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Penerapan Algoritma Genetika Untuk Mencari Optimasi Kasus TSP Pada 20 Gerai Indomart Rosanti, Yerika Puspa; Triana, Iwel; Pancahayani, Sigit
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.423

Abstract

In the delivery of a package, goods, and conducting business, location is a crucial factor to manage. A common issue is the late arrival of packages because delivery couriers cannot find the fastest or most efficient route. This study aims to apply a genetic algorithm to optimize the traveling salesman problem (TSP) for the distribution of goods to 20 Indomaret outlets in the Dago area of Bandung City. TSP is a classic optimization problem that seeks to find the shortest route that visits each city once and returns to the origin city. The genetic algorithm, as a population-based search and optimization method, is used due to its capability to find near-optimal solutions for complex and large problems. This algorithm leverages natural selection mechanisms such as selection, crossover, and mutation to develop solutions from one generation to the next. Initial parameters were set with a population of 100 and a maximum of 500 generations to increase the variety of solutions without taking too much time. The fitness value was obtained by taking the negative of the total distance traveled, and after the iteration process, an optimal result with a fitness value of -0.10 was achieved. It only took 50 seconds to run 500 generations for selecting the distribution route of 20 Indomaret outlets.
Understanding the Effect of Fruits Maturity Level on Its Effectiveness as a Dielectric for Parallel Plate Capacitors for Senior High School Student Rosanti, Yerika Puspa; Fahra, Raden Manzilah Mubarokah; Khotimah, Siti Nurul
International Journal of STEM Education for Sustainability Vol 5, No 1 (2025)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI) 

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/ijses.v5i1.444

Abstract

Indonesia is an agrarian country that produces fruits in abundant quantities and in various variations. Fruits contain diverse contents, one of which can be utilized as a dielectric capacitor. This research is conducted to provide senior high school students with an understanding of the influence of dielectrics from several fruits on capacitance. This experiment analyzed the maturity level of fruits and their effectiveness as dielectric capacitors for parallel plate capacitors. Due to the maturity level of fruits being composed of many variables, this study is focused on differences in water content, sugar concentration, and acidity level. Through laboratory experiments, researchers examined these factors in guava, papaya, pear, mango, and apple fruits. The capacitance value of parallel plates is measured using an LCR meter, and it is found that the capacitance of parallel plates with air dielectric increases significantly when infiltrated with fruit dielectric. Water content has a significant influence. The capacitance value is also high in fruits with high water content and vice versa. Meanwhile, the influence of sugar concentration is less significant in this study, only noticeable in papaya fruits. However, this is supported by the fruit's acidity level as seen from its pH value. Fruits with high pH values also have high capacitance. Experiments found that as fruits ripen, their water content, sugar concentration, and pH value tend to increase. This causes mature fruits to be more effective when used as dielectric capacitors.
Exploring Energy Data through Clustering: A Hyperparameter Approach to Mapping Indonesia's Primary Energy Supply Windarto, Agus Perdana; Rosanti, Yerika Puspa; Mesran, Mesran
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i2.29032

Abstract

The rapid economic growth and population development in Indonesia have significantly increased the demand for energy, presenting complex challenges in managing the primary energy supply due to geographical variability and dispersed natural resources. This study addresses these challenges by applying clustering techniques with a hyperparameter approach to explore and map Indonesia's primary energy supply. The research contributes to the field by offering an effective method for analyzing energy data patterns and optimizing energy management. Secondary data on energy production, consumption, and distribution from reliable sources such as the Ministry of Energy and Mineral Resources were collected and analyzed. Various clustering algorithms, including K-Means, Fast K-Means, X-Means, and K-Medoids, were applied to identify energy supply patterns across different regions. The Davies-Bouldin Index was used to evaluate the effectiveness of the clustering algorithms. The results indicate that distance measures such as Euclidean Distance and Chebychev Distance consistently show excellent clustering performance. The study found that the choice of distance measure significantly impacts the clustering quality. The insights gained from this analysis provide valuable information for stakeholders involved in energy planning and policy-making, enhancing the efficiency and sustainability of energy management in Indonesia. This research establishes a foundation for further detailed and holistic energy data analysis, supporting better decision-making in energy planning and development.