irwiensyah; Firman Noor Hasan
Jurnal Teknik Informatika dan Komputer Vol. 2 No. 1 (2023): Jurnal Teknik Informatika dan Komputer
Publisher : UHAMKA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jutikom.v2i1.11500

Abstract

Cooking oil is a basic need for Indonesian people. Indonesia experienced a shortage of oil in March 2022. This was a hot topic of discussion on social media Twitter last March, many people thought positively or negatively. However behind it all, there are differences in the assessment of parties who feel the pros and cons, various parties have different points of view. In this article, we conduct a sentiment analysis of public responses regarding the scarcity of cooking oil using a dataset obtained from the Twitter digital platform. This article aims to classify tweets related to the scarcity of cooking oil into positive and negative sentiments using a machine learning strategy with the Naive  Bayes and lexicon based methods. This algorithm was chosen to make it easier for interested users to compare methods and find out how accurate it is, which is where the level of accuracy obtained from the lexicon method is 42% and the method using the naïve Bayes classifier is 72%. Shows the results of the analysis related to the scarcity of cooking oil for the highest level of accuracy, namely the method that uses the naïve Bayes classifier compared to the method that uses lexicon based
IMPLEMENTASI SISTEM INFORMASI KESEHATAN BERBASIS KADER POSYANDU UNTUK DIGITALISASI DATA KESEHATAN Dodi Syaripudin; Faldy Irwiensyah; Rusdi Doviyanto; Zuhri Halim
Jurnal Pengabdian Masyarakat Berkelanjutan Vol. 2 No. 1 (2026): Jurnal Pengabdian Masyarakat Berkelanjutan (JPMB), Februari 2026
Publisher : Yayasan Nusa Cendekia Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64020/jpmb.v2i1.21

Abstract

Posyandu plays a crucial role in maternal and child health monitoring; however, manual recording systems using KIA/KMS books often lead to data inconsistency, physical damage risks, and delays in reporting health indicators such as stunting. This community service activity was carried out through an approach focused on the development and implementation of a health information system based on Posyandu cadres. This study aims to design and implement a digital health information system to transform data management processes at the Posyandu level to be more accurate, efficient, and integrated. This research employs the Research and Development (R&D) method with the Waterfall development model. The system design is modeled using the Unified Modeling Language (UML), including use case, activity, and class diagrams. Testing was conducted using Black Box Testing for functional validation and User Acceptance Test (UAT) to measure the level of user acceptance.  The results show that the developed information system is 100% functional according to technical specifications. UAT testing among Posyandu volunteers (kader) indicated a satisfaction rate of 88%, categorizing the system as Highly Acceptable. Data digitalization through this system significantly accelerates the data recapitulation process and minimizes input errors, thereby supporting more targeted medical decision-making at the Community Health Center (Puskesmas) level.
Co-Authors Dodi Syaripudin Firman Noor Hasan Rusdi Doviyanto Zuhri Halim