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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Teknik Informatika UNIKA Santo Thomas JUKI : Jurnal Komputer dan Informatika MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Widya Climago Jurnal Pengabdian Masyarakat Nauli
Marzuki, Sinambela
Badan Meteorologi, Klimatologi dan Geofisika
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences Other

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Timeseries forecasting for Local Average Temperature in Northern Sumatera Using Long Short-Term Memory Model Marzuki Sinambela; Maman Sudarisman; Munawar Munawar
JUKI : Jurnal Komputer dan Informatika Vol. 5 No. 2 (2023): JUKI : Jurnal Komputer dan Informatika, Edisi Nopember 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/juki.v5i2.385

Abstract

For better management and planning of water resources in a basin, it is important to understand trends and predict average temperature as one of the parameters of weather and climate data. The study of weather trends using normal and local annual average temperature, comparison and observation. In this study, we will analyse the local and normal average temperature data in the city of Medan, based on the observation station in situ. The main objective of this study is to compare the normal temperature with the local station and to predict the temperature data in the city of Medan, North Sumatra by using the long term short term memory model. Based on the result of normal data science of exploring temperature with local temperature correlation, we got the display of training curve, residual plot and the scatter plot are shown using these codes. The good performance of Kualanamu and better than Deliserdang station had MSE value 0.01 and R2 value 0.98, close to zero represents better prediction quality.
Pendekatan AI dan Data Sains dalam Bencana Geo-Hidrometeorologi di Sumatera Utara Sinambela, Marzuki; Suharini, Yustina Sri
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 1 (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No1.pp152-158

Abstract

Challenges in the era of society 5.0 in disaster mitigation and management in Indonesia encourage the importance of innovation and adaptation to new technologies in dealing with geo-hydrometeorological disasters in North Sumatra, Indonesia. North Sumatra is one of the provinces in Indonesia located in the northwestern part of Sumatra Island. It is an area that has the potential for Geo-Hydrometeorological disasters, whether it comes from earthquakes, floods, strong winds, drought due to climate change, landslides, and others. In this research, disaster management is needed to provide the widest possible information to the community related to mitigation, preparedness, emergency response, and recovery. The purpose of this research is to provide an understanding of geo-hydrometeorological disasters to the people of North Sumatra, Indonesia with AI and Data Science approaches, namely Prediction and Early Warning, risk and vulnerability analysis, monitoring, real-time response, data and information management, and education and public awareness. In general, the development of informatics engineering in geo-hydrometeorology disasters based on AI and Data Science has had a very good impact, both from the code of ethics and ethics of Professional Engineers, Professional and Safety, Occupational Health and Safety, and the Environment. AI and Data Science approaches in engineering practice in the community encourage the handling of geo-hydrometeorological disasters in North Sumatra has great potential to improve the effectiveness of disaster mitigation, response and recovery. Data analysis with AI and data science approaches helps in making policies that are more targeted and effective in disaster risk mitigation. Data Science can be used to analyse disaster impacts and assist in effective recovery planning. It requires data availability, and collecting data post-disaster can be difficult, but it is essential for impact analysis and model improvement.
VISUAL ANALYSIS OF LOCAL EARTHQUAKE IN NORTH TAPANULI BASED ON DATA SCIENCE Sinambela, Marzuki; Darnila, Eva
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp363-367

Abstract

Earthquakes are natural phenomena that occur when the Earth's tectonic plates move and release energy. Big Data's emergent epistemological and research paradigms, as well as data science, an increasingly integrated field of data research, are opening up new opportunities. Visualizing earthquake data is all about understanding earthquake characteristics such as size, location and depth. The result show that September was the quietest month in terms of earthquakes, and in this graph we can see the number of earthquakes for each month in 2022. The month of October is the one that has the highest number of earthquakes. We can see the average depth and magnitude of each year on the bubble chart. In addition, the size and color of the bubbles indicate the number of earthquakes that month. In general, most of the earthquakes occurred in the shallow earthquake range and the 1.8-3.85 magnitude range.
TRANSFORMASI PUBLIKASI STMKG DIGITAL: PENINGKATKAN SUMBER DAYA MANUSIA UNGGUL DAN PERCEPATAN AKREDITASI INSTITUSI Sinambela, Marzuki; Hidayat, Nur; Adi, Suko Prayitno; Sulistya, Widada; Sudarisman, Maman; Riama, Nelly Florida
Majalah Ilmiah METHODA Vol. 13 No. 2 (2023): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol13No2.pp207-216

Abstract

Improving excellent human resources is an initiative that aims to develop and strengthen individual and collective potential within the BMKG (Meteorology, Climatology and Geophysics Agency) organization to make it a leading global player in the fields of meteorology, climatology, geophysics and instrumentation. Excellent human resources in higher education institutions have the potential to conduct quality research and produce quality scientific publications. In this action of change, the integration of the STMKG Digital publication service program, both updating the E-Journal and building the STMKG PRESS publishing media as a single digital-based and indexed account, has been successfully carried out and is the key to the realization of a comprehensive publication information system. The integration of publication services is aimed at improving efficiency and effectiveness in both indexing and digital documents. This transformation will encourage teams involved in this change action plan to collaborate more, effective communication, and writing literacy. The results of this change action are expected to be useful for STMKG's internal interests, namely to facilitate the accreditation preparation process, academic data collection, and the accreditation assessment simulation process. The benefits for BMKG are the implementation of the BMKG 2022-2024 strategic plan and the improvement of superior human resources towards 500 Doctorates and BMKG Global Player.
Experiential learning for the Management of Communication Networks at Ranai Meteorological Station - Natuna Sinaga, Winton; Supandi, Achmad; Setiawan, Elyas; Sinambela, Marzuki
Jurnal Widya Climago Vol 5 No 2 (2023): BMKG Public Service Leadership: Implementation of changes to leadership training
Publisher : Pusdiklat BMKG

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

Abstract

Network management is the process of designing, implementing, monitoring and maintaining computer networks and their associated infrastructure to ensure optimal performance, availability, efficiency, security and reliability of data communications. The implementation of network management is beneficial for security, providing optimal network service quality, reducing downtime and network problems, and ensuring that the network is always available and reliable in disseminating information. Bandwidth management helps to improve the efficiency of network resource utilisation, quality of service optimisation and quality of service improvement. As technology evolves, security policies need to be regularly updated.
Characteristic of Background Seismic Noise of Local Tarutung Earthquake Based on Power Spectral Density and Probabilistic Density Function Method Sinambela, Marzuki; Hartoyo, Puji
JUKI : Jurnal Komputer dan Informatika Vol. 7 No. 1 (2025): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2025
Publisher : Yayasan Kita Menulis

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

Abstract

An evaluation of four broadband BMKG stations' ambient seismic noise is provided. Knowing the seismic ambient noise tiers confirmed by a community of seismic stations is essential for earthquake monitoring and detection purposes in the Sumatra area. Waveform records from May 2020 are used to calculate the power spectral density and likelihood density characteristic (PSDPDF) for a single day when an excessive noise stage is detected. This study aims to assess the vertical channel of waveform data using waveform information in miniSEED and SAC architecture. Because of their low probability of occurrence, the method used permits the use of data contaminated with earthquakes (a 4.8 magnitude earthquake occurred on May 11, 2020, at Tarutung, North Sumatera, Indonesia) and other demanding signals. The results obtained are extremely important for assessing the overall performance of the current seismic broadband stations, evaluating the web page resolution of new stations, and modifying the detection settings for the computerized processing machine in the Indonesia Seismic Network. Compared to TTSM, TKSM, and RSSM stations, the noise at LSTM stations is weaker, but the likelihood of an increase increases at high frequencies. Cultural noise in human endeavors produces certain noise and fluctuation over extended periods of time, which is typically certified for the process of earthquake signals
Pengenalan Aplikasi Kahoot! Bagi Guru Dan Siswa-Siswi Pada SMA GKPI Padang Bulan Medan Larosa, FGN Larosa; Sitepu, Surianto; Saragih, Naikson F.; Situmorang, Alfonsus; Dumayanti, Imelda Sri; Naibaho, Jimmy F.; Manurung, Samuel; Jaya, Indra Kelana; Yohanna, Margaretha; Rumahorbo, Benget; Simanullang, Harlen; Sinambela, Marzuki; Silalahi, Veraci
Jurnal Pengabdian Masyarakat Nauli Vol. 2 No. 1 (2023): Agustus, Jurnal Pengabdian Masyarakat Nauli
Publisher : Marcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/nauli.v2i1.102

Abstract

interaksi antar personal, yang mempengaruhi interaksi antara guru/pendidik dengan siswa-siswi, bersifat praktis, menarik dan mudah dibawa-bawa, sangat populer, dan banyak dipakai pada pembelajaran dengan metode Blended Learning. Salah satu aplikasi yang dimaksud adalah Kahoot!, yang sangat mudah dalam pemasangan bahkan gratis. Kahoot! mulai menyebar ke berbagai pembelajaran seperti Bahasa Indonesia, Bahasa Inggris, dan Kimia. Hasil penelitian menunjukkan bahwa Kahoot! mampu tampil sebagai media permainan digital berbasis pembelajaran, di mana Kahoot! memberikan persepsi positif dalam efektivitas pembelajaran, ketertarikan dalam aktvitas pembelajaran dan motivasi dalam aktivitas pembelajaran
Classification of Labor Using Support Vector Machine in North Sumatera Ritonga, Anggiat P; Adithya, Andri Ramadhan; Agustina, Idri; Limbong, Tonni; Sinambela, Marzuki
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 4 No 2: Tahun 2019
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (610.001 KB) | DOI: 10.17605/jti.v4i2.658

Abstract

Labor markets in Indonesia are key challenges and policy issues. Balai Besar Pengembangan Latihan Kerja (BBPLK) Medan is a services unit to develop and implementation of labor to increase skill and knowledge. The classification of labor in North Sumatera is very interesting to evaluate the performance of the labor in North Sumatera. In this case, we compute the labor data to classify and evaluate the model and performance of the dataset. The computation of the dataset using the support vector machine (SVM) as a model in machine learning or probabilistic approach by training and test data. The data was collected from Badan Pusat Statistik (BPS) Sumatera Utara for 2018 samples. Labor force dataset in North Sumatera had been computed and shown the result, indicates the support vector machine classifier is the good algorithm for this classification problem, offering good values in terms of accuracy, for describe the labor force in North Sumatera and can be recommended to BBPLK to add more development and implementation.
Prediction of Domestic Passengers at Kualanamu International Airport Using Long Short Term Memory Network Sunardi, Sunardi; Dwiyanto, Dwiyanto; Sinambela, Marzuki; Jamaluddin, Jamaluddin; Manalu, Darwis Robinson
MEANS (Media Informasi Analisa dan Sistem) Volume 4 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (366.293 KB) | DOI: 10.54367/means.v4i2.566

Abstract

Domestic passenger forecasting provides key input into decisions of daily operation management and infrastructure planning of airports and air navigation services and for aircraft ordering and design. Planning for the future is one of the most important keys to success, forecasting is the way. The goal of this study to predict the number of domestic passengers at Kualanamu International Airport. The time-series data were employed from Badan Pusat Statistik (BPS). The result is then discussed in the context of the potential use of the proposed for a new perspective for the predicting of domestic passengers at Kualanamu International Airport, Indonesia. The machine learning approach using long short term memory (LSTM) presents a useful way of observing the domestic passenger predict the passenger time series.
A Review of Digital Image Classification Based on Fuzzy Logic Sinambela, Marzuki; Rahayu, Teguh; Darnila, Eva; Limbong, Tonni
MEANS (Media Informasi Analisa dan Sistem) Volume 5 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.127 KB) | DOI: 10.54367/means.v5i1.704

Abstract

Fuzzy logic has long been an important issue for in the field of computer science, computer vision, image processing, machine learning and control theory and mathematics. In this review paper, we also see that the basics of fuzzy logic as well as fuzzy logic system (Fuzzy Inference System) use as decision making technique under a linguistic view of fuzzy sets. In this study, we focused to review the fuzzy logic to classification of digital image. The aim of this study was to review the fuzzy logic algorithm for classification of image.
Co-Authors Adi, Suko Prayitno Adithya, Andri Ramadhan Agustina, Idri Albertus Tua Simanullang Alexander F.T Parera Bertalina Sihotang Darwis Robinson Manalu Dumayanti, Imelda Sri Dwiyanto . Emerson Limbong Eva Darnila Eva Darnila eva darnila, eva darnila Hadi, Ahmad Fauzi Faishal Hartoyo, Puji Indra Kelana Jaya Jamaluddin Jamaluddin Jamaluddin, Jamaluddin Janner Simarmata Larosa, FGN Larosa Maman Sudarisman Manurung, Samuel Margono Mira Hestina Ginting Munawar Munawar Naibaho, Jimmy F. Niken Woro Palupi Nur Hidayat Patra Mesiari Tarigan Rachmawardani, Agustina Rahayu, Teguh RB. Yanuar Harry W Riama, Nelly Florida Ritonga, Anggiat P Rumahorbo, Benget Saragih, Naikson F. Setiawan, Elyas Silalahi, Veraci Simanullang, Harlen Sinaga, Winton Sudarisman, Maman SUHARINI, YUSTINA SRI Sunardi Sunardi Sunardi, Sunardi Supandi, Achmad Surianto Sitepu Teguh Rahayu Teguh Rahayu TONNI LIMBONG Trihadi, Edward Widada Sulistya Wisnu Wardono Yohanna, Margaretha Yosvin Apriando