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Khalimaturrofi’ah
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Computer Science & IT Economics, Econometrics & Finance

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Sistem Pendukung Keputusan Penyaluran Bantuan Balita Stunting Menggunakan Metode SAW (Simple Additive Weighting) Studi Kasus Posyandu Mawar Herlina Vika Safriyani; Khalimaturrofi’ah; Purwanto
Journal Of Informatics And Busisnes Vol. 3 No. 3 (2025): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i3.3457

Abstract

Stunting in toddlers is a chronic malnutrition that impacts child growth and development. This study aims to develop a Decision Support System for Distribution of Stunting Toddler Assistance Using the SAW (Simple Additive Weighting) Method at the Mawar Dukuh Tambakan Integrated Health Post (Posyandu). This system was developed to assist Posyandu cadres in determining toddler assistance recipients more objectively and efficiently. The selection process that has been carried out manually is at risk of errors in recording, inaccurate data and errors in determining assistance for stunted toddlers. Therefore, a system is needed that is able to assess based on various criteria in a structured manner. This system was designed using the waterfall development method with stages of needs analysis, system design, implementation, and testing. The research method used is a qualitative method, namely using observation, documentation, and interviews. At the design stage, namely star UML for system modeling, figma for interface design. Frontend uses HTML, CSS, Javascript. Backend uses PHP, Database uses MYSQL, XAMPP as a local web server and Visual Studio Code as the main editor. Testing uses blackbox and a Likert scale questionnaire. The results of the study show that the system can help the selection process for aid recipients quickly, accurately and objectively. Based on the questionnaire evaluation with a Likert scale, the system received a user satisfaction percentage of 86.4%.
Perancangan dan Implementasi Aplikasi Samsat Pintar (Si Sapi) Berbasis Android dengan Integrasi Teknologi Optical Character Recognition (OCR) untuk Pembacaan Otomatis Data STNK Studi Kasus: Kantor Samsat Banjarnegara Imroatun Isna Nur Fadhilah; Purwanto; Khalimaturrofi’ah
Journal Of Informatics And Busisnes Vol. 3 No. 3 (2025): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i3.3475

Abstract

The administration of motor vehicle services at the Samsat Banjarnegara office still faces challenges in terms of efficiency and accuracy, particularly in the manual data entry process of the Vehicle Registration Certificate (STNK). These issues result in service queue delays of up to 25% per year and data entry errors at a similar rate. This study aims to design and implement the Samsat Pintar (Si SAPI) application, an Android-based system integrated with Optical Character Recognition (OCR) technology to automatically read and extract data from STNK documents. The system development method employed is the Waterfall model with a Research and Development (R&D) approach. The application was implemented using the Kotlin programming language in Android Studio, with Tesseract OCR as the main engine. Data were collected through observation, interviews, and literature study, while the system testing was conducted using the black box testing method.The testing results showed that all application features functioned as expected, with no system errors found during trials, and the application response time was relatively fast (±5 seconds). Furthermore, testing with 25 Samsat Banjarnegara staff members through questionnaires consisting of five evaluation indicators produced a total score of 549 out of a maximum score of 600, resulting in a satisfaction percentage of 91%. This indicates that the Si SAPI application was very well accepted by users and is proven to help accelerate and simplify the process of motor vehicle administration services.on the questionnaire evaluation with a Likert scale, the system received a user satisfaction percentage of 86.4%.
Co-Authors Herlina Vika Safriyani Imroatun Isna Nur Fadhilah Purwanto