Abstract:Abstract: Twitter, as a social media platform, has rapidly grown as a means for people to express their opinions and thoughts on various topics, including education. The number of Twitter users surged to 10.645.000 in 2020,…
20, with a significant increase during the pandemic. Telkom University, as a private institution of higher education in Indonesia, has become one of the topics of discussion on Twitter. Users’ opinions about Telkom University vary, ranging from positive to negative. To gain deeper insights into public view, sentiment analysis is essential. The analysis follows the Knowledge Discovery in Databases (KDD) process, utilizing the Naive Bayes classification algorithm. The evaluation results indicate the best accuracy achieved with an 80:20 data split, resulting in an accuracy rate of 82.05%, precision of 82.3%, recall of 82.05%, and F1-Score of 82.08%. The Naïve Bayes model demonstrates good performance for sentiment analysis of public views regarding Telkom University on Twitter.
Keywords: naïve bayes; sentiment analysis; twitter; telkom university.
Abstrak: Media sosial Twitter berkembang pesat sebagai sarana masyarakat berekspresi untuk menuangkan opini dan pikiran mereka mengenai topik apapun, termasuk pendidikan. Pengguna Twitter meningkat tajam hingga 10.645.00 pengguna pada tahun 2020 dan terus meningkat selama pandemi. Telkom University sebagai perguruan tinggi menjadi salah satu topik yang dibicarakan yang berkaitan dengan pendidikan. Pendapat mengenai Telkom University yang diungkapkan oleh pengguna Twitter beragam, baik positif maupun negatif. Analisis sentimen diperlukan untuk memahami pandangan publik lebih mendalam. Digunakan tahapan Knowledge Discovery in Databases dan algoritma klasifikasi Naïve Bayes dalam analisis ini. Hasil evaluasi menunjukkan akurasi paling baik dicapai dengan rasio data 80:20, dengan nilai akurasi sebesar 82.05%, nilai presisi sebesar 82.3%, nilai recall sebesar 82.05%, dan nilai F1-Score sebesar 82.08%. Model klasifikasi Naïve Bayes memiliki performa baik untuk analisis sentimen pandangan publik di Twitter mengenai Telkom University.
Kata kunci: analisis sentimen; naïve bayes; twitter; telkom university.
Abstract:Abstract: Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in the economic growth of Indonesia. However, their contribution has not reached its maximum potential, with over 40% of MSMEs facing various challenges,…
llenges, one of which is funding. The funding issue has become a hindrance to the growth of this sector. One contributing factor is the difficulty in obtaining loans with high interest rates.Crowdfunding has been considered a potential solution, but it has not been fully utilized due to the lack of literacy and negative cases surrounding it. In this context, the development of a Shariah-compliant crowdfunding application is seen as a suitable solution, given the government's efforts to strengthen the Shariah economic ecosystem. To support this application's development, the Laravel framework and the Extreme Programming method, emphasizing simplicity and accelerating the development process, are employed. The result of this research is the implementation of the UML design and system logic, resulting in the Tasha Crowdfunding application as a funding solution for MSMEs. It can accelerate the development process. The research outcomes include the backend implementation of the UML design and system logic, with a 100% successful blackbox testing result, leading to the creation of the Tasha Crowdfunding application as an MSME funding solution.
Keywords: backend services; crowdfunding syariah; extreme programming; MSMEs.
Abstrak: Di Indonesia Usaha Mikro Kecil Menengah (UMKM) mempunyai peran yang sangat penting bagi pertumbuhan perekonomian negara. Meskipun demikian, ternyata kontribusi yang diberikan oleh UMKM belum mencapai angka yang maksimum dikarenakan lebih dari 40% UMKM masih mengalami banyak permasalahan salah satunya adalah pendanaan. Permasalahan pendanaan yang dihadapi oleh Usaha Mikro Kecil Menengah (UMKM) di Indonesia telah menjadi penghambat pertumbuhan sektor ini. Salah satu faktor penyebabnya adalah kesulitan dalam memperoleh pinjaman dengan suku bunga yang tinggi. Crowdfunding telah dianggap sebagai solusi potensial, namun belum dimanfaatkan secara optimal karena kurangnya literasi dan kasus negatif yang terjadi. Dalam konteks ini, pengembangan aplikasi crowdfunding syariah dianggap sebagai solusi yang cocok, mengingat penguatan ekosistem ekonomi syariah yang sedang dilakukan oleh pemerintah. Untuk mendukung pengembangan aplikasi ini, digunakan framework laravel dan metode Extreme programming yang menekankan kesederhanaan dan percepatan proses pengembangan. Hasil penelitian ini berupa implementasi perancangan UML dan logika sistem yang menghasilkan aplikasi Tasha Crowdfunding sebagai solusi pendanaan UMKM.dapat mempercepat proses pengembangan. Hasil dari penelitian ini berupa implementasi backend dari perancangan UML dan logika sistem yang telah dibuat dengan hasil pengujian blackbox testing 100% sukses dan menghasilkan aplikasi tasha crowdfunding sebagai solusi pendanaan UMKM.
Kata kunci: backend service; crowdfunding syariah; extreme programming; UMKM.
Abstract:Automatic text summarization is challenging research in natural language processing, aims to obtain important information quickly and precisely. There are two main approach techniques for text summary: abstractive and extractive…
tractive summary. Abstractive Summarization generates new and more natural words, but the difficulty level is higher and more challenging. In previous studies, RNN and its variants are among the most popular Seq2Seq models in text summarization. However, there are still weaknesses in saving memory; gradients are lost in long sentences so resulting in a decrease in lengthy text summaries. This research proposes a Transformer model with an Attention mechanism that can fetch important information, solve parallelization problems, and summarize long texts. The Transformer model we propose is GPT-2. GPT-2 uses decoders to predict the next word using the pre-trained model from w11wo/indo-gpt2-small, implemented on the Indosum Indonesian dataset. Evaluation assessment of the model performance using ROUGE evaluation. The study's results get an average result recall for R-1, R-2, and R-L were 0.61, 0.51, and 0.57, respectively. The summary results can paraphrase sentences, but some still use the original words from the text. Future work increase the amount of data from the dataset to improve the result of more new sentence paraphrases.
Abstract:Abstract: Population is a group of people who live or settle in an area for six months or more. Increasing the population in an area results in more problems being faced by the area such as high unemployment rates, poverty…
ty and food shortages which result in hunger. BPS Asahan Regency records that there is an increase in population every year. Asahan Regency BPS cannot predict population growth in the following year, so an application is needed to predict population growth. The purpose of this study is to predict population growth in Asahan Regency in the following year based on previous data using the concept of data mining. By applying data mining using multiple linear regression methods can be used to calculate population growth estimates based on previous data. This quantitative research used population data of Asahan Regency from 2016 to 2022. From the calculation of the multiple linear regression model using data from the previous five years, the estimated population growth of Asahan for 2023 was 824,617 people and the process of estimating the population became more systematic and calculated. well with this population estimation system and the process of storing data becomes easier and does not require a lot of paper to print and save.
Keywords: Application; Data Mining; Multiple Linear Regression
Abstrak: Penduduk merupakan sekumpulan orang yang tinggal atau menetap pada suatu wilayah selama enam bulan atau lebih. Bertambahnya jumlah penduduk pada suatu daerah mengakibatkan semakin banyak pula persoalan yang di hadapi oleh daerah tersebut seperti tingkat pengangguran yang tinggi, kemiskinan dan kekurangan pangan yang mengakibatkan kelaparan. BPS Kabupaten Asahan mencatat terjadi adanya pertambahan penduduk pada setiap tahunnya. BPS Kabupaten Asahan tidak dapat memprediksi pertumbuhan penduduk pada tahun berikutnya sehingga dibutuhkan suatu aplikasi untuk memprediksi pertambahan penduduk tersebut. Tujuan penelitian ini adalah untuk memprediksi pertumbuhan penduduk Kabupaten Asahan pada tahun berikutnya berdasarkan data sebelumnya menggunakan konsep data mining. Dengan menerapkan data mining menggunakan metode regresi linier berganda dapat digunakan untuk menghitung estimasi pertumbuhan penduduk berdasarkan data sebelumnya. Penelitian yang dilakukan secara kuantitatif ini menggunakan data penduduk Kabupaten Asahan dari tahun 2016 sampai tahun 2022. Dari perhitungan model regresi linier berganda menggunakan data lima tahun sebelumnya didapat estimasi pertumbuhan penduduk Asahan untuk tahun 2023 sebesar 824.617 jiwa dan proses estimasi jumlah penduduk menjadi lebih sistematis dan terkalkulasi dengan baik dengan adanya sistem estimasi jumlah penduduk ini dan proses penyimpanan data menjadi lebih mudah dan tidak memerlukan banyak kertas untuk di cetak dan di simpan.
Kata kunci: Aplikasi; Data Mining; Regresi Linier Berganda
Abstract:Abstract: This study illustrates the use of the Analytical Hierarchy Process (AHP) in a decision support system (SPK) and combined with the Geographic Information System (GIS) to select funds for School Operational Assistance…
tance (BOS) at the secondary school level as a recommendation. for decision-makers, so that the selection of BOS fund receipts can run properly, quickly and as expected. The problem of delays in the distribution of BOS funds and the price of goods that can change every year, thereby affecting the unstable amount of funds spent on operational costs. The purpose of this study is to utilize a decision support system in determining the priority of receiving BOS funds at the secondary school level using the AHP method combined with GIS so that the implementation of the information system can be optimized. With this system, it is very useful to monitor the distribution of BOS funds so that they run smoothly by the expectations and goals of government programs. Determination of latitude and longitude using google maps to obtain maps and locations of aid recipients, connected with MySQL as a database and PHP programming and modeled with UML. The results of this study can be used to determine the receipt of BOS funds and their mapping by providing various criteria and alternatives for decision-makers.
Keywords: AHP, BOS, GIS, Google Map, SPK
Abstrak: Penelitian ini memaparkan tentang pemanfaatan Analitical Hierarchy Process (AHP) dalam sistem pendukung keputusan (SPK) dan dikombinasikan dengan Geographic Information System (GIS) untuk menyeleksi penerimaan dana Bantuan Operasional Sekolah (BOS) jenjang SMA sebagai rekomendasi bagi pihak pengambil keputusan, agar seleksi penerimaan dana BOS tersebut dapat berjalan secara tepat, cepat dan sesuai dengan yang diharapkan. Masalah keterlambatan pada saat penyaluran dana BOS dan harga barang-barang yang setiap tahunnya bisa berubah sehingga berpengaruh terhadap tidak stabilnya jumlah pengeluaran dana untuk biaya operasional. Tujuan yang ingin dicapai dari penelitian ini adalah pemanfaatan sistem pendukung keputusan dalam menentukan prioritas penerimaan dana BOS jenjang SMA dengan menggunakan metode AHP dikombinasikan dengan GIS, sehingga implementasi sistem informasi dapat optimal. Dengan adanya sistem ini bermanfaat untuk memantau penyaluran dana BOS agar berjalan dengan lancar sesuai dengan harapan dan tujuan dari program pemerintah. Penentuan latitude dan longitude menggunakan google maps untuk mendapatkan peta dan lokasi penerima bantuan, dikoneksikan dengan mysql sebagai database dan pemrograman PHP serta dimodelkan dengan UML. Hasil penelitian ini dapat digunakan untuk menentukan penerimaan dana BOS dan pemetaannya dengan memberikan berbagai kriteria dan alternatif kepada pihak pengambil keputusan.
Kata kunci: AHP, BOS, GIS, Google Map, SPK
Abstract:Abstract: Tiansi is a company that markets health products. This company has difficulty predicting people's interest in products that are in high demand. By knowing precisely the consumer interest in the product, it will…
increase sales. The research aims to predict consumer interest in Tiansi products appropriately. The method used is one of the Artificial Neural Network (ANN) techniques, namely Backpropagation with Momentum. The sales data tested were sourced from Stockist 319 Padang. The results of this research that can precisely determine consumer interest are architecture 5-2-1 and 5-3-1. So that this research is very helpful in the procurement of goods to increase the value of sales.
Keywords: Artificial neural network, backpropagation, consumer interest rates, predictions.
Abstrak: Tiansi merupakan sebuah perusahaan yang memasarkan produk-produk kesehatan. Perusahaan ini mengalami kesulitan dalam memprediksi minat masyarakat terhadap produk yang sangat diminati. Dengan mengetahui dengan tepat minat konsumen terhadap produknya, maka akan dapat meningkatkan penjualan. Penelitian ini bertujuan untuk memprediksi minat konsumen terhadap produk Tiansi dengan tepat. Metode yang digunakan salah satu teknik Artificial Neural Network (ANN), yaitu Backpropagation dengan Momentum. Data penjualan yang diuji bersumber dari Stokist 319 Padang. Hasil dari penelitian ini yang dapat dengan tepat menentukan minat konsumen adalah arsitektur 5-2-1 dan 5-3-1. Sehingga penelitian ini sangat membantu sekali dalam pengadaan barang untuk meningkatkan nilai penjualan.
Kata kunci: Jaringan Syaraf Tiruan, Backpropagation, prediksi, minat konsumen, penjualan.
Abstract:Abstrack:To produce a 3D animated film requires a long process flow so that the processing time of manufacture is also prolonged. This is a constraint in the development of the local animation film in Indonesia for a long…
g time will lead to high production costs making it difficult to compete commercially with animated films from abroad who have abundant funds and the support of various parties in the country. Therefore, efforts to improve the competitiveness of local animated film and one of these efforts is by analyzing the stages of the manufacturing process and apply it to the process of making the actual 3D animated film.In general there are three stages of the filmmaking process, namely the 3D animation pre-production, production and post-production. Although this time the animation industry in Indonesia has not been detailed separates each of these stages, but still be important for designing detail the activities of these stages, in order to see the strengths and weaknesses of each process that existed at that stage. Therefore, this study was conducted with the hope to provide recommendations to improve the local animation industry.
Keywords: 3D Animation, Animation Film Pre-Production Stage, Princess Peacock Orange
Abstak: Untuk menghasilkan sebuah film animasi 3D membutuhkan alur proses yang panjang sehingga waktu pembuatannya juga berlangsung lama. Ini yang menjadi kendala dalam perkembangan film animasi lokal di Indonesia karena waktu yang yang panjang akan mengakibatkan tingginya cost production sehingga sulit untuk bersaing secara komersial dengan film animasi dari luar negeri yang memiliki dana berlimpah dan dukungan dari berbagai pihak di negaranya. Untuk itu diperlukan upaya untuk meningkatkan daya saing film animasi lokal dan salah satu upaya tersebut adalah dengan menganalisa tahapan-tahapan proses pembuatan dan menerapkannya pada proses pembuatan film animasi 3D yang sebenarnya.Secara umum ada 3 tahapan proses pembuatan film animasi 3D yaitu pra produksi, produksi dan paska produksi. Meskipun saat ini industri animasi di Indonesia belum secara detail memisahkan setiap tahapan tersebut, namun tetap menjadi penting untuk merancang detail aktifitas dari tahapan tersebut, dengan tujuan untuk melihat kekuatan dan kelemahan dari setiap proses yang ada pada tahapan tersebut.
Kata Kunci: Animasi 3D, Tahap Pra Produksi Film Animasi, Putri Merak Jingga
Abstract:Abstract: The human eye can distinguish objects from digital images, however, computers do not have the ability as human eyes that can directly distinguish objects from digital images. Therefore the bag of visual words method…
ethod was created. Bag of visual words is a method for presenting digital images based on local features. Bag of visual words illustrates how an image can be taken its characteristics, so that computers can distinguish objects on digital images. The test results show that the bag of visual words are still not maximal in classifying digital image categories, especially the chair category, which is only able to produce the most accurate accuracy of 75%. To improve the performance quality of bag of visual words in classifying digital image categories, especially the chair category, you can add an approach to determine the good number of K in clustering the visual words pattern.
Keywords: Bag Of Visual Words, Classification, Digital Image, Speed-Up Robust Feature, Support Vector Machine
Abstrak: Secara kasat mata manusia bisa membedakan objek pada citra digital, namun, komputer tidak memiliki kemampuan sebagai mata manusia yang dapat secara langsung membedakan objek pada citra digital. Maka dari itu diciptakanlah metode bag of visual words. Bag of visual words adalah metode untuk menyajikan citra digital berdasarkan fitur lokal. Bag of visual words menggambarkan bagaimana suatu gambar dapat diambil karakteristiknya, sehingga komputer dapat membedakan objek pada citra digital. Hasil pengujian menunjukkan bag of visual words masih belum maksimal dalam mengklasifikasi kategori citra digital khususnya kategori chair, yang hanya mampu menghasilkan akurasi paling akurat sebesar 75 %. Untuk meningkatkan kualitas kinerja bag of visual words dalam mengklasifikasi kategori citra digital khususnya kategori chair, dapat menambahkan pendekatan untuk menentukan jumlah K yang baik dalam mengkluster pola visual words.
Kata kunci: Bag Of Visual Words, Klasifikasi, Citra Digital, Speed-Up Robust Feature, Support Vector Machine
Abstract:The rapid advancement of digital technology and artificial intelligence (AI) in the twenty-first century has fundamentally transformed the structure of modern constitutional governance. Digitalization has reshaped the interactions…
teractions between governments and citizens, altered the patterns of political participation, and presented major challenges to constitutional principles. This study aims to analyze the implications of technological development for constitutional law and propose the concept of a digital constitution as an adaptive framework in the AI era. This study employs a normative legal method, using both conceptual and statutory approaches. Legal materials consist of primary, secondary, and tertiary sources, which are analyzed qualitatively and descriptively. The findings reveal that, while digital transformation enhances governmental efficiency and public transparency, it also generates serious risks, including data misuse, digital surveillance, and political disinformation. These dynamics demand a reinterpretation of constitutional norms to protect citizens' digital rights in cyberspace. The concept of a digital constitution is proposed as a normative response that integrates digital rights into constitutional rights and reaffirms the principle of the rule of law within technological governance. To achieve a democratic and just constitutional order, it is crucial to strengthen regulatory frameworks, ensure algorithmic accountability, and foster collaboration among state institutions, civil society, and the private sector. Ultimately, constitutional law must evolve into an adaptive, transparent, and fair system that can address the profound challenges of the digital and AI-driven era.
Abstract:This study aims to develop a comprehensive constellation model and identify optimal strategies for strengthening lecturers’ professional commitment in the largest private universities in Bogor. Penelitian ini mengkaji secara…
secara mendalam bagaimana emosi dan belajar sosial memengaruhi proses pembelajaran di sekolah dasar melalui perspektif neuropedagogik dan brain‑based learning. A mixed methods approach was used by combining quantitative analysis (meta-analysis of 173 respondents and 47 indicators of NP, EC, OB, MS, BS) and descriptive qualitative analysis using thematic analysis techniques on semi-structured interviews with five elementary school teachers. The meta-analysis results showed a very strong average effect of the latent construct relationship (t(128) = 12.92; p < 0.001; r ≈ 1.00) with almost zero heterogeneity (Qₑ(128) = 1.67; τ² = 0; I² = 0%), and no significant moderating effects were found for all indicators; the partial meta-regression coefficients for all items were very close to zero and the R² value was 0.000. Qualitatively, three main themes emerged: (1) positive emotions as the foundation of learning readiness, (2) social interaction as a reinforcement of meaning formation, and (3) contextual learning that integrates cognitive, emotional, and social dimensions. Although most teachers have not yet mastered the concepts of neuropedagogy and brain-based learning theoretically, they have intuitively implemented its principles through motivation, praise, humor, group work, collaborative projects, and learning experiences relevant to students' real lives. These findings support the latest theory that places emotions and social interactions as the main drivers of brain function in learning (Immordino Yang, 2016; Tyng et al., 2017; Vygotsky, 1978; Jensen, 2008), and emphasizes the importance of strengthening teachers' competence in understanding and designing brain- and emotion-based learning to support the holistic development of elementary school students.