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PREDIKSI JARAK TEMPUH KAPAL MOTOR SANGIANG MENGGUNAKAN SUPERVISED MACHINE LEARNING Afrioni Roma Rio; Berton Maruli Siahaan
Journal of Engineering, Computer Science and Information Technology (JECSIT) Vol 2, No 2 (2022): Volume 2 Nomor 2, Oktober 2022
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jecsit.v2i2.249

As a maritime nation with thousands of islands and a vast sea area, sea transportation is the most effective transportation used by the people of Indonesia. A motorboat is one type of maritime transportation that is used to move people or commodities. In this article, we will discuss predicting the daily mileage of one of the motorboats, the Sangiang, which travels from Bitung to Ternate. Three independent variables, Anchor Time (minutes), Speed (knots/hour), and Sailing Time (minutes), are used in supervised machine learning techniques to estimate the daily mileage (mile). Of the various methods evaluated, the multiple regression model was found to be the most accurate at forecasting the Sangiang motorboat’s daily mileage.

Pengaruh Miopi Terhadap Aktivitas Gelombang Alfa pada Otak di Area Oksipital Ernawatil Gani; Mahendra Kusuma Nugraha; Afrioni Roma Rio
Jurnal MIPA Vol. 13 No. 2 (2024): Cover
Publisher : Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/jm.v13i2.56125

Miopi merupakan kondisi mata seseorang yang mengalami kesulitan dalam mengamati objek yang jauh dengan jelas. Kondisi ini akan mempengaruhi kerja sistem saraf di otak. Sistem saraf di otak dapat diketahui melalui beberapa aktivitas gelombang salah satunya gelombang alfa. Gelombang ini berhubngan dengan kemampuan mata memvisualisasikan suatu benda. Sehingga, penelitian ini bertujuan untuk menganalisis kondisi sinyal alfa di otak khususnya area oksipital pada penderita miopi menggunakan metode Power Spectral Density (PSD). Sebanyak tujuh peserta direkam menggunakan EEG Emotiv Epoc masing-masing selama 5 menit dengan mata terbuka tanpa kacamata dan dengan kacamata. Data EEG diolah melalui filtering, rejecting artefak, dan analisis PSD dengan metode Periodogram Welch menggunakan Python. Hasil menunjukkan perbedaan signifikan dalam distribusi daya frekuensi antara area oksipital pada otak bagian kiri (O1) dan bagian kanan (O2), dengan aktivitas alfa yang lebih dominan dan konsisten di O2 pada frekuensi 10-11 Hz. Dengan demikian, kondisi ini mengindikasikan aktivitas neural yang lebih intens di oksipital kanan pada penderita miopi, mungkin sebagai bentuk kompensasi atau adaptasi dalam pemrosesan visual. Analisis lebih lanjut diperlukan untuk memahami implikasi penuh dari aktivitas neural ini dan untuk memastikan hasil yang lebih valid melalui teknik pengolahan sinyal yang lebih canggih. Myopia is a condition in which a person's eyes have difficulty seeing distant objects clearly, affecting the neural system's function in the brain. The nervous system of the brain can be identified through several wave activities, including alpha waves, which are related to the eye's ability to visualize objects. Therefore, this study aims to analyze the condition of alpha signals in the brain, specifically in the occipital area, of individuals with myopia using the Power Spectral Density (PSD) method. Seven participants were recorded using the EEG Emotiv Epoc for 5 minutes each with eyes open, both with and without glasses. The EEG data was processed through filtering, artifact rejection, and PSD analysis using the Welch Periodogram method in Python. The results showed significant differences in the frequency power distribution between the occipital on the left side of the brain (O1) and on the right side (O2), with more dominant and consistent alpha activity in O2 at 10-11 Hz. This indicates more intense neural activity in the right occipital region in myopic individuals, possibly as a form of compensation or adaptation in visual processing. Further analysis is required to fully understand the implications of this neural activity and to ensure more valid results through advanced signal processing techniques.

Pemetaan Potensi Energi Matahari di Sulawesi Utara menggunakan Machine Learning K-Means Afrioni Roma Rio; Berton Maruli Siahaan; Ernawatil Gani
Jurnal MIPA Vol. 14 No. 1 (2024): Artikel
Publisher : Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/jm.v14i2.57778

Penelitian ini mengkaji potensi energi matahari di Sulawesi Utara dengan menganalisis parameter lingkungan seperti suhu, kelembaban relatif, jumlah awan, dan radiasi matahari selama periode 2018 hingga 2022. Metode machine learning K-Means digunakan untuk mengelompokkan data secara optimal, dengan penentuan jumlah klaster terbaik melalui metode siku. Penggunaan machine learning ini penting untuk menangani data yang besar dan kompleks, serta mengidentifikasi pola tersembunyi yang membantu pemetaan potensi energi matahari. Hasil analisis menunjukkan bahwa Klaster 2, yang terdiri dari wilayah dengan suhu tinggi dan radiasi matahari yang optimal, memiliki potensi terbesar untuk instalasi tenaga surya skala besar, didukung oleh infrastruktur tenaga surya yang sudah ada di wilayah pada klaster tersebut. Penelitian ini menghasilkan peta energi surya hingga tingkat desa, yang dapat digunakan untuk pengembangan energi surya di Sulawesi Utara This study examines the solar energy potential in North Sulawesi by analyzing environmental parameters such as temperature, relative humidity, cloud cover, and solar irradiance over the period of 2018 to 2022. The machine learning K-means method was used to optimally cluster the data, with the best number of clusters determined through the elbow method. The use of machine learning is important for handling large and complex datasets, as well as identifying hidden patterns that aid in mapping solar energy potential. The analysis results show that Cluster 2, which consists of areas with high temperatures and optimal solar irradiance, has the greatest potential for large-scale solar power installations, supported by existing solar infrastructure in the region. This study produces a detailed solar energy map down to the village level, which can be used for the development of solar energy in North Sulawesi

Penentuan Nilai Koefisien Restitusi Kelereng Kaca menggunakan Metode Pencitraan Jeda Waktu Sederhana Mahendra Kusuma Nugraha; Ernawatil Gani; Berton Maruli Siahaan; Afrioni Roma Rio
JFT : Jurnal Fisika dan Terapannya Vol 10 No 2 (2023): DESEMBER
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jft.v10i2.36479

Time-lapse imaging has been performed to observe the physical phenomena of imperfect elastic collisions between a glass marble and a tiled floor surface. The glass marble is dropped at a certain height until it hits the floor and experiences repeated rebounds. The event was recorded using the Infinix® Hot S3 smartphone device camera with a shutter speed of 30 frames per second. Analysis of time lapse photography is then carried out using the frame splitting method which is then observed visually to determine the height of each reflection that occurs. The results of the analysis and measurement of the maximum height for the initial state, the first bounce state and the second bounce state are respectively: 15.7 cm, 13.65 cm and 11.45 cm. The coefficient of restitution of glass marbles—based on the data obtained—at the initial maximum height ( towards the first reflection ( ) is ± 0.93242 and the first reflection ( ) towards the second reflection ( ) is equal to. ±0.91587. These results prove that the interaction that occurs is an imperfect elastic collision interaction due to . Keywords: marble, maximum height, restiution coefficient, time-lapse imaging.

Agglomerative Clustering of 2022 Earthquakes in North Sulawesi, Indonesia Rio, Afrioni Roma; Siahaan, Berton Maruli
Buana Information Technology and Computer Sciences (BIT and CS) Vol 4 No 2 (2023): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v4i2.5361

This paper presents a cluster analysis of earthquake data in the surrounding region of North Sulawesi, Indonesia. The dataset comprises seismic data recorded throughout the year 2022, obtained from the BMKG earthquake repository. A total of 211 earthquakes were included in the analysis, with a minimum magnitude threshold of 2.5 and a maximum depth of 300 km. The agglomerative clustering technique, combined with the elbow method, was employed to determine the optimal and distinct number of clusters. As a result, four unique clusters were identified. Cluster 1 exhibited high magnitudes, with an average magnitude of 4.4, and shallow depths, averaging at 20 km. Cluster 2 also had high magnitudes, averaging at 4.4, but deeper depths, with an average of 199 km. Cluster 3 consisted of earthquakes with low magnitudes, averaging at 3.4, and shallow depths, averaging at 21 km. Lastly, Cluster 4 comprised earthquakes with low magnitudes, averaging at 3.4, but deeper depths, with an average of 136 km. Among the 211 earthquakes, 29 were assigned to Cluster 1, 39 to Cluster 2, 100 to Cluster 3, which had the highest population, and 43 to Cluster 4. This study provides valuable insights into the clustering patterns and characteristics of earthquakes in the region, contributing to a better understanding of seismic activity in North Sulawesi, Indonesia

Strain-Induced Control of Magnetic Anisotropy Energy in NbS2 Monolayer: First-Principles Study Berton Maruli Siahaan; Afrioni Roma Rio
Jurnal Fisika Unand Vol 12 No 4 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.12.4.667-674.2023

In this work, we investigate the strain controllability of magnetic anisotropy energy (MAE) in the monolayer form of niobium disulfide (NbS2) using density functional theory (DFT). Our calculation reveals a negative MAE of -1.82 meV, indicating a preference for spins to align in the in-plane directions (x or y). By systematically applying biaxial tensile strain to the NbS2 monolayer, ranging from 1% to 10%, we observe a linear relationship between strain and MAE. Interestingly, the strain-induced modulation of MAE leads to a remarkable phenomenon, where the easy axis of magnetization shifts from the in-plane to an out-of-plane orientation at a critical strain of 7%. This ability to switch the magnetic anisotropy by manipulating strain demonstrates the promising potential of NbS2 monolayer in the development of spintronic devices.

The Effect of Myopia on Brain Signals: Insights from EEG Studies Gani, Ernawatil; Rio, Afrioni Roma; Nugraha, Mahendra Kusuma; Haryanto, Freddy
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Vol. 14 No. 1 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v14n1.p19-32

Refractive vision disorders, such as myopia, can significantly influence an individual's cognitive performance, particularly their ability to perceive and interpret visual stimuli. Myopia, a common refractive error affecting children and adults, can be assessed using various methods, including electroencephalography (EEG). The primary objective of this investigation was to identify distinctive brain signals associated with myopia. This study delves into analyzing brain signals in myopic individuals by employing EEG data and spectral entropy analysis through MNE-Python. EEG data were collected from five myopic participants during a 10-minute session, both with and without their corrective glasses. The collected data underwent preprocessing and power spectral density calculations. Subsequently, spectral entropy analysis was employed to assess the complexity and distribution skewness of EEG frequency patterns. The results of this study revealed notable differences in brain activity, particularly in the occipital region, between individuals wearing glasses and those without them. This variance could be attributed to the enhanced visual clarity experienced by individuals wearing glasses, enabling them to perceive better and process the visual stimuli presented in the study videos. Specifically, spectral entropy values were lower in children without glasses (averaging 1.0) than those with glasses (averaging 3.5), indicating a higher degree of irregularity in the brain activity of myopic children who do not wear corrective eyewear. In conclusion, this study indicates an increase in brain activity irregularities among children without glasses. The findings suggest that specific factors, such as blinking and hand movements, play a role in exacerbating this irregularity. These findings reveal how myopia affects brainwave patterns and indicate that EEG and spectral entropy analysis can enhance our understanding of refractive vision disorders.

Strain-Induced Control of Magnetic Anisotropy Energy in NbS2 Monolayer: First-Principles Study Berton Maruli Siahaan; Afrioni Roma Rio
Jurnal Fisika Unand Vol 12 No 4 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.12.4.667-674.2023

In this work, we investigate the strain controllability of magnetic anisotropy energy (MAE) in the monolayer form of niobium disulfide (NbS2) using density functional theory (DFT). Our calculation reveals a negative MAE of -1.82 meV, indicating a preference for spins to align in the in-plane directions (x or y). By systematically applying biaxial tensile strain to the NbS2 monolayer, ranging from 1% to 10%, we observe a linear relationship between strain and MAE. Interestingly, the strain-induced modulation of MAE leads to a remarkable phenomenon, where the easy axis of magnetization shifts from the in-plane to an out-of-plane orientation at a critical strain of 7%. This ability to switch the magnetic anisotropy by manipulating strain demonstrates the promising potential of NbS2 monolayer in the development of spintronic devices.

Penentuan Nilai Koefisien Restitusi Kelereng Kaca menggunakan Metode Pencitraan Jeda Waktu Sederhana Mahendra Kusuma Nugraha; Ernawatil Gani; Afrioni Roma Rio; Berton M. Siahaan
Jurnal Lentera: Penelitian dan Pengabdian Masyarakat Vol. 4 No. 1 (2023): Jurnal Lentera - Penelitian dan Pengabdian Masyarakat
Publisher : Yayasan Bina Lentera Insan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57207/wgjaya09

Pencitraan jeda waktu (time-lapse imaging) telah dilakukan untuk mengamati fenomena fisis tumbukan lenting tidak sempurna antara kelereng kaca dengan permukaan lantai ubin. Kelereng kaca dijatuhkan pada ketinggian tertentu hingga menumbuk permukaan lantai dan mengalami pemantulan berulang. Kejadian tersebut direkam menggunakan kamera perangkat ponsel pintar Infinix® Hot S3 dengan kecepatan kerangka per detik adalah 30 kerangka. Analisis fotografi jeda waktu kemudian dilakukan dengan metode pemisahan kerangka (frame splitting) yang kemudian diamati secara visual untuk menentukan ketinggian setiap pantulan yang terjadi. Hasil analisis dan pengukuran tinggi maksimum untuk keadaan awal, keadaan pantulan pertama dan keadaan pantulan kedua masing-masing: 15.7 cm, 13,65 cm dan 11,45 cm. Angka koefisien restitusi kelereng kaca—berdasarkan data yang diperoleh—pada ketinggian maksimum mula-mula (????0) menuju pantulan pertama (????1) adalah sebesar ± 0,93242 dan pantulan pertama (????1) menuju pantulan kedua (????2) adalah sebesar. ± 0,91587. Perolehan tersebut membuktikan bahwa interaksi yang terjadi adalah interaksi tumbukan lenting tak sempurna dikarenakan ????≠1.

Analisis Tren Suhu Radiasi Matahari Periode Maret – April 2023 di Kota Manado Berton Maruli Siahaan; Afrioni Roma Rio
Jurnal Lentera: Penelitian dan Pengabdian Masyarakat Vol. 4 No. 1 (2023): Jurnal Lentera - Penelitian dan Pengabdian Masyarakat
Publisher : Yayasan Bina Lentera Insan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57207/76tn7j24

Penelitian ini bertujuan untuk melakukan analisis potensi energi surya di Kota Manado berdasarkan suhu radiasi matahari. Suhu radiasi matahari dianggap sebagai faktor kunci dalam menentukan potensi energi surya yang dapat dihasilkan. Dalam penelitian ini, dilakukan analisis terhadap data suhu radiasi matahari yang diperoleh dengan mengumpulkan data sekunder dari website satelit. Metode analisis yang melibatkan pengolahan data rata-rata suhu radiasi matahari pada periode Maret-April 2023 yang diukur pada rentang waktu berbeda yaitu pukul 10.00, 11.00, 12.00, 13.00 dan 14.00 yang digunakan untuk memperoleh pemahaman yang mendalam tentang potensi energi surya yang dapat diekstraksi dari sinar matahari di wilayah tersebut. Hasil penelitian ini menunjukkan bahwa suhu radiasi matahari pada bulan Maret meningkat pada pukul 11.00 hingga 12.00, tetapi pada pukul 12.00 hingga pukul 14.00 suhu radiasi matahari berada pada nilai yang sama sebesar 30,850C, sedangkan pada bulan April juga terjadi peningkatan suhu radiasi matahari pada pukul 11.00 hingga pukul 12.00, dan memiliki nilai suhu radiasi matahari yang sama pada pukul 12.00 hingga pukul 14.00 yaitu sekitar 31,910C. Hasil penilaian potensi ini dapat digunakan sebagai dasar untuk merencanakan dan mengembangkan sistem energi surya yang optimal di Kota Manado.

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