Garuda - Garba Rujukan Digital

PEMETAAN DAERAH RAWAN RESIKO GEMPA BUMI BERDASARKAN METODE PROBABILISTIC SEISMIC HAZARD ANALYSIS (PSHA) DAN DATA MIKROTREMOR DI KEPULAUAN NIAS Mitranikasih Laia
Journal of Energy, Material, and Instrumentation Technology Vol 4 No 1 (2023): Journal of Energy, Material, and Instrumentation Technology
Publisher : Departement of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jemit.v4i1.200

UPAYA MENINGKATKAN HASIL BELAJAR IPA SISWA KELAS VIII SMP SWASTA KRISTEN BNKP TELUKDALAM MELALUI STRATEGI PEMBELAJARAN INKUIRI Liberkat Solomasi Hulu; Laia, Mitranikasih; Laia, Askarman
TUNAS : Jurnal Pendidikan Biologi Vol 4 No 2 (2023): TUNAS: Jurnal Pendidikan Biologi
Publisher : Universitas Nias Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57094/tunas.v4i2.1176

The aim of this research is to determine the improvement in the quality and cognitive learning outcomes of students in semester 1 science subjects class VIII-B BNKP Telukdalam Christian Private Middle School for the 2022/2023 academic year through the application of inquiry learning strategies. This research was implemented at BNKP Telukdalam Christian Private Middle School for the 2022/2023 Academic Year. The subjects in this research were students in class VIII-B with a total of 30 students and the object of this research was the application of inquiry learning strategies. Data collection techniques use tests, observation, questionnaires and interviews. The test used is a multiple choice test which is carried out at the end of each cycle. Based on the results of research on improving science learning outcomes through inquiry learning strategies at BNKP Telukdalam Christian Private Middle School in cycle I with the number of students completing 18 people (60%) out of 30 students with an average score of 60.2 while student learning outcomes in cycle II were The number of students who completed was 23 (76.6%) out of 30 students with an average score of 76.6. The results of observations of student activity in the first cycle at the first meeting obtained an average percentage of 54.6% (less) and at the second meeting the first cycle obtained a percentage of 63.2% which was categorized as sufficient while in the second cycle the student activity at the first meeting increased to 72.6% which was in the good category and at the second meeting increased to 83.5% and is classified in the very good category. Meanwhile, the results of questionnaire processing in cycle I obtained a percentage of 65.2%, including the sufficient category, and in cycle II the percentage of questionnaires increased to 76.82% (good). In conclusion: one of the efforts to improve the learning outcomes of class VIII-B students at the BNKP Telukdalam Christian Private Middle School is to implement inquiry learning strategies. Suggestions: 1) In the learning process, teachers should use inquiry learning strategies in science subjects, 2) Subject teachers should pay attention to weaknesses that occur in the implementation of learning.

Klasifikasi Data Gempa Bumi di Pulau Sumatera Menggunakan Algoritma Naïve Bayes Duha, Tobias; Laia, Mitranikasih; Huda, Amirudin Khorul; Jasuma, Agung
Jurnal Informatika Vol 2 No 1 (2023): Jurnal Informatika
Publisher : LPPM Universitas Nias Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57094/ji.v2i1.840

Indonesia is one of the countries located in the Pacific Ring of Fire, where three tectonic plates meet. This makes Indonesia very vulnerable to natural disasters such as earthquakes, volcanic eruptions, and tsunamis. These natural phenomena occur very frequently, as evidenced by events such as those that have occurred on the island of Sumatra. This study aims to classify earthquake data in the Sumatra Islands based on hypocenter using the Naive Bayes Algorithm. The study uses earthquake datasets specifically from the Sumatra Islands, which are divided into training and testing data. The results of the study indicate that classification can be performed using the Naive Bayes Algorithm based on three categories, ranging from shallow earthquakes, moderate earthquakes, to deep earthquakes.

The Application of Artificial Intelligence for Anomaly Detection in Big Data Systems for Decision-Making Octiva, Cut Susan; Suryadi, Dikky; Judijanto, Loso; Laia, Mitranikasih; Irwan, Dedy
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3358

The development of big data technology has generated huge volumes of diverse data, creating challenges in detecting anomalies that could potentially affect decision-making. This research aims to examine the application of artificial intelligence (AI) in detecting anomalies in big data systems to support faster, more accurate and effective decision-making. The approach used includes the integration of machine learning algorithms, such as classification-based detection, clustering, and deep learning, in identifying abnormal patterns in large datasets. The research method involves real-time dataset-based simulations by measuring the performance of AI models using accuracy, precision, recall, and F1-score metrics. The results show that the application of AI can significantly improve the anomaly detection capability compared to conventional methods, with an average accuracy of 92%.

Introduction to Cybersecurity for Teachers and Students in Indonesia in the Digital Era (Pengenalan Keamanan Siber bagi Guru dan Siswa di Indonesia di Era Digital) Octiva, Cut Susan; Rahayu, Novi; Laia, Mitranikasih; Suryadi, Dikky; Hakim, Muhammad Lukman
Indonesia Berdaya Vol 6, No 1 (2025)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.20251004

This Community Service (PKM) activity aims to increase cybersecurity literacy among teachers and students as part of efforts to support digital transformation in education. The training was conducted online with an interactive approach, involving 50 participants from various schools in Indonesia. The material includes an introduction to cyber threats, mitigation strategies, and daily digital security practices. The evaluation was done through pre-test and post-test, accompanied by a participant satisfaction questionnaire. The results showed a significant improvement in participants' understanding, with an average score increase of 73%. The level of satisfaction of participants with the training reached the "excellent" category with an average score of 4.75 on a scale of 5. These findings reflect the effectiveness of the designed training methods. However, the limitations of digital infrastructure are the main challenge in implementing activities. This Activity has contributed positively to building cybersecurity awareness and literacy in the education sector. In addition to providing direct benefits to participants, this program is expected to be a model for similar training that supports the sustainable strengthening of digital literacy in Indonesia.Abstrak. Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan literasi keamanan siber di kalangan guru dan siswa sebagai bagian dari upaya mendukung transformasi digital dalam pendidikan. Pelatihan dilakukan secara daring dengan pendekatan interaktif, melibatkan 50 peserta dari berbagai sekolah di Indonesia. Materi yang diberikan meliputi pengenalan ancaman siber, strategi mitigasi, dan praktik keamanan digital sehari-hari. Evaluasi dilakukan melalui pre-test dan post-test, disertai dengan kuesioner kepuasan peserta. Hasil penelitian menunjukkan adanya peningkatan pemahaman peserta yang signifikan, dengan peningkatan skor rata-rata sebesar 73%. Tingkat kepuasan peserta terhadap pelatihan mencapai kategori “sangat baik” dengan skor rata-rata 4,75 dari skala 5. Temuan ini mencerminkan efektivitas metode pelatihan yang dirancang. Namun, keterbatasan infrastruktur digital menjadi tantangan utama dalam pelaksanaan kegiatan. Kegiatan ini telah memberikan kontribusi positif dalam membangun kesadaran dan literasi keamanan siber di sektor pendidikan. Selain memberikan manfaat langsung kepada peserta, program ini diharapkan dapat menjadi model pelatihan serupa yang mendukung penguatan literasi digital di Indonesia secara berkelanjutan.

Inovasi Terbaru pada Fotokatalis Karbon dalam Meningkatkan Kinerja Fotokatalitik: Systematic Literature Review Mitranikasih Laia
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.6290

Photocatalysis is one of the environmentally friendly technologies with great potential to address global issues related to pollution and the demand for clean energy. However, limitations of conventional photocatalyst materials, such as low light absorption and high electron–hole recombination rates, have hindered optimal efficiency. This review highlights the role of carbon-based materials as the latest innovation in enhancing photocatalytic performance. Various forms of carbon materials, including graphene, carbon nanotubes (CNTs), carbon quantum dots (CQDs), and porous carbon, have been shown to improve charge separation, broaden the light absorption spectrum into the visible region, and enhance the structural stability of photocatalysts. Literature analysis indicates that the integration of carbon with semiconductors significantly increases pollutant degradation efficiency, cycle stability, and the potential application in renewable energy production. Moreover, the utilization of biomass waste as a source of porous carbon opens opportunities for more economical, sustainable, and eco-friendly technologies. This article provides a comprehensive overview of research progress, performance enhancement mechanisms, and future development directions of carbon-based photocatalysts, which are expected to contribute to innovative solutions in the fields of energy and environmental sustainability.

Identifikasi Ketebalan Lapisan Lapuk pada Area Rawan Longsor Menggunakan Metode Seismik Refraksi (Studi Kasus: Desa Kalirejo Kabupaten Kulonprogo) Muhardi Muhardi; Radhitya Perdhana; Muhammad Reza July Utama; Mitranikasih Laia; Tisar Dewi Pratiwi; Randha Ayu Nurwulandari
Jurnal Teori dan Aplikasi Fisika Vol. 8 No. 2 (2020): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v8i2.251

Abstract. Kalirejo Village, Pengasih District, Kulonprogo Regency, is an area that is prone to landslides. The purpose of this study is to identify the weathering layer thickness, which is one of the triggering factors for landslides. This study was conducted using the seismic refraction method by applying two lines. Line 1 uses 24 geophones, has a distance of 1 meter between geophones, while Line 2 uses 24 geophones, has a distance of 2 meters between geophones. The results showed that the velocity of seismic wave propagation in the weathering layer for Line 1 was 400 m/s, and in the slip surface was 2,300 m/s. The weathering layer thickness on Line 1 is 7.6 - 9.8 meters and the slope is steep so that this location is predicted to have a potential landslide. While the velocity of seismic wave propagation in the weathering layer for Line 2 was 300 m/s, and in the slip surface was 2,200 m/s. The weathering layer thickness on Line 2 is at less than 2 meters, so this location is predicted not to have a landslide potential even though the slope is steep

Pengujian Kualitas Air Kemasan Minieral dengan Pengukuran Indeks Biasa Air Menggunakan Metode Difraksi Fraunhofer Tisar Dewi Pratiwi; Radhitya Perdhana; Mitranikasih Laia; Rohmawati Metaningrum
Jurnal Teori dan Aplikasi Fisika Vol. 12 No. 02 (2024): Jurnal Teori dan Aplikasi Fisika
Publisher : Department of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtaf.v12i02.406

On a laboratory scale, water quality measurements generally use the degree of acidity (pH) and wather index. This study aims to implement simple physics equations with the tools we make by applying the principle of light diffraction. One of the parameters to determine the level of water quality can be through the measurement of the water index. We use the single-slit Fraunhofer diffraction method to measure the water index in mineral bottled water, including Tripanca, Grand and Aqua. Then the results are compared with the results of measuring the water index in turbid water. The results we obtained showed that Tripanca bottled water was 1.34 ± 0.16, Grand was 1.36 ± 0.39 and Aqua was 1.32 ± 0.51. Turbid water measurements get a water index value of 1.62 ± 0.003. When compared with the laboratory water index value of 1.33, the average bottled water has a water index that is lower than the laboratory water index, and turbid water has a water index that is greater than the laboratory water index. This is because the greater the value of the refractive index of water, it will inhibit light from entering the water medium, thereby reducing the quality of the water. Keywords: Light diffraction, Refractive index of water, Water Mineral Content, Linear regression.

The Application of Artificial Intelligence for Anomaly Detection in Big Data Systems for Decision-Making Cut Susan Octiva; Dikky Suryadi; Loso Judijanto; Mitranikasih Laia; Dedy Irwan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3358

The development of big data technology has generated huge volumes of diverse data, creating challenges in detecting anomalies that could potentially affect decision-making. This research aims to examine the application of artificial intelligence (AI) in detecting anomalies in big data systems to support faster, more accurate and effective decision-making. The approach used includes the integration of machine learning algorithms, such as classification-based detection, clustering, and deep learning, in identifying abnormal patterns in large datasets. The research method involves real-time dataset-based simulations by measuring the performance of AI models using accuracy, precision, recall, and F1-score metrics. The results show that the application of AI can significantly improve the anomaly detection capability compared to conventional methods, with an average accuracy of 92%.

Analisis Big Data untuk Deteksi Hoaks dan Disinformasi di Platform Berita Online Mitranikasih Laia; Ayuliana; Wasiran; Muhammad Lukman Hakim; Dikky Suryadi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3859

In the digital era, the spread of hoaxes and disinformation on online news platforms is a serious challenge that can affect public opinion and social stability. This research aims to analyze the application of Big Data technology in automatically detecting hoaxes and disinformation. The methods used include data collection from various online news sources, text processing using Natural Language Processing (NLP), and the application of machine learning algorithms to classify news based on their level of credibility. The dataset used includes news from various categories, which are validated with trusted sources. The results show that the combination of Big Data, NLP, and machine learning techniques can improve the accuracy of hoax detection with a high success rate. This study is expected to contribute to the development of a fake news detection system that is more effective and adaptive to the trend of information dissemination in the digital world.

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