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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Mantik
Samuel Indra Gunawan Situmeang
Institut Teknologi Del
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Survey on Ditenun Application Utilization Through Independent Learning – Independent Campus Program (Merdeka Belajar – Kampus Merdeka) Humasak Tommy Argo Simanjuntak; Arlinta Christy Barus; Samuel Indra Gunawan Situmeang; Arie Satia Dharma
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The policy of Independent Learning - Independent Campus (Merdeka Belajar - Kampus Merdeka: MBKM) by the Ministry of Education, Culture, Research, and Technology provides opportunities for students to gain real work experience in an industrial or professional environment to prepare students in social, cultural, work and technological changes. DiTenun (Digital Tenun Nusantara) responds to this challenge by organizing an independent learning program to accelerate student work readiness while increasing the competitiveness of DiTenun’s industry and products. This study aims to evaluate the successful implementation of MBKM in the development of the DiTenun application. The implementation was analyzed from the perspective of students and application users. This study used a survey research method and a saturated sampling technique. Hypothesis testing showed that the implementation of MBKM program positively affects the development of DiTenun application.
Impact of Text Preprocessing on Named Entity Recognition Based on Conditional Random Field in Indonesian Text Samuel Situmeang
Jurnal Mantik Vol. 6 No. 1 (2022): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The text preprocessing stage within a natural language processing application framework helps eliminate parts that are not helpful in the text analysis process or particular noise. Despite having a potential impact on the final performance of the application, text preprocessing has not received attention in the text analysis application literature, especially in the named entity recognition application in Indonesian texts. This paper aims to comprehensively examine the impact of text preprocessing in the Indonesian named entity recognition based on a baseline model, namely Conditional Random Field, to find the fittest preprocessing procedures for a NER model compelling performance. Various forms of text preprocessing contribute to the successful recognition of named entities assessed comparatively across three categories: people, places, and organizations. Experimental analysis of the data set reveals that several combinations of preprocessing text forms are useful. Rather than enabling or disabling them all, several combinations can significantly improve the accuracy of Indonesian named entity recognition depending on the entity category.
A cluster and association analysis visualization using Moodle activity log data Andri Reimondo Tamba; Krista Lumbantoruan; Aulia Pakpahan; Samuel Situmeang
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i2.pp150-161

Abstract

The course activity log is where a learning management system (LMS) like Moodle keeps track of the various learning activities. In order to conduct a quicker and more in-depth examination of the students' behaviors, the instructor may either directly examine the log or make use of more complex methodologies such as data mining. The majority of the proposed methods for analyzing this log data center mostly on predictive analysis. In this research, cluster analysis and association analysis, two separate data mining functions, are investigated in order to analyze the log. The students' activities are used in the cluster analysis performed with K-Means++, and the association analysis performed with Apriori is used to investigate the connections between the students' various activities. A dashboard presentation of the findings is provided in order to facilitate clearer comprehension. Based on the findings of the analysis, it can be concluded that the structure of the student cluster is medium, whereas the association between the activities undertaken by students is positively correlated and well-balanced. The subjective review of the dashboard reveals that the visualization is already sufficient, but there are some recommendations for making it even better.
Co-Authors Andri Reimondo Tamba Arie Satia Dharma Arlinta Christy Barus Aulia Pakpahan Humasak T. A. Simanjuntak Krista Lumbantoruan