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All Journal TEKNIK INFORMATIKA MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Indonesian Journal of Electrical Engineering and Computer Science
Nashrul Hakiem
Syarif Hidayatullah State Islamic University Jakarta
Computer Science & IT

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The Information System Project Profiles among Universities in Indonesia A'ang Subiyakto; Abd. Rahman Ahlan; Mira Kartiwi; Nashrul Hakiem; Muhammad Qomarul Huda; Aries Susanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp865-872

Abstract

Information system (IS) utilizations may have been one of the determinant factors for the survival requirement of the higher education sector in Indonesia. Despite the IS projects have been conducted since the 1980s in this country, but many studies indicated that success of the projects seems like in the low level. This survey study was purposed to know the status of the IS project success among universities by involving the internal stakeholders. The higher education database of the Ministry of Research, Technology, and Higher Education (MRTHE) and the Association of Computing and Informatics Institutions Indonesia (ASCII-I) in the year 2015 were used for selecting around 1.230 respondents based on a purposive random sampling. The blended questionnaires were then distributed with almost 298 (±24%) responses. This paper presents five project profiles, including the aim, IS strategic plan availability, internal team involvement, budget allocation, and the success level of the projects.
A Comparative Analysis of Random Forest, XGBoost, and LightGBM Algorithms for Emotion Classification in Reddit Comments Nenny Anggraini; Syopiansyah Jaya Putra; Luh Kesuma Wardhani; Farid Dhiya Ul Arif; Nashrul Hakiem; Imam Marzuki Shofi
JURNAL TEKNIK INFORMATIKA Vol 17, No 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.38651

Abstract

This research aims to compare the performance of three classification algorithms, namely Random Forest, XGBoost, and LightGBM, in classifying emotions in Reddit comments. Emotion classification in Reddit comments is a complex classification problem due to its numerous variations and ambiguities. This research utilizes the GoEmotions Fine-Grained dataset, filtered down to 7,325 Reddit comments with 5 different basic emotion labels. In this study, data preprocessing steps, feature extraction using CountVectorizer and TF-IDF, and hyperparameter tuning using GridSearchCV for each algorithm are conducted. Subsequently, model evaluation is performed using Cross-Validation and confusion matrix. The results of the study indicate that Random Forest outperforms the XGBoost and LightGBM algorithm with an accuracy of 75.38% compared to XGBoost with 69.05% accuracy and LightGBM with 66.63% accuracy.
Development of Smart Charity Box Monitoring Robot in Mosque with Internet of Things and Firebase using Raspberry Pi Nenny Anggraini; Zulkifli Zulkifli; Nashrul Hakiem
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4209

Abstract

Mosques are the center of Muslim communities’ spiritual and communal life, thus requiring effective financial management. The purpose of this study was to develop a smart donation box robot that utilizes Internet of Things technology to address efficiency and increase transparency in managing donations. The methodology in this study used a prototyping method consisting of Rapid Planning, Rapid Modeling, Construction, and Evaluation stages, which aimed to develop a functional prototype quickly. The results showed that the smart donation box robot detected and counted banknote denominations with varying degrees of success, achieving a detection success rate of 100% for all tested denominations at an optimal sensor distance of 1 cm. However, the detection rate dropped to 42.86% at 0.5 cm and 28.57% at 1.5 cm, highlighting the significant impact of sensor placement on performance. Coin detection was performed accurately, correctly identifying and sorting denominations without error. This enabled real-time financial monitoring via the Telegram application, significantly increasing transparency for mosque administrators and congregants. The conclusion of this study confirms that IoT technology can substantially improve mosque donation management by automating the collection process and providing real-time
Co-Authors A'ang Subiyakto Abd. Rahman Ahlan Aries Susanto Farid Dhiya Ul Arif Huda, Muhammad Qomarul Imam Marzuki Shofi Luh Kesuma Wardhani Mira Kartiwi Nenny Anggraini Syopiansyah Jaya Putra Zulkifli Zulkifli