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All Journal Lingua Cultura Jurnal Khatulistiwa Informatika JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI
Rahmi Yulia Ningsih
Universitas Bina Nusantara
Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Linguistic Creativity of the Indonesian for Foreign Speakers (BIPA) Students at the Morphological, Syntactic, and Semantic Levels Rahmi Yulia Ningsih; Zainal Rafli; Endry Boeriswati
Lingua Cultura Vol. 15 No. 2 (2021): Lingua Cultura
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/lc.v15i2.7613

Abstract

The research aimed to describe the forms of linguistic creativity of BIPA students at the morphological, syntactic, and semantic levels. The research method used was descriptive qualitative with content analysis techniques. The research data were 78 sentences written by BIPA students at Bina Nusantara University academic year 2020/2021. The results show that BIPA students’ sentences have linguistic creativity in the form of the morphological, syntactic, and semantic levels sentences. At the morphological level, the process of linguistic creativity in words is carried out by (1) inserting foreign terms into sentences, (2) using non-standard words, and (3) abbreviating words. While in phrases, linguistic creativity is done by (1) reversing the structure of the phrase, (2) forming nominal phrases with less common word pairs, and (3) forming nominal phrases by incorporating elements of student culture. At the syntactic level, linguistic creativity is carried out in the form of compiling compound sentences with the expansion of descriptions, expansion of objects, expansion of subjects, and expansion of predicates. At the semantic level, linguistic creativity is manifested in the form of the figure of speech: personification, simile, hyperbole, repetition, and metaphor.
ANALISIS FITUR-FITUR DARI BERBAGAI APLIKASI PENCARI PEKERJAAN Valina Evelyn Pranoto; Neisya Holly Santoso; Abraham Mahayana Setiawan; Felix Gustino Tjuatja; Shaquille Ditama Putra; Rahmi Yulia Ningsih; Chairani Putri Pratiwi
Jurnal Khatulistiwa Informatika Vol 11, No 1 (2023): Periode Juni 2023
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jki.v11i1.14409

Abstract

Aplikasi pencari pekerjaan adalah salah satu jenis aplikasi yang sedang populer di berbagai negara. Namun, pemakaian aplikasi pencari pekerjaan oleh masyarakat Indonesia masih belum optimal. Adapun penelitian ini dilakukan untuk menganalisis permasalahan tersebut. Penelitian memiliki tujuan untuk membantu para pengembang aplikasi pencari pekerjaan dalam mempertimbangkan fitur yang dihadirkan. Melalui metode studi literatur dan analisis isi, peneliti memaparkan fitur-fitur yang dimiliki oleh berbagai aplikasi pencari pekerjaan, yaitu LinkedIn, Kalibrr, dan Jobstreet serta mengidentifikasi keunggulan dan kelemahan fitur tersebut. Berdasarkan penelitian yang dilakukan, diperoleh hasil bahwa fitur Filter dan Reccomended Jobs dihadirkan oleh kebanyakan aplikasi pencari kerja. Tidak hanya itu, beberapa fitur diantaranya ATS, Company Review, Course, Resume Templates, dan Discussion Forum juga turut ambil andil dalam penyuksesan aplikasi pencari pekerjaan yang telah ada saat ini. Peneliti juga memberikan saran pengembangan fitur dan sejumlah rekomendasi fitur untuk pengembangan aplikasi pencari pekerjaan. Rekomendasi fitur tersebut, yakni fitur Expert Class dan Career Consultant yang dilengkapi dengan fitur Starred and Notification. Dengan adanya analisis fitur-fitur serta rekomendasi dari peneliti, para pengembang aplikasi pencari pekerjaan diharapkan dapat mempertimbangkan hasil analisis untuk menuangkan inovasi mereka agar aplikasi pencari pekerjaan bisa menjadi lebih baik dan dapat mengatasi masalah pengangguran di Indonesia.
PERANCANGAN MODEL YOLOv8-LSTM UNTUK DETEKSI GERAKAN ANOMALI Frolentika Frolentika; Hebert Karsten Juwono; Luigi Emiliandra; Kevin Pierre Rafael Sabran; Windy Sulistiawati; Rahmi Yulia Ningsih
PENDIDIKAN SAINS DAN TEKNOLOGI Vol 13 No 1 (2026): in Press
Publisher : STKIP PGRI Situbondo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47668/edusaintek.v13i1.2092

Abstract

Manual monitoring of CCTV systems for detecting anomalous movements, such as criminal activity, is highly inefficient and prone to human error, thus urging the need for automated surveillance systems. A key research gap is that most object detection models (spatial in nature) fail to understand the temporal context (movement patterns over time) which is key to distinguishing normal and anomalous activities. This study proposes the design of a hybrid deep learning model YOLOv8-LSTM to address this issue. Using the 4D R&D (Define, Design, Develop) research methodology, an architecture is designed in which YOLOv8 (yolov8m) functions as a spatial feature extractor (generating a 106-dimensional vector) from each video frame. The sequence of these features is then analyzed using a Bidirectional Long Short- Term Memory (Bi-LSTM) equipped with an Attention Pooling mechanism to model temporal dependencies and classify movements. The prototype test results on the test set show strong performance, achieving an AUC of 0.8646 and an F1-Score of 0.6530. Qualitative analysis through 3D latent space visualization successfully demonstrated the model's effectiveness: initially overlapping spatial features (YOLOv8 input) were successfully mapped into clearly separated clusters of normal and anomalous classes (LSTM output). This study validates that the proposed hybrid architecture effectively combines spatial and temporal understanding for accurate anomalous motion detection.
Co-Authors Abraham Mahayana Setiawan Chairani Putri Pratiwi Endry Boeriswati Felix Gustino Tjuatja Frolentika Frolentika Hebert Karsten Juwono Kevin Pierre Rafael Sabran Luigi Emiliandra Neisya Holly Santoso Shaquille Ditama Putra Valina Evelyn Pranoto Windy Sulistiawati Zainal Rafli, Zainal