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All Journal Desimal: Jurnal Matematika Dharma Bakti
Astuti, Febriani
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Humanities Education Mathematics Social Sciences Other

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PEMBERDAYAAN MASYARAKAT MELALUI PROGRAM KULIAH KERJA NYATA DI DUSUN GAMELAN, DESA SENDANGTIRTO, KAPANEWON BERBAH, SLEMAN Cahyono, Sadin; Ikhlas Yulianto, Muhammad; Putri Aprilia, Adinda; Kurniawan Putra, Muhammad Rafi; Munthe, Ryan Giggs; Astuti, Febriani
DHARMA BAKTI Dharma Bakti-Vol 7 No 1-April 2024
Publisher : LPPM IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/dharma.v7i1.4673

Abstract

Community empowerment is important to improve the quality of life and active community participation in local regional development. One way can be implemented is through the Community Service Program (KKN). This program is implemented in Gamelan Hamlet, Sendangtirto Village, Kapanewon Berbah, Sleman, which has large natural and human resources and can be improved. The research method used involves active community participation and observation of needs in the community. Furthermore, the programs provided include live pharmacy and the formation of study groups. The research results show that the KKN Program is able to make a significant contribution to empowering the Gamelan Hamlet community. Through collaboration between students, lecturers and the local community, this program has succeeded in providing skills training, increasing awareness of local potential and building strong social networks. In this process, it was identified that there was an increase in active community participation in decision-making for managing the living environment through the living pharmacy program and an increase in children's interest in learning through study groups.
Backpropagation algorithm modeling to predict the number of foreign tourist visits to indonesia via air gates Astuti, Febriani; Bekti, Rokhana Dwi; Br Keliat, Aurora Arianita; Sebo, Theodorina Inya
Desimal: Jurnal Matematika Vol. 6 No. 3 (2023): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v6i3.19751

Abstract

The tourism sector is a supporting sector for the Indonesian economy. One of the important actors in Indonesian tourism is foreign tourists. After the COVID-19 pandemic, the trend of foreign tourist visits to Indonesia has increased. The Central Statistics Agency (BPS) recorded that foreign tourist visits to Indonesia during 2022 reached 5.47 million. This figure has increased by 251.28% compared to the 2021 period. According to BPS, one of the gates most accessed by foreign tourists is the air gate. Based on these conditions, this research aims to predict the number of foreign tourists coming to Indonesia via air gates. The method used to predict is the backpropagation algorithm. The use of the backpropagation algorithm is able to provide prediction results with the highest level of accuracy of 91.40% for tourist visits at Ngurah Rai Airport, Bali. Furthermore, an MSE value of 0.056 was obtained. Thus, predictions using the backpropagation algorithm can be said to be good and quite accurate and can be used for prediction calculations in the following year.
Application of the perceptron algorithm in selecting statistics laboratory assistants Astuti, Febriani; Kris Suryowati; Olin Putra Pratama; Anggelina Karolina Teti
Desimal: Jurnal Matematika Vol. 8 No. 2 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/br4tf213

Abstract

Artificial Neural Networks (ANN) are computational models inspired by the structure and function of the human brain, particularly in utilizing interconnected neurons to solve complex problems. One of the foundational algorithms in ANN is the Perceptron algorithm, which is capable of identifying patterns and classifying data based on a set of input variables. This research aims to implement the Perceptron algorithm in the selection process of Statistics Laboratory Assistants at Akprind University. The method involves the use of fuzzy logic to assign weights to seven assessment variables determined by the laboratory: student semester, Grade Point Average (GPA), attitude, activeness during lectures, health condition, organizational involvement, and leadership. A dataset of 40 student records was used for training and testing the model. The results showed that the Perceptron algorithm, when integrated with fuzzy logic, successfully classified the data with an accuracy of 100%. In conclusion, the combination of the Perceptron algorithm and fuzzy logic proved to be effective in recognizing selection patterns, making it a reliable method for supporting the assistant recruitment process in the Statistics Laboratory at Akprind University.
Co-Authors Anggelina Karolina Teti Br Keliat, Aurora Arianita Cahyono, Sadin Ikhlas Yulianto, Muhammad Kris Suryowati Kurniawan Putra, Muhammad Rafi Munthe, Ryan Giggs Olin Putra Pratama Putri Aprilia, Adinda Rokhana Dwi Bekti, Rokhana Dwi Sebo, Theodorina Inya