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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jambura Journal of Informatics Engagement: Jurnal Pengabdian Kepada Masyarakat
Handri Santoso
Pradita University
Religion Arts Humanities Computer Science & IT Education Social Sciences

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Enhancing the Efficiency of Jakarta's Mass Rapid Transit System with XGBoost Algorithm for Passenger Prediction Muhammad Alfathan Harriz; Nurhaliza Vania Akbariani; Harlis Setiyowati; Handri Santoso
Jambura Journal of Informatics VOL 5, NO 1: APRIL 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v5i1.18814

Abstract

This study is based on a machine learning algorithm known as XGBoost. We used the XGBoost algorithm to forecast the capacity of Jakarta's mass transit system. Using preprocessed raw data obtained from the Jakarta Open Data website for the period 2020-2021 as a training medium, we achieved a mean absolute percentage error of 69. However, after the model was fine-tuned, the MAPE was significantly reduced by 28.99% to 49.97. The XGBoost algorithm was found to be effective in detecting patterns and trends in the data, which can be used to improve routes and plan future studies by providing valuable insights. It is possible that additional data points, such as holidays and weather conditions, will further enhance the accuracy of the model in future research. As a result of implementing XGBoost, Jakarta's transportation system can optimize resource utilization and improve customer service in order to improve passenger satisfaction. Future studies may benefit from additional data points, such as holidays and weather conditions, in order to improve XGBoost's efficiency.
Word-Level Story Generator Bahasa Indonesia Menggunakan Markov Chain dan Bidirectional GRU Cecilia Angieta Winata; Handri Santoso; Ito Wasito; Haryono .
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 4 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i4.5574

Abstract

Story generator plays an important role to help story writers generate story ideas, even initial concepts. Usage of Keras Tokenizer as well as word embedding model requires relatively slower model training speed in order to execute hundreds of training iterations. In this research, we propose design method to create a word-level Indonesian language story generator by implementing Markov Chain model and Bidirectional GRU, which is able to generate quality text as good as the outputs of word embedding models, while having faster model training speed. The performance of Markov Chain-BiGRU model was compared with the performance of word-level BiGRU model and character-level GRU model. The first stage of model evaluation was done by comparing each model’s loss value and model training speed; the second stage was done by giving survey to 33 assessors; while the third stage was done by comparing model’s performance with model from related work. The proposed Indonesian story generator succeeded on increasing the model training speed by 66.38% from related work’s model, as well as producing better-quality text compared to outputs from conventional neural-based and word embedding models.
Efforts to Improve the Welfare of Ornamental Fish Farmers in Kalipaten Village Through the Implementation of LoRaWAN-Based IoT Technology William Widjaja; Theresia Herlina Rochadiani; Handri Santoso; Ninuk Yasmarini; Sherensia Putri Angeliani; Gabriel Alexander
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 7 No 2 (2023): November 2023
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v7i2.1339

Abstract

The ornamental fish business is currently one of the popular businesses in the community. The relatively fast reproduction cycle, around 0.5 – 1.5 months, with a relatively high selling price, makes this ornamental fish business much in demand by the public. The maximum utilization of technology will help MSMEs in increasing their income. This service activity aims to build a LoRaWAN-based IoT system for ornamental fish farming along with a mobile-based ornamental fish monitoring application to help manage ornamental fish livestock, which ultimately has an impact on improving the quality of ornamental fish and the income of CV Home Aquafish partners. The method utilizes a service-learning approach through stages: Identify, design, and build a LoRaWAN-based IoT and mobile-based monitoring system, implementing, mentoring, and measuring the effectiveness of the LoRaWAN device in improving the quality of ornamental fish and the income of CV Home Aquafish partners. As a result, LoRaWAN can effectively help minimize mortality in ornamental fish seedlings so that the quality of the fish is maintained. The income of CV Home Aquafish's ornamental fish nursery partners in Kalipaten Village, Gading Serpong, Tangerang also increases.
Co-Authors Cecilia Angieta Winata Gabriel Alexander Harlis Setiyowati Haryono . Ito Wasito Muhammad Alfathan Harriz Ninuk Yasmarini Nurhaliza Vania Akbariani Sherensia Putri Angeliani Theresia Herlina Rochadiani William Widjaja