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All Journal Jurnal Pendidikan Teknologi dan Kejuruan JTEV (Jurnal Teknik Elektro dan Vokasional Jurnal Informatika Upgris Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MANAJEMEN MOTIVASI JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal BIOEDUIN : Program Studi Pendidikan Biologi Jurnal Basicedu MAJU : Jurnal Ilmiah Pendidikan Matematika Majalah Ilmiah UNIKOM EDUKATIF : JURNAL ILMU PENDIDIKAN Building of Informatics, Technology and Science Informatika EDUTEC : Journal of Education And Technology Journal of Computer System and Informatics (JoSYC) U-NET Jurnal Teknik Informatika Tematik : Jurnal Teknologi Informasi Komunikasi Journal of Informatics Management and Information Technology Journal of Social Responsibility Projects by Higher Education Forum Bulletin of Information Technology (BIT) Jurnal Basicedu Proceeding Applied Business and Engineering Conference Journal of Systems Engineering and Information Technology Jurnal Pendidikan MIPA
Ronal Watrianthos
Universitas Al Washliyah Labuhanbatu
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Implementasi Model Hybrid CNN-LSTM untuk Optimasi Pengalaman Pengguna Perangkat Seluler Yuhefizar; Ismael; Arif Rizki Marsa; Dedi Mardianto; Ronal Watrianthos
TEMATIK Vol. 11 No. 2 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Desember 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i2.2125

Abstract

This research employs a convolutional neural network (CNN) with long short-term memory (LSTM) to analyse and predict the behaviour of users of mobile devices, utilising a dataset comprising 700 users. The model combines the strengths of convolutional neural networks (CNNs) in spatial feature extraction and long short-term memory (LSTM) networks in temporal sequential analysis. The results demonstrate that the model exhibits excellent performance, with 92% accuracy, 89% precision, 91% recall, and 90% F1 score. The temporal pattern analysis revealed significant variation between the user classes, with the intensive class showing consistently high usage, averaging 300 minutes per day. The key factors influencing the user experience were identified as app usage time (25%), screen on time (22%), and battery consumption (18%). The segmentation of users resulted in the identification of five distinct groups, with Segment 2 exhibiting the highest usage level (6.2 hours per day) and Segment 5 displaying the lowest (1.3 hours per day). The strong correlation (0.89) between app usage time and screen time serves to confirm the importance of optimising the performance of apps. These findings provide a basis for more effective service personalisation and more targeted app development, thereby paving the way for the optimisation of the user experience on mobile devices.
Mapping Digital Business Innovation: A Bibliometric Analysis of SDG Integration Yuhefizar, Yuhefizar; Watrianthos, Ronal
ABEC Indonesia Vol. 12 (2024): 12th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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

Abstract

This study investigates how research in digital business innovation has evolved to incorporate sustainabilityobjectives through a systematic analysis of academic literature from 2016 to 2024. The research employs a comprehensivebibliometric approach to analyze 1,627 documents from 684 sources in the Scopus database, focusing on publicationpatterns, thematic evolution, and emerging research directions. The analysis reveals three distinct phases in the field's development: foundation (2016-2018), integration (2019-2021), and transformation (2022-2024). Publication volumesshow significant growth from 7 articles in 2016 to 482 in 2024, with a marked acceleration following the COVID-19pandemic. Research themes cluster around three main areas: digital business innovation (572 publications), economicstability (245 publications), and sustainability implementation (156 publications). Core integration themes focus onenvironmental, social, and governance (ESG) implementation and green innovation, while emerging areas emphasizeartificial intelligence applications and circular economy principles. The findings demonstrate a clear shift from technologyfocused approaches to integrated frameworks that align digital transformation with sustainability goals. Analysis ofresearch patterns reveals increasing emphasis on ESG integration (16.8% of recent publications) and sustainable businessmodels, though significant gaps remain in standardization and long-term impact measurement. This study contributes tounderstanding how organizations can effectively combine digital innovation with sustainability objectives, highlightingopportunities for future research in measurement frameworks and ethical implementation guidelines.
A Text Mining Approach to Analyzing the Role of Negative Sentiment Words in News Articles on Suicide and Related Incidents Subagio, Selamat; Samsir, Samsir; Dalimunthe, Abdul Hakim; Ronal Watrianthos
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1745

Abstract

This study examines the role of negative sentiment words in news media coverage of suicide and related incidents through analysis of 1,515 news articles published between 2019 and 2024. Using advanced text mining techniques and sentiment analysis, we investigated patterns in emotional language use and their impact on public discourse. The research revealed frequent usage of negative sentiment words such as "crisis" (256 occurrences), "despair" (214 occurrences), and "death" (189 occurrences), which significantly influenced the emotional framing of these sensitive topics. Statistical analysis showed strong correlations between negative sentiment words and mental health-related terms (correlation value 0.75), indicating consistent patterns in media narrative construction. Temporal analysis identified a notable increase in negative sentiment during the COVID-19 pandemic (2020-2021), followed by a shift toward more solution-focused coverage in 2022-2024. The findings suggest that while negative sentiment words are inherent in covering suicide-related topics, their use can be balanced with solution-oriented language to promote more responsible reporting. This research contributes to understanding how emotional language shapes public discourse on mental health crises and provides insights for developing more effective guidelines for responsible journalism.
Machine Learning-Driven Sentiment Analysis of Social Media Data in the 2024 U.S. Presidential Race Samsir, Samsir; Ritonga, Wahyu Azhar; Aditiya, Rahmad; Watrianthos, Ronal
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1762

Abstract

This study investigates public sentiment patterns during the 2024 U.S. Presidential Race through machine learning analysis of social media data from X (formerly Twitter). Using a dataset of 500 annotated tweets collected from Kaggle, we employ BERT-based sentiment analysis, temporal engagement tracking, and Latent Dirichlet Allocation (LDA) topic modeling to examine discourse across five major candidates. The analysis reveals predominantly positive sentiment (54.2%) in political discussions, with established party candidates receiving higher positive engagement. Temporal analysis demonstrates strong correlations between major campaign events and public engagement, with presidential debates generating peak interaction levels. Topic modeling identifies five key themes driving voter discourse: economic policy, healthcare, climate change, social justice, and foreign policy. Positive content consistently achieved 20-30% higher engagement rates than negative content, though negative sentiments showed sharp spikes during controversies. Our findings contribute to understanding digital political discourse dynamics and offer practical insights for campaign strategy in the social media era. The study's limitations include platform-specific constraints and a two-month observation period, suggesting opportunities for cross-platform analysis in future research.
Penerapan Metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) dalam Seleksi Penerimaan Peserta Kegiatan Program Pendidikan Kecakapan Wirausaha Fazlur Rahman; Abdi Harfani; Mesran; Kelik Sussolaikah; Nelly Khairani Daulay; Ronal Watrianthos
Journal of Informatics Management and Information Technology Vol. 3 No. 1 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v3i1.238

Abstract

The Entrepreneurial Skills Education Program (PKW), is one of the programs from the Ministry of Education and Culture in 2019. PKW is an educational service through courses and training to provide knowledge, skills, and foster an entrepreneurial mental attitude in managing self-potential and the environment as a basis for entrepreneurship. This study aims to select the acceptance of participants in the Entrepreneurial Skills Education (PKW) program. The method used in the selection is by applying the MOORA method. The MOORA method is a method with very simple steps. The results showed that A1 is the best compared to several other alternatives with a value of 0.304
MODEL e-GOVERNMENT PEMERINTAHAN DESA Watrianthos, Ronal; Nasution, Ade Parlaungan; Syaifullah, Muhammad
Majalah Ilmiah UNIKOM Vol. 17 No. 1 (2019): Majalah Ilmiah Unikom
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (874.027 KB) | DOI: 10.34010/miu.v17i1.2239

Abstract

E-Government development has become the government commitment as established in the Inpres 3/2003 concerning about the National E-Government Development Policy and Strategy. However, this government policy has not been fully implemented in local government, resulting the e-Government role as the pledge of the government that cannot run well. Resistance to change is one of the inhibiting factors in e-Government development. The Law No. 6 of 2014 about Villages states that the implementation of village governance by utilizing Information Technology can be done through e-Government Villages. An in-depth study of models suitable for e-Government villages is needed. The process of identifying the Village e-Government needs is carried out with a Critical Success Factor (CSF) analysis. The results of the analysis produce four stages of the model which are divided into dimensions of technological complexity and organization with the level of data and information integration. Whereas the results of portfolio futures from the development of this model using McFarlan's Analyst Grid so that strategic modules, high potential, support, and operational key can be elaborated. Key words: e-Government, CSF, Village
Sistem pendukung keputusan penentuan penyakit busuk kuncup pada tanaman kelapa sawit dengan metode trend moment di PT. PERKEBUNAN NUSANTARA III (PERSERO) KEBUN AEK NABARA UTARA Hilman Taufik, Riski Nurjannah; Watrianthos, Ronal; Dalimunthe, Abdul Hakim
U-NET Jurnal Teknik Informatika Vol. 8 No. 2 (2024): U-NET Jurnal Teknik Informatika | Agustus
Publisher : LPPM Universitas Al Washliyah Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52332/u-net.v8i2.820

Abstract

Oil palm planting has bright prospects due to the sufficient availability of various supporting factors, although there are also various challenges to the existence and sustainability of these natural resources. Oil palm (Elaeis Guineensis Jacq) is a plantation crop that is very tolerant of unfavorable environmental conditions. Bud rot (spear rot) is a disease that attacks the bud or shoot area of oil palm plants. You have to be wary of this disease because it attacks young plants so that the plant grows abnormally, is unable to form fruit, is stunted, and grows slowly. The most worrying thing is that the attack is at the growing point. If a hole is made in the stem, a foul-smelling yellow liquid will come out. The decision support system is a system device capable of solving problems efficiently and effectively, which aims to assist decision making in choosing various decision alternatives which are the result of processing information obtained using a decision making model. Using the Trend Moment method, the aim is to determine the criteria for determining bud rot disease in oil palm plants at PTPN III Aek Nabara Utara.
SISTEM PAKAR MENDETEKSI PENENTUAN PENYAKIT ANEMIA MENGGUNAKAN METODE TEOREMA BAYES STUDI KASUS LABORATORIUM ANUGERAH RANTAUPRAPAT Hasibuan, Abdul Khairul Arby Hasibuan; Watrianthos, Ronal; Pasaribu, Endi Zunaedy
U-NET Jurnal Teknik Informatika Vol. 8 No. 2 (2024): U-NET Jurnal Teknik Informatika | Agustus
Publisher : LPPM Universitas Al Washliyah Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52332/u-net.v8i2.833

Abstract

Expert systems are a branch of artificial intelligence that studies how to adopt an expert's way of thinking in solving a problem and making a decision to reach a conclusion. In this case, an expert system is used to diagnose anemia. What was discussed was how to determine the type of disease, how to overcome anemia in society and designing an expert system using technology. anemia is caused by a lack of red blood cells or red blood cells that do not function in the body. This causes reduced oxygen flow to the body's organs. Vitamin B supplements can be used for low vitamin levels. The Bayes method is a method for producing parameter estimates by combining information from samples and other previously available information. Bayes' theorem is used to calculate the probability of an event occurring based on the influence obtained from the results of the observation. From several studies that have been carried out, solutions have been obtained to prevent anemia. Anemia can cause weakness and headaches due to lack of blood, which can lead to complications.
Effectiveness Blended Learning During Pandemic in Indonesia: A Meta-Analysis Watrianthos, Ronal; Hasibuan, Rosmidah; Rimbano, Dheo; Jalinus, Nizwardi; Abdullah, Rijal
Jurnal Pendidikan MIPA Vol 22, No 2 (2021): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

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

Abstract

The current blended learning method, which mixes online and traditional classroom instruction, is appropriate for the epidemic. According to various research studies, blended learning benefits students by allowing them to study independently without regard for location or time constraints. This article explores and describes the use of the blended learning paradigm during a pandemic using a meta-analysis technique. The objective is to determine the effect of blended learning on learning outcomes; according to the conclusions of a research released in 2021 based on ten published articles, employing the blended learning approach greatly improved learning outcomes during the pandemic, with an effect size value of 1.21. However, the outcomes of this study suggest that publication bias exists as a result of an unbalanced distribution of effect sizes.Keywords: blended learning, pandemic, meta-analysis DOI: http://dx.doi.org/10.23960/jpmipa/v22i2.pp270-278
Sentiment analysis of face-to-face learning based on social media Batubara, Hendra Saputra; Ambiyar, Ambiyar; Syahril, Syahril; Fadhilah, Fadhilah; Watrianthos, Ronal
Jurnal Pendidikan Teknologi Kejuruan Vol 4 No 3 (2021): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v4i3.22623

Abstract

The use of restricted face-to-face learning during the epidemic in Indonesia was discussed not just by education and health professionals, but also on social media. The study used the Twitter dataset with the keywords 'school' and 'face-to-face' to examine public opinion about face-to-face learning. The research data was obtained from Twitter utilizing Drone Emprit Academic, and it was then processed using the Naive Bayes method to create sentiment analysis. During that time, research revealed that 32% of people were positive, 54% were negative, and 14% were indifferent. Because of worries about the dangers associated with the use of face-to-face learning, negative attitudes predominate.
Co-Authors Abdi Harfani Abdullah, MT, Dr. Rijal Ade Parlaungan Nasution, Ade Parlaungan Afrina, Afrina Agariadne Dwinggo Samala Agus Perdana Windarto Ahmad Habin Sagala Ambiyar Ambiyar Ambiyar, Ambiyar Aminuyati Arie Pramana Arif Rizki Marsa Basyarul Ulya Batubara, Hendra Saputra Dalimunthe, Abdul Hakim Danil Polanda Deci Irmayani Decky Antony Kifta Dedi Mardianto Dedy Irfan Dheo Rimbano Endi Zunaedy Pasaribu Erlia Utami Panjaitan Fadhilah Fadhilah Fahmi Rizal Fazlur Rahman Firman Edi Firman Edi Firman Edi Gomal Juni Yarnis Gulo, Ria Nurani Hasibuan, Abdul Khairul Arby Hasibuan Hasibuan, Rosmidah Hendra Sahputra Batubara Hilman Taufik, Riski Nurjannah Ibnu Rasyid Munthe ibnu Rasyid Munthe Ibnu Rasyid Munthe Ibnu Rasyid Munthe Indarta, Yose Ismael Iwan Purnama Kelik Sussolaikah Khairul Kusmanto Kusmanto Kusmanto Kusmanto M Fauzi Romadhon Marpaung M. Giatman Marnis Nasution Mesra Wati Ritonga Mesran Mesran Mesran, Mesran Muhammad Bobbi Kurniawan Nasution Muhammad Irwansyah Hasibuan, Ira Triyana Dewi, Muhammad Syaifullah Muhammad Syaifullah, Muhammad Mukhlidi Muskhir Munthe, Ibnu Rasyid Nelly Khairani Daulay Nelly Khairani Daulay Nizwardi Jalinus Novi Hendri Adi Pasaribu, Endi Zunaedy Peronika Hulu Putra Akhir, Ade Fitrah Raden Sri Ayu Ramadhana Rahma Muti’ah Rahmad Aditiya Rahmi Syafriyeti Rahmi Syafriyeti Ratna Aisyah Siregar Refdinal, Refdinal Reti Handayani Reti Handayani Ria Nurani Gulo Rita Yunida Rizki Kurniawan Rangkuti Rosmidah Hasibuan S Solikhun Samsir Samsir Samsir Samsir Samsir Samsir Samsir Samsir, Samsir Saragih, Reagan Surbakti Shabrina Rasyid Munthe Shabrina Rasyid Munthe Siagian, Taufiqqurrahman Nur Simanjorang, Elida F. S. Simatupang, Wakhinuddin Simatupang, Wakhinuddin Subagio, Selamat Sumitro Sarkum Suryadi, Sudi Syahril Syahril Tri Hastuti Nasution Unung Verawardina Unung Verawardina Unung Verawardina Wahyu Azhar Ritonga Wanto, Anjar Waskito Witma Novita Atnur Yose Indarta Yose Indarta Yuhefizar Yuhefizar Zulkifli