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All Journal Jurnal Informatika dan Teknik Elektro Terapan Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Kridatama Sains dan Teknologi
Fallo, Diana Yanni Ariswati
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Social Sciences Other

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Analisis Algoritma Klasifikasi dalam Pembelajaran Sistem Informasi Geografis di Pendidikan Informatika Paju, Benediktus Kurniawan; Fallo, Diana Yanni Ariswati; Mowata, Sergius Erdin
Jurnal Kridatama Sains dan Teknologi Vol 7 No 01 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i01.1676

Abstract

The rapid development of information technology has encouraged the use of spatial data in various fields, including in education. This study aims to analyze the application of classification algorithms in the learning of geographic information systems (GIS) at Citra Bangsa University. The main focus lies in how students understand and implement algorithms such as K-Nearest Neighbor (K-NN), Decision Tree, and Naive Bayes in the context of spatial data. The approach used is descriptive qualitative with data collection techniques through an open questionnaire to 26 students of Citra Bangsa University, who followed project-based GIS learning. The results of the study show that the use of classification algorithms can improve students' understanding of basic GIS concepts, especially in spatial data processing and visualization. And also the results obtained from 26 students with different percentage points for the questionnaire given. Nonetheless, some obstacles were found such as technical difficulties in the data classification process and low initial understanding of algorithm concepts. This study provides an overview of the importance of integrating the concept of algorithms and GIS in the learning process to improve students' competencies in the field of spatial technology
Analisis Pemahaman Mahasiswa Informatika dalam Menyelesaikan Rute Terpendek Menggunakan Algoritma Dijkstra dengan Graf Berbobot Jaiman, Fridolin; Fallo, Diana Yanni Ariswati; Banung, Floriana Letni
Jurnal Kridatama Sains dan Teknologi Vol 7 No 01 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i01.1678

Abstract

The Dijkstra algorithm is one of the shortest path search methods that is widely applied in various fields of computer science, such as digital navigation systems, logistics planning, and computer network optimization. In the context of informatics education, these algorithms are taught to reinforce programming logic and understanding of the structure of weighted graphs. However, the implementation of learning in higher education still faces various challenges, especially the understanding of informatic education students in solving the shortest path problems using the Dijkstra algorithm, as well as developing a learning approach based on case studies ans simulation. The method used is aused is a deskriptive qualitative approcah with data collection techniques in the form of learning obsevations, analysis of student assignment documents, and open questionnaires. The results showed that most students understood the process of initialization and tracing the minimum weight, but encountered difficulties in selecting the next node and tracking the shortest path. Case studies of weighted graphs and manual visualizations have been shown to help students understand and help students understand algorithmic processes more thoroughly. These findings show that real-life case-based learning models and manual simulations are able to improve students’ analytical skills and understanding of the working mechanisms of the Dijkstra algorithm.
Tinjauan Literatur tentang Pemanfaatan Algoritma Greedy untuk Pencarian Jalur Terpendek Dima, Javiardi; Hamzah, Moh. Syukron; Tallo, Clerinzia Gladista; Fallo, Diana Yanni Ariswati
Jurnal Kridatama Sains dan Teknologi Vol 7 No 01 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i01.1683

Abstract

The shortest path problem is a classical issue encountered in various applications such as geographic information systems (GIS), logistics management, transportation planning, and disaster evacuation routing. The Greedy Algorithm offers a simple solution approach that focuses on selecting the best local solution at each decision step, assuming that such local decisions will lead to a globally efficient solution. This research is a systematic literature review discussing the working principles, advantages, limitations, and real-world implementations of the Greedy Algorithm in solving shortest path problems. Based on the reviewed literature, the Greedy Algorithm performs efficiently for problems with low to medium complexity. However, its main limitation lies in its inability to guarantee globally optimal solutions in complex graphs with multiple alternative routes. Several empirical studies have demonstrated that the Greedy Algorithm is effectively utilized in tourist route mapping, parcel delivery systems, urban logistics management, adaptive traffic signal control, and disaster evacuation route planning. Therefore, the Greedy Algorithm remains a practical approach, particularly in systems that require fast computation with limited decision space.
PRESEPSI MAHASISWA TERHADAP SISTEM PEMINJAMAN PROYEKTOR/LCD YANG DIOTOMATISASI DENGAN ALGORITMA PENJADWALAN tahu, Deryanti; Bado, Mariana Wiwin; Fallo, Diana Yanni Ariswati
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6982

Abstract

Pemanfaatan teknologi dalam manajemen fasilitas pendidikan menjadi hal krusial untuk meningkatkan efisiensi dan pelayanan. Penelitian ini bertujuan untuk menganalisis persepsi mahasiswa terhadap sistem peminjaman Proyektor/LCD yang diotomatisasi menggunakan algoritma penjadwalan. Sistem ini dirancang untuk mengatasi berbagai kendala dalam peminjaman manual, seperti bentrokan jadwal, keterlambatan pengambilan, dan kurangnya transparasi dalam alokasi perangkat. Dengan menerapkan algoritma penjadwalan, sisttem secara otomatis menentukan prioritas dan jadwal peminjaman berdasarkan waktu permintaan, durasi penggunaan, serta ketersediaan perangkat. Metode penelitian yang digunakan adalah survei kualitatif terhadap mahasiswa dalam penggunaan sistem. Hasil penelitian ini menunjukkan bahwa mayoritas responden merasa sistem lebih adil, efisien, dan mudah digunakan dibandingkan metode konvesional. Temuan ini menvgindikasikan bahwa otomatisasi berbasis algoritma penjadwalan dapat meningkatkan kualitas layanan peminjaman fasilitas di lingkungan perguruan tinggi.  
PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS AUGMENTED REALITY PADA MATERI TOPOLOGI JARINGAN UNTUK MENINGKATKAN HASIL BELAJAR SISWA KELAS X TJKT SMK NEGERI 1 KUPANG Angelina Heleni Perada Liat; Sogen, Maria Magdalena Beatrice; Fallo, Diana Yanni Ariswati
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 02 (2026): Volume 11 Nomor 02, Juni 2026 Published
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i02.49023

Abstract

This thesis was conducted based on the problem that the learning process in the subject of Basic Computer and Telecommunication Network Engineering at Class X TJKT of SMK Negeri 1 Kupang still relies on conventional learning methods, causing difficulties for students in understanding abstract concepts of network topology and resulting in low learning engagement and varied learning outcomes. This research aims to develop an Augmented Reality-based learning media on network topology materials and to determine its effectiveness in improving student learning outcomes. This thesis employed a Research and Development (R&D) method using the ADDIE model, which consists of Analysis, Design, Development, Implementation, and Evaluation stages. The media was developed using Unity 3D and Vuforia to present interactive three-dimensional visualizations of network devices and learning materials. Data collection techniques included observation, interviews, questionnaires, tests, and documentation. The developed media was validated by media and material experts before implementation in the learning process. The findings indicate that Augmented Reality-based learning media can support a more interactive, engaging, and contextual learning experience, helping students understand network topology concepts more effectively and contributing to improved student learning outcomes.
PENGARUH PENERAPAN DEEP LEARNING TERHADAP PENINGKATAN HASIL BELAJAR SISWA PADA MATA PELAJARAN INFORMATIKA KELAS VIII SMP KRISTEN CITRA BANGSA MANDIRI KUPANG Toulay, Yulce Getruida; Enstein, Jhon; Fallo, Diana Yanni Ariswati
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 Nomor 03, September 2026 Verified
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.64811

Abstract

This study aims to evaluate the effectiveness of implementing the Deep Learning instructional model in improving student learning outcomes in the topic "Applying Computational Thinking" within the Informatics subject. A quantitative approach with a True-Experimental method was employed in this research. Data were gathered through pre-test and post-test instruments administered to both a control group (N = 14) and an experimental group (N = 18).The results indicated that the implementation of the Deep Learning model had a significant effect on student learning outcomes. The mean pre-test score of the experimental group was 36.00, which increased significantly to 87.22 in the post-test. Meanwhile, the control group using traditional lecture-based learning achieved a mean pre-test score of 26.07 and a post-test score of 40.71. Hypothesis testing using an Independent Samples t-Test yielded t_calculated = -11.066 (df = 30) with a 2-tailed significance value of p < 0.001, indicating the rejection of H0 (p < 0.05). The mean difference of 46.452 points and a large effect size (Cohen's d = 3.943) confirm that the Deep Learning model is highly effective in significantly enhancing student skills and learning outcomes.
Co-Authors Angelina Heleni Perada Liat Bado, Mariana Wiwin Banung, Floriana Letni Dima, Javiardi Hamzah, Moh. Syukron Jaiman, Fridolin Jhon Enstein Mowata, Sergius Erdin Paju, Benediktus Kurniawan Sogen, Maria Magdalena Beatrice tahu, Deryanti Tallo, Clerinzia Gladista Toulay, Yulce Getruida