Chepi Nur Albar
Universitas Komputer Indonesia

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Tree Algorithm Model on Size Classification Data Mining Agis Abhi Rafdhi; Eddy Soeryanto Soegoto; Senny Luckyardi; Chepi Nur Albar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 4 (2023): August 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i4.4572

Abstract

The goal of this research is to use a tree algorithm to categorize student clothing in order to acquire an accurate size. This research is qualitative through descriptive analysis, while the analysis used C.45 tree algorithm classification. Manual calculations utilizing the tree algorithm formula revealed that most students require XL-sized clothing. On the characteristic of X5 (length of the shoulder), the maximum entropy and information gain values were obtained at 0.212642462. According to the forecast, the shoulder length attribute is the first calculation in developing a decision tree scheme since it has the largest entropy and the value of information gain. Lastly, the findings of this study analysis can be used as a mapping prediction to make decisions on the size of the student group's clothing.
DREAM: Design of Higher Education Curriculum Based on Spiritual Values Senny Luckyardi; Hanhan Maulana; Bagus Hary Prakoso; Benny Widaryanto; Chepi Nur Albar; Silvi Munawaroh; Juliana Karin
Jurnal Pendidikan Islam ARTICLE IN PRESS
Publisher : The Faculty of Tarbiyah and Teacher Training associated with PSPII

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aimed to develop an alternative curriculum design to meet the increasing demand for high-quality graduates in today’s dynamic economy. This research used a mixed-method approach for data collection and analysis to ensure comprehensive, reliable, and objective findings. The results highlighted a growing need to cultivate strong leadership traits, emphasizing the development of holistic and spiritual leadership that integrates ethics, decision-making, and practical actions. Individuals with prophetic leadership qualities were found to be highly dependable due to their strong sense of responsibility, spiritual grounding, and ability to make wise decisions based on available resources. In response, the DREAM curriculum was designed to nurture graduates with these attributes, equipping them to meet the evolving needs of modern industries. Graduates of the DREAM curriculum are expected to excel not only in hard and soft skills but also as inspirational leaders who motivate others. This research is projected to have several significant impacts, including bridging the skills gap, fostering leadership character development, enhancing graduate quality, equipping students with relevant technological knowledge and expertise, and promoting a curriculum rooted in Islamic spiritual values.
Perbedaan Ekspresi Emosional Terjemahan Mesin dan Manusia: Studi Kasus Google Translate Retno Purwani Sari; Tatan Tawami; Nenden Rikma Dewi; Chepi Nur Albar
Ranah: Jurnal Kajian Bahasa Vol 15, No 1 (2026): Ranah: jurnal Kajian Bahasa
Publisher : Badan Pengembangan dan Pembinaan Bahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26499/rnh.v15i1.8528

Abstract

This study seeks to compare how machine translation (MT) and human translation (HT) convey emotional expressions in Dahl’s Matilda. The study discusses the limitation of neural-network machine translation, such as Google Translate, in fully capturing emotional nuance in literary texts although this technology has contributed significantly to improve translation speed and cross-linguistic accessibility. This study employs a descriptive qualitative with a comparative approach. Character-centered content analysis is applied to examine differences in linguistic accuracy and emotional nuance between MT and HT, translation produced by a professional human translator. The results show that the degree of success between MT and HT varies in preserving interpersonal effect, stylistic nuance, and emotional intensity. The tendency of MT to prioritize lexical and semantic fidelity often weakens expressions with emotional loaded, and reduces the naturalness of dialog. In contrast, HT potentially produces the stylistic dictions with a higher degree of functional equivalence in terms of tenor, mode, and interpersonal function although there may be minor emotional shift, such as the imagery softening, occur. Nevertheless, both MT and HT successfully maintain the ideational meaning and emotional development of Matilda’s characteristics. These findings suggest that the main limitation of MT is in its inability to reproduce the adequate emotional and stylistic dimension of literary texts. MT may serve as a useful translation tool, but human evaluation plays significantly in preserving emotional nuance and communicative depth in literary translation. Abstrak Penelitian ini bertujuan untuk membandingkan bagaimana terjemahan mesin (machine translation, MT) dan terjemahan manusia (human translation, HT) menyampaikan ekspresi emosional dalam novel Matilda karya Roald Dahl. Penelitian ini mendiskusikan keterbatasan sistem terjemahan mesin berbasis neural machine translation, seperti Google Translate, dalam menangkap nuansa emosional secara menyeluruh dalam teks karya sastra, meskipun teknologi ini telah meningkatkan kecepatan data dan aksesibilitas komunikasi lintas bahasa. Penelitian ini menggunakan metode deskriptif kualitatif dengan pendekatan komparatif. Teknik analisis konten yang difokuskan pada karakter Matilda (character-centered analysis), digunakan untuk mengkaji perbedaan akurasi linguistik dan nuansa emosional antara hasil terjemahan MT dan terjemahan penerjemah profesional, HT. Hasil penelitian menunjukkan perbedaan tingkat keberhasilan MT dan HT dalam mempertahankan efek interpersonal, nuansa stilistika, dan intensitas emosional. Kecenderungan MT mempertahankan fidelitas leksikal dan semantik melemahkan ungkapan bermuatan emosional dan kealamian dialog. Sementara itu, pilihan diksi stilistik HT memungkinkan terjemahan mencapai ekuivalensi fungsional yang lebih tinggi dalam aspek tenor, mode, dan fungsi interpersonal meskipun pergeseran emosi minor seperti pelunakan pencitraan kerap terjadi. Namun, secara umum keduanya berhasil mempertahankan makna ideasional dan perkembangan emosi karakter Matilda. Temuan ini menunjukkan keterbatasan MT terletak pada reproduksi dimensi emosional dan stilistika yang menjadi ciri khas teks karya sastra. MT dapat dimanfaatkan sebagai alat bantu awal, sedangkan evaluasi manusia tetap menjadi aspek penting untuk mempertahankan nuansa emosional dan kedalaman komunikasi dalam penerjemahan karya sastra.