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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Computatio : Journal of Computer Science and Information Systems Jurnal Akuntansi Jurnal CoreIT Jurnal Komputasi Network Engineering Research Operation [NERO] BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teknoinfo Krea-TIF: Jurnal Teknik Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Madani Jurnal Tekno Kompak Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Journal of Computer System and Informatics (JoSYC) JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Mattawang: Jurnal Pengabdian Masyarakat JTIKOM: Jurnal Teknik dan Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Telematics and Information Technology (TELEFORTECH) Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Paradigma Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Social Sciences and Technology for Community Service
Dedi Darwis
Universitas Teknokrat Indonesia
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : Building of Informatics, Technology and Science

 1 
Penerapan Metode TOPSIS dalam Pemilihan Moda Transportasi Berkelanjutan untuk Pengurangan Emisi Gas Rumah Kaca Pramita, Galuh; Darwis, Dedi
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5361

Abstract

The choice of sustainable modes of transportation for the reduction of greenhouse gas emissions is an important aspect in efforts to mitigate climate change. By choosing environmentally friendly modes of transportation, such as public transportation, electric vehicles, bicycles, or ride-sharing, individuals and organizations can contribute significantly to the reduction of greenhouse gas emissions produced by the transportation sector. The research objective of the application of decision support systems in the selection of sustainable modes of transportation for the reduction of greenhouse gas emissions is to provide a structured and effective framework in assisting individuals and organizations in choosing alternative modes of transportation that best suit their needs while also minimizing negative impacts on the environment. DSS can be a very useful tool in the selection of sustainable modes of transportation for the reduction of greenhouse gas emissions. DSS can integrate various factors such as energy efficiency, greenhouse gas emissions, infrastructure accessibility, and cost to determine the mode of transportation that best suits user needs and preferences. The ranking results are based on the respondents' assessment data for rank 1 with a final score of 0.92974 with an alternative name for Bicycles, rank 2 with a final score of 0.78159 with an alternative name for Hydrogen-Based Public Transportation, rank 3 with a final score of 0.76089 with an alternative name for Public Transportation, and rank 4 with a final score of 0.15703 with an alternative name for Electric Vehicles. The results of processing respondent response data based on 4 TRITAM Model criteria obtained Trust results of 76.25%, Risk of 75%, Perceived usefullness of 93.96%, Perceived easy of Use of 82.92%. Of the overall criteria of the TRITAM Model for technology acceptance, the result was very good at 84.17%
Perbandingan Algoritma NBC, SVM dan Random Forest untuk Analisis Sentimen Implementasi Starlink pada Media Sosial X Kencono, Lintang; Darwis, Dedi
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6813

Abstract

Internet development in Indonesia continues to progress rapidly, but equitable access remains a challenge, especially in remote areas. Starlink, a satellite internet service from SpaceX, comes as a solution to reduce this gap by providing fast and stable connectivity. This research analyzes public sentiment towards the implementation of Starlink on social media platform X through a comparative approach using three Machine Learning algorithms: Naive Bayes Classifier, Support Vector Machine, and Random Forest. The research data consisted of 6,780 Indonesian tweets collected during the period September 1 to November 30, 2024 using the harvest tweet library with the keywords “starlink,” “internet starlink,” and “SpaceX starlink”. After preprocessing, a total of 5,382 tweets were used, consisting of 4,348 tweets with negative sentiment and 884 tweets with positive sentiment. To overcome data imbalance, Synthetic Minority Over-sampling Technique (SMOTE) was applied. Before the application of SMOTE, the Random Forest model showed the highest accuracy of 92%, followed by Support Vector Machine with 91%, and Naive Bayes Classifier with 85%. After SMOTE was applied, the accuracy of the three models increased significantly, with Random Forest reaching 99%, Support Vector Machine 98%, and Naive Bayes Classifier 91%. Random Forest also showed the best performance in detecting positive sentiment, with Precision and Recall values reaching 100%. This research provides an in-depth insight into the effectiveness of Machine Learning algorithms in analyzing public sentiment towards Starlink services on social media and shows that the application of SMOTE can improve the model's performance in classifying sentiment more evenly.
Co-Authors . Yuniarwati ., Rusliyawati Abhishek R Mehta Abhishek R Mehta Ade Dwi Putra Ade Surahman Ade Surahman Adhie Thyo Priandika Aditia Yudhistira Agung Saputra Agus Wantoro Agustina, Intan Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Suhendri Aidil Akbar Alita, Debby Andi Ilham Rahmansyah Andre Setiawan Andri Pramuditya An’ars, M. Ghufroni Aprian Nuriansah Ariany, Fenty Arie Qur’ania Aulia Mustika Sari Ayu Vidiasari Bambang Dwi Setyarto Bayu Dwi Juniansyah Budiawan, Aditia Chaswarina Nimas Maharani Cici Dian Paramita Damayanti, Damayanti Dartono Dartnono Dartono Dartono Dartono Dartono Depriansah Depriansah Dini Wahyuni Ditha Nurjayanti Dwi Andika Dwi Maila Pauristina Dwi Rahma Sari Eka Shintya Pratiwi Elvano Delisa Mega Endi Febrianto Fadila Shely Amalia Fahri Hanif Fatmawati Isnain Fernando, Yusra Fikri Hamidy Gunawan, Rakhmat Dedi Heni Sulistiani I Gede Heri Susanto Ichtiar Lazuardi Putra Ikbal Yasin Ilham Muhammad Ghoffar Ilham Utama Putra Imam Ahmad Ismail, Izudin Ismail, Izzudin Isnain, Auliya Rahman Kencono, Lintang Khoirunnisa, Yosi Kisworo KISWORO Kisworo Kisworo Lusiana Indawa M Joko Priono Maria Ainun Nazar Marzuki, Dwiki Hafizh Maulana, Nanda Arif Megawaty, Dyah Ayu Meylinda Meylinda Mirza Wijaya Putra Muhammad Bakri Muhammad Fauzan Ramadhani Muhammad Khotimul Anwar Nova Evrilia Novi Eka Wati Nugraha Ashari Nurhuda Budi Pamungkas Nurhuda Budi Pamungkas Nurul Hotimah Pasaribu, A. Ferico Octaviansyah Prabowo, Rizky Pramita, Galuh Prastowo, Agung Tri Priandika, Adhie Thyo Prita Dellia Purnomo Aji Putra, Ade Dwi Putri Lestari Rachmad Nugroho Ramadan, Nabil Safiq Rayin Biilmilah Rika Mersita Riskiono, Sampurna Dadi Ryan Randy Suryono Saefulloh Saefulloh Salsa Safhira Sampurna Dadi Riskiono Sanriomi Sintaro Saputra, Febrian Eko Sari, Priskila Lovika Setiawansyah Setiawansyah Sitna Hajar Hadad suaidah suaidah Surahman, Ade Surya Indra Gunawan Tika Yusiana Tithania Marta Putri Trisnawati, Fika Ummy Permata Hakim Vera Herlinda Very Hendra Very Hendra Saputra Very Hendra Saputra Very Hendra Saputra Wamiliana Wamiliana Wang, Junhai Waqas Arshad, Muhammad Wayan Kresna Yogi Swara yasin, ikbal Yuri Rahmanto Yusra Fernando Yusra Fernando Yusri Kusumayuda