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All Journal Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding Prosiding University Research Colloquium
Nuryani, Ira
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences

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RKM Monitoring and Evaluation System in the City of Magelang: Proposed Concept Nuryani, Ira; Primadewi, Ardhin
Proceedings of Universitas Muhammadiyah Yogyakarta Graduate Conference Vol. 3 No. 2 (2024): Crafting Innovation for Global Benefit
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/umygrace.v3i2.592

Abstract

Local government such as Regional Development Planning Agency (Bappeda), holds an important role in budget management. For example Bappeda of Magelang City in Jawa Tengah. However, there are still several issues related to the distribution of the budget from Bappeda of Magelang City to the community. One of the issues is related to the large number of neighborhood associations (RT) managed by Bappeda, which the total is 1032 RT. The issues create a challenge in managing, distributing, and monitoring the budget effectively and efficiently. The Government of Magelang City created an Advanced, Healthy and Happy Community Empowerment Program or commonly called Rodanya Masbagia. Therefore, a monitoring system for the implementation of Rodanya Masbagia is needed for the community so that the use of funds is in accordance with the needs of the community. This system focuses on monitoring Community Needs Plan (RKM) managed by Bappeda of Magelang City, especially in managing a budget of 30 million rupiah per year for each RT. This study uses a qualitative method, including data and information collection, analysis, and observation. The sample consists of one neighborhood from each district in Magelang City, focusing on mapping the results of monitoring and evaluating programs and budgets. Therefore, the results of this system will enable Bappeda of Magelang City to monitor and evaluate the distribution of funds for each RT, ensuring compliance with the proposed plan. The business process in the optimize of SIMASBAGIA uses the Ward and Peppard Methods. Analysis is carried out using PIECES, Value Chain Analysis and Fishbone Diagram which provides a big picture of the problem in terms of various aspects. The result of this research is a proposed information system for more optimal monitoring and evaluation.
Classification of Avocado Ripeness Levels using Naïve Bayes Method Nuryani, Ira; Fadli, Aldi Muhammad Nur; Saputri, Nadila Dwi; Fadhilah, Alfira Nisa; Yudianto, Muhammad Resa Arif; Maimunah, M
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Mahasiswa (Student Paper Presentation) B
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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

Abstract

During this time most people in determining the ripeness of avocados for personal consumption is not difficult because they can distinguish themselves but another case if used for production, which requires a lot of labor to group ripe and raw avocados. One of the innovations in information and communication technology in agriculture and plantations is the use of classification methods with naïve bayes algorithms. The formula of the problem in this study is how to do the classification on the ripeness of avocados and see the accuracy rate of the data. The purpose of this study is to classify avocado ripeness and to acquire intelligent systems, so that it becomes the first step towards the implementation stage. Based on the results and analysis that has been done, it can be concluded that the Naive Bayes method is considered capable in classifying avocado ripeness by using RGB color features. The accuracy in testing using Naïve Bayes method reached 83.34%. The performance obtained from this intelligent system is also effective and efficient so that the classification of avocado ripeness can be implemented.
Co-Authors Ardhin Primadewi Fadhilah, Alfira Nisa Fadli, Aldi Muhammad Nur Maimunah, M Muhammad Resa Arif Yudianto Saputri, Nadila Dwi