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All Journal Variance : Journal of Statistics and Its Applications Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat International Journal of Research in Community Services
Gunawan, Naftali Brigitta
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Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance Energy Engineering Law, Crime, Criminology & Criminal Justice Mathematics Nursing Social Sciences Other

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IMPLEMENTATION OF LONG SHORT-TERM MEMORY (LSTM) IN FORECASTING THE NUMBER OF TRAIN PASSENGERS IN JAVA ISLAND Gunawan, Naftali Brigitta; Wiyanti, Wiwik
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 1 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss1page1-10

Abstract

For certain Indonesians, trains are a particularly popular form of land transportation. Every year, during specific seasons, this mode of transportation consistently experiences a surge in passenger numbers. Due to this, it is necessary to make accurate predictions to make policies, such as whether additional carriages are needed. The selection of prediction methods will significantly impact policymaking. One of the methods currently being developed for prediction is related to machine learning. This study aims to implement a forecasting method using machine learning that can be used to predict time series data. The machine learning used in this study is the Long Short-Term Memory (LSTM) method. In this study, we used time series data on the number of train passengers. The data used is secondary data from the Statistics Indonesia (BPS). The data analysis process in this study uses Python software. The results of this analysis show that the LSTM model has a high level of accuracy in prediction, indicated by the mean squared error value of 2,941,137.156 and MAPE of 0.07%. Forecasts show a gradual increase in the number of passengers, starting from 32,381 people in the first month to 33,068 people in the third month. These results indicate that the LSTM model is thought to be effective in predicting changes in the number of train passengers, and further research is needed to verify this assumption.
Talent Classification: Recognizing and Developing Personal Potential Optimally at Tarsisius Vireta High School Januaviani, Trisha Magdalena Adelheid; Kalfin, Kalfin; Arifin, Alicia; Gunawan, Naftali Brigitta
International Journal of Research in Community Services Vol. 5 No. 2 (2024)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v5i2.607

Abstract

Knowing students' talents and interests from an early age is very important to help them develop their potential more effectively. Every individual is unique, and the process of identifying talents and interests requires patience and a deep understanding of the student. With a good approach, we can help students develop their potential optimally. This research aims to explore the potential of students at Tarsisius Vireta High School using a talent classification approach. In the educational context, recognizing and developing students' potential is the key to achieving personal success and positive contributions to society. The research method used is qualitative with data collection techniques through questionnaires given before (Pre Test) and after (Post Test) the seminar given to students. The data obtained becomes evaluation material in determining how much students know the talents each student has. Based on the results of the analysis, it was found that there was a significant increase in students' awareness of their talents and interests, as well as their ability to identify and categorize talents. With a deeper understanding of students' potential, it is hoped that education at Tarsisius Vireta High School can be more optimal in developing students' talents and interests, so that they are ready to face the future with confidence and honed abilities.
Pelatihan Visualisasi Data Menggunakan Excel di SMA Erenos Tangerang Siregar, Bakti; Gunawan, Naftali Brigitta; Riswandi, Calvin
Abdimas Galuh Vol 6, No 1 (2024): Maret 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v6i1.13358

Abstract

Visualisasi Data merupakan bidang terapan yang meliputi statistika, ilmu komputer, dan bisnis. ilmu dan menganalisis data, khususnya data kuantitatif (numerik), baik yang terstruktur maupun tidak terstruktur. Saat ini kebutuhan terhadap profesi data scientist (Analis Data) sangat tinggi seiring pengkembangan teknologi digital.  Banyak siswa-siswi SMA/SMU sangat tertarik tetapi belum mengetahuai bagaimana mereka memulai pembelajaran Visualisasi Data menggukan Excel. Olehkarena itu, Universitas Matana melalui prodi Statistika komitmen dalam melakukan pengenalan dasar mengenai pemanfaat Excel dalam mengolah data (sains data).  Adapun mitra dalam Pengabdian Kepada Masyarakat (PKM) ini adalah SMA Erenos.  Pelaksaan pelatihan ini terbukti memberikan kenaikan pengetahuan sebanyak 19% terkait Visualisasi data berdasarkan evaluasi nilai post-test dan nilai pre-test yang diberikan kepada peserta. Sehingga, konsep pembelajaran praktikum ini dapat diterapkan lebih banyak pembelajaran di Sekolah.
Co-Authors Arifin, Alicia Bakti Siregar Januaviani, Trisha Magdalena Adelheid Kalfin, Kalfin Riswandi, Calvin Wiwik Wiyanti, Wiwik