ANALYSIS OF ZAKAT MANAGEMENT EFFICIENCY LEVELS IN TWO ASEAN COUNTRIES (STUDIES IN INDONESIA AND MALAYSIA) Mukhtar Adinugroho, Nur Farahiah Binti Azmi, Ubaidillah Zuhdi, Moh. Saiful Hakiki, Ahmad Ridhuan Abdullah, Zujajatul 'Ilmi Revista De Gestao Social E Ambiental, 2024 Purpose: This study aims to determine the level of efficiency of the Zakat Management Agency in ASEAN, especially Indonesia, Malaysia and Singapore as a country that has a Zakat Institution and publish its financial statements in the period 2020 to 2023. Method/design/approach: The efficiency of this research is processed using Data Envelopment Analysis (DEA) with a production approach. This method measures the ratio between input and output compared between the zakat institution studied. Output variables used in this study include collecting funds and distribution funds. While the input variables used are Personnel Costs, Operational Costs and Socialization Costs. Result and conclusion: The results of this study indicate that the optimal efficiency consistently for four years was owned by MAIK (Majelis Agama Islam dan Adat Istiadat Melayu Kelantan) and MUI (Majelis Ulama Indonesia) while in BAZNAS had experienced inefficiencies in Maluku Utara 55%, in Papua 77%, and in Nusa Tenggara Timur it was 68%. The contribution of this research can be an evaluation tool for the Zakat Institution in terms of managing funds and arranging strategies for raising and channeling funds better. Originality/value: Zakat is believed to be a means to create justice for the distribution of community wealth. However, in fact the reality emerged in Indonesia shows that the collecting of zakat is still far from the potential that exists. In Malaysia, the problem of zakat distribution is still found in many states. Therefore it is necessary to optimize zakat through efficiency.
Analysis of Customer Satisfaction Survey on E-Wallets Using Simple Additive Weighting and TOPSIS Methods Nonlinear Dynamics and Systems Theory, 2024
Prototype for Current and Voltage Monitoring of Distribution Transformer Based on WiFi Firman Yudianto, Teguh Herlambang, Mukhtar Adinugroho, Fajar Annas Susanto, Tri Deviasari Wulan, Imam Wahyudi Farid 2023 International Conference on Advanced Mechatronics Intelligent Manufacture and Industrial Automation Icamimia 2023 Proceedings, 2023 A transformer is a key component in the electrical power distribution system. To maintain the continuity and reliability of the power system, it is essential to ensure the reliability of the energy distribution system. Factors affecting the quality of electrical energy include current, voltage, and temperature. With an increase in load, the transformer's temperature and current can rise, and the increase in current can be influenced by excessive load, thus raising the transformer's temperature. The temperature rise can also be influenced by the environmental conditions inside the transformer room. Excessive temperature in the transformer room can lead to explosions. Therefore, this thesis research aims to design a prototype monitoring device based on WiFi for parameters such as current, voltage, and temperature, to provide real-time information about the transformer's condition. The results of this research show that the prototype monitoring device for the transformer provides values very close to manual calculations, with the largest error percentages being 2.18% for current measurement, 1.04% for voltage measurement, and 3.3% for temperature measurement. This prototype monitoring device also provides information to the user when the current value in the circuit reaches 2A, making it easier for the user to identify potential transformer faults before they lead to damage. The transformer's efficiency ranges from 99.54% to 99.82%. Maintenance is required for the transformer as it approaches high temperatures to ensure optimal transformer performance.
Forecasting average room rate using k-nearest neighbor at Hotel S Vaizal Asy'ari, Mohamad Yusak Anshori, Teguh Herlambang, Imam Wahyudi Farid, Denis Fidita Karya, Mukhtar Adinugroho 2023 International Conference on Advanced Mechatronics Intelligent Manufacture and Industrial Automation Icamimia 2023 Proceedings, 2023 In managing a hospitality business, it takes a lot of data and analysis to make the right decisions. One important indicator in assessing the performance of a hotel is the Average Room Rate (ARR) which shows the average price of rooms sold by the hotel in a certain period. From the ARR data obtained, it can make a picture of the future regarding expansion to increase the value of ARR in the future. In this study, ARR forecasting was carried out for Hotel S using the k-nearest neighbor (k-NN) method. The dataset used in this study is in the form of room sold out, room revenue, and average room rate at Hotel S from April 2018 to June 2023. The simulation was carried out by dividing the data into training data and testing data with a ratio of 70:30 and 80:20, and the selection of k-values are 3 to 7. The forecasting results that have been carried out using k-NN for split data 70%:30% produce an optimal RMSE of 6,335 at k-values is 3. The forecasting results that have been carried out using k-NN for 80%:20% data split produce an optimal RMSE of 7,452 at k-values is 5. From this comparison, the results of forecasting ARR using k-NN obtained the best RMSE of 6,335. The results of this study can be used by Hotel S in determining the price of various types of rooms that are appropriate and expected to provide benefits for management.
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