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Journal : International Journal Software Engineering and Computer Science (IJSECS)

Implementation of an Asset Management System Using the Straight-Line Method of Depreciation Based on Odoo 14 CE at PT Forecastle Indonesia Saputra, Hendra Ekky; Rasiban
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.2975

Abstract

The purpose of this research is to implement an asset management system based on Odoo 14 Community Edition (CE) using a straight-line method at PT Forecastle Indonesia. Only the straight-line method is chosen as it gives the simple and efficient way to compute the depreciation of the asset over the useful life. Odoo 14 CE is selected for its rich features for asset management for tracking, depreciation calculation, maintenance, and reporting capabilities built in. The study consists of an analysis of the company needs, design based on straight-line method, Odoo 14 CE configuration, and observation and evaluates the implementation results. Key Outcomes: Increased efficiency in managing assets, accurate depredation tracking, reduced manual errors, better inter- department integration. The system is also expected to help prepare reports on assets-financial relations. We will then assess the implementation outputs against improvements in asset management efficiency and effectiveness (e.g. asset condition monitoring, maintenance costs management per asset, asset value tracking). The study will benefit the company by improving its operational and financial performance.
Sentiment Analysis of the Tapera Law on Platform X Using Naive Bayes Algorithm Bimantoro, Dava Sevtiandra; Rasiban
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3077

Abstract

The implementation of the 2016 Public Housing Savings Law (UU Tapera) aims to help legal and informal workers have decent houses through the management of housing savings funds by BP Tapera. However, when implemented, this program experienced obstacles amidst various problems including the transparency of the fund collection and management system, the unevenness of benefit provision, and variations in public perception. Sentiment analysis was conducted on Twitter data for sentiment regarding the Tapera Law to obtain public perception with Naïve Bayes. This approach classifies sentiment into positive, negative, and neutral. The accuracy of the Analysis Results was 62.47% (343 negative sentiments, 23 neutral, and finally 32 positive sentiments). The public mostly has negative sentiment towards the Tapera Law, because many of them are afraid of losing justice and effectiveness with this policy. These results underline the need to intensify transparency and communication of the benefits of the Tapera Law and its mechanisms to increase public acceptance and trust.