Jurnal Universitas Dharma Andalas
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Pengembangan Model Pohon Keputusan untuk Menentukan Jurusan Pada SMA Menggunakan Bahasa C++
Get PDFThe selection of a high school major is one of the crucial decisions that will determine the future of students. Decision Support Systems (DSS) can be used to assist students in making such decisions. DSS can provide information and advice to students based on relevant criteria. The decision tree method is one of the classification methods that can be applied to DSS. This method utilizes a tree representation consisting of several nodes. Nodes in the decision tree represent attributes that influence decision-making in specific cases. This research aims to develop a decision tree model using the C++ programming language to assist high school students in choosing their majors. The decision tree model is developed by considering relevant criteria, namely interests, talents, and grades obtained by students in various subjects. The research results indicate that the developed decision tree model can provide relevant information and advice to students in choosing their majors. This model can significantly contribute to the effectiveness of the decision-making process undertaken by high school students when selecting their majors.Pemilihan jurusan SMA merupakan salah satu keputusan penting yang akan menentukan masa depan siswa. Siswa dapat memanfaatkan sistem pendukung keputusan (SPK) untuk membantu mereka membuat keputusan.. SPK dapat digunakan untuk memberikan informasi dan saran kepada siswa berdasarkan kriteria-kriteria yang relevan. Metode pohon keputusan merupakan salah satu metode klasifikasi yang dapat diterapkan pada SPK. Metode ini menggunakan representasi pohon yang terdiri dari sejumlah node. Node dari pohon keputusan mewakili atribut yang mempengaruhi pengambilan keputusan dalam kasus. Penelitian ini bertujuan untuk mengembangkan model pohon keputusan menggunakan bahasa pemrograman C++ untuk membantu siswa SMA dalam menentukan jurusan. Model pohon keputusan ini dikembangkan dengan mempertimbangkan kriteria-kriteria yang relevan, yaitu minat, bakat, dan nilai yang diperoleh siswa dari beberapa mata pelajaran. Hasil penelitian menunjukkan bahwa model pohon keputusan yang dikembangkan dapat memberikan informasi dan saran yang relevan kepada siswa dalam menentukan jurusan. Model ini dapat memberikan kontribusi signifikan terhadap efektivitas proses pengambilan keputusan yang dilakukan siswa SMA saat memilih jurusan mereka
Analisis Sentimen Ulasan Aplikasi Identitas Kependudukan Digital Menggunakan Metode Support Vector Machine
Get PDFDigital Population Identity Application, developed by the Directorate General of Civil Registration of the Ministry of Home Affairs, Indonesia, represents a digitalization initiative for population documents including electronic ID cards (KTP-el), Family Cards, Covid-19 vaccination certificates, tax identification numbers (NPWP), vehicle ownership information, National Civil Service Agency (BKN) data, social security (BPJS), national socioeconomic data (DTKS), and voter lists. Sentiment analysis is crucial to understand user feedback on the application. This study aims to analyze user sentiment toward the Digital Population Identity Application on Google Play Store, categorize sentiments using ISO 9126 standards, and evaluate accuracy using Support Vector Machine (SVM) algorithms within the framework of the Cross-Industry Standard Process for Data Mining (CRISP-DM). Research findings indicate positive sentiment from users toward the Digital Population Identity Application, with a primary focus on application functionality in positive reviews. SVM models trained using lexicon-based labeling achieved an accuracy of 80%, while models trained with ISO 9126 labeling achieved 84% accuracy. The conclusion of this study is that the Digital Population Identity Application is well-received by users, providing valuable guidance for developers to improve the quality and future development of the application.Aplikasi Identitas Kependudukan Digital merupakan inovasi yang dikembangkan oleh Ditjen Dukcapil Kementerian Dalam Negeri. Sebagai langkah digitalisasi dokumen kependudukan yang saat ini digunakan oleh penduduk Indonesia seperti KTP-el, Kartu Keluarga, kartu vaksin Covid-19, NPWP, informasi Kepemilikan Kendaraan, Informasi BKN (Badan Kepegawaian Nasional), BPJS, DTKS, serta Daftar Pemilih Tetap. Analisis sentimen perlu dilakukan untuk menganalisis ulasan yang diberikan oleh pengguna aplikasi.Penelitian ini dilakukan dengan tujuan untuk mengetahui sentimen pengguna aplikasi Identitas Kependudukan Digital di Google Play Store, mengategorikan dengan ISO 9126, dan menguji akurasi dengan algoritma Support Vector Machine (SVM). Dengan menerapkan Cross-Industry Standard Process for Data Mining (CRISP-DM). Hasil penelitian ini menunjukkan bahwa sentimen aplikasi Identitas Kependudukan Digital mendapat respon positif dari pengguna, dengan fungsionalitas aplikasi menjadi fokus utama dalam ulasan positif. Model SVM yang dilatih dengan menggunakan pelabelan lexicon memiliki akurasi sebesar 80%. Sedangkan model SVM yang dilatih dengan menggunakan pelabelan kategori ISO 9126 memiliki akurasi sebesar 84%. Kesimpulan dari penelitian ini Aplikasi Identitas Kependudukan Digital diterima dengan baik oleh pengguna, yang dapat memberikan panduan berharga bagi pengembang untuk meningkatkan kualitas dan pengembangan aplikasi di masa depan
Pemanfaatan Alat Berbasis Web untuk Otomatisasi Pengambilan Data Publikasi dari Google Scholar
No full textHere’s the revised abstract in English: The rapid growth of academic publications requires efficient tools for publication data extraction and management, especially from widely used platforms like Google Scholar. To address this need, an automated web-based tool was developed, designed to simplify the processes of data crawling, extraction, and publication data management, allowing researchers to handle large volumes of academic publications more effectively. The tool supports both simple and detailed crawling modes, enabling users to input multiple Google Scholar URLs and neatly organize the extracted data into CSV files. For multiple URLs, the data is compiled into a ZIP file containing separate CSV files for each source, ensuring organized and accessible publication data management. The tool was tested with various dataset sizes. When processing 41 entries, the simple mode completed extraction in 9.054 seconds, while the detailed mode took 71.898 seconds. For smaller datasets of 5 entries, the simple mode executed in 3.283 seconds, while the detailed mode required 11.908 seconds. These results indicate that the tool is efficient and performs well with both small and large datasets. The differences in execution time between the simple and detailed modes offer users flexibility in balancing speed and depth of data extraction according to their research needs. This web-based tool not only automates the data extraction process from Google Scholar but also enhances the organization and accessibility of publication data, making it an asset for researchers and institutions in managing publication data.Here’s the revised abstract in English: The rapid growth of academic publications requires efficient tools for publication data extraction and management, especially from widely used platforms like Google Scholar. To address this need, an automated web-based tool was developed, designed to simplify the processes of data crawling, extraction, and publication data management, allowing researchers to handle large volumes of academic publications more effectively. The tool supports both simple and detailed crawling modes, enabling users to input multiple Google Scholar URLs and neatly organize the extracted data into CSV files. For multiple URLs, the data is compiled into a ZIP file containing separate CSV files for each source, ensuring organized and accessible publication data management. The tool was tested with various dataset sizes. When processing 41 entries, the simple mode completed extraction in 9.054 seconds, while the detailed mode took 71.898 seconds. For smaller datasets of 5 entries, the simple mode executed in 3.283 seconds, while the detailed mode required 11.908 seconds. These results indicate that the tool is efficient and performs well with both small and large datasets. The differences in execution time between the simple and detailed modes offer users flexibility in balancing speed and depth of data extraction according to their research needs. This web-based tool not only automates the data extraction process from Google Scholar but also enhances the organization and accessibility of publication data, making it an asset for researchers and institutions in managing publication data
Implementation Of UI/UX Concepts And Techniques In Web Layout Design With Figma
Get PDFTechnological trends are always dynamic and experiencing rapid development, especially the internet with many sites emerging, both formal and entertainment (intertain). This requires a web developer, especially in terms of appearance, to always innovate in order to provide a good user experience, intuitive design, and easy to use by all groups. Of course, in designing an attractive interface page, you have to know the needs of the user, in order to optimize existing features, for that UI/UX concepts and techniques need to be applied in designing the interface. In this research trial using the Figma tool as the main tool starting from designing, wireframing to the prototyping process. The test results found that by applying UI/UX concepts and techniques to the interface design the design is more consistent, solid, harmonization, color alignment, font type and size according to the design system that has been determined.Tren teknologi yang selalu dinamis dan mengalami perkembangan yang begitu cepat, khususnya internet dengan banyaknya situs bermunculan dari yang sifatnya formal maupun hiburan (intertain). Hal ini menuntut seorang developer web khususnya dari segi tampilan untuk selalu berinovasi guna memberikan pengalaman pengguna yang baik, desain yang intuitif, dan mudah digunakan oleh semua kalangan. Tentu dalam mendesain halaman antarmuka yang menarik harus mengetahui kebutuhan pengguna, agar dapat mengoptimalkan fitur yang ada, untuk itu konsep dan teknik UI/UX perlu diterapkan dalam merancang tampilan antarmuka tersebut. Dalam ujicoba penelitian ini menggunakan perangkat Figma sebagai perangkat utama mulai dari merancang, wireframing hingga proses prototyping. Hasil ujicoba didapatkan bahwa dengan menerapkan konsep dan teknik UI/UX ke dalam rancangan antarmuka desain lebih konsisten, solid, harmonisasi, keselaran warna, jenis dan ukuran huruf sesuai dengan design system yang sudah ditentukan
Penerapan Metode Dempster Shafer Sistem Pakar Pada Penyakit Tuberkolosis
Get PDFThe Dempster-Shafer (DS) method is a method in trust theory that is used to overcome uncertainty in decision making. An expert system that utilizes the Dempster-Shafer method can be used to diagnose tuberculosis (TB). Application of the Dempster-Shafer method in an expert system for TB requires a good understanding of the medical domain and the ability to correctly combine evidence from multiple sources. In addition, collaboration with medical experts in developing this system will increase the accuracy and usefulness of the expert system. At the Wonokromo Community Health Center, the use of websites to diagnose tuberculosis is still lacking, therefore the aim of using this website is to help the community know more about tuberculosis. In the design process, this system uses a user interface, and is equipped with HTML, CSS, Boostrap, and Java Script. The result of this research is a website-based expert system application using the website-based Dempster Shafer method, and is able to overcome the problems that exist at the Wonokromo Community Health Center. The black box testing results show that the module configuration functions well and meets user needs.Metode Dempster-Shafer (DS) adalah suatu metode dalam teori kepercayaan yang digunakan untuk mengatasi ketidakpastian dalam pengambilan keputusan. Sistem pakar yang memanfaatkan metode Dempster-Shafer dapat digunakan untuk mendiagnosis penyakit tuberkolosis (TBC). Penerapan metode Dempster-Shafer dalam sistem pakar untuk TBC memerlukan pemahaman yang baik tentang domain medis dan kemampuan dalam menggabungkan bukti dari berbagai sumber dengan benar. Selain itu, kolaborasi dengan ahli medis dalam pengembangan sistem ini akan meningkatkan keakuratan dan kebermanfaatan sistem pakar tersebut. Pada Puskesmas Wonokromo penggunaan website untuk mendiagnosa penyakit tuberkolosis masih terbilang kurang, maka dari itu penggunaan website ini bertujuan dapat membantu mesyarakat untuk lebih mengetahui penyakit tuberkolosis. Dalam proses perancangan sistem ini menggunakan user interface, dan dilengkapi dengan html, css, boostrap, dan java script. Hasil penelitian ini adalah aplikasi sistem pakar berbasis website dengan menggunakan metode dempster shafer berbasis website, dan mampu mengatasi permasalahan yang ada di Puskesmas Wonokromo. Hasil pengujian blackbox menunjukkan bahwa konfigurasi modul berfungsi dengan baik dan memenuhi kebutuhan user
Analisa Performa Algoritma Random Forest & Logistic Regression Dalam Sistem Credit Scoring
Get PDFThe rapid advancement of technology, particularly in the field of Artificial Intelligence (AI), has had a significant impact across various industries. One increasingly popular implementation is ChatGPT, enabling more intuitive human-computer interactions. Moreover, AI has transformed the landscape of the financial sector, particularly in Credit Scoring. Using Supervised Machine Learning, algorithms like Random Forest and Logistic Regression are employed to enhance accuracy and efficiency in the Credit Scoring process. However, comparing the accuracy between these two algorithms remains a question. Therefore, this research aims to compare the accuracy levels of Random Forest and Logistic Regression in the context of Credit Scoring. From the research that have been conducted got result Random Forest given better AUC score on 0.90 than Logistic Regression which only got 0.89.Perkembangan teknologi yang pesat, terutama dalam bidang Artificial Intelligence (AI), telah membawa dampak besar pada berbagai sektor industri. Salah satu implementasi yang semakin populer adalah ChatGPT, yang memungkinkan interaksi manusia dengan komputer secara lebih intuitif. Selain itu, AI juga telah mengubah lanskap sektor keuangan, terutama dalam hal Credit Scoring. Dengan menggunakan Machine Learning Supervised, algoritma seperti Random Forest dan Logistic Regression digunakan untuk meningkatkan akurasi dan efisiensi dalam proses Credit Scoring. Namun, perbandingan antara akurasi kedua algoritma tersebut masih menjadi pertanyaan. Oleh karena itu, penelitian ini bertujuan untuk membandingkan tingkat akurasi antara Random Forest dan Logistic Regression dalam konteks Credit Scoring. Dari hasil penelitian kali ini didapatkan bahwa untuk dataset yang digunakan dalam penelitian Random Forest menghasilkan nilai AUC yang lebih baik yaitu sebesar 0.90 dibandingkan Logistic Regression pada angka 0.89
Penerapan Metode Technology Acceptance Model Untuk Mengetahui Tingkat Penerimaan Pengguna Aplikasi Vidio
Get PDFVidio is a Subscription video-on-demand (SVOD) platform offering video streaming services. Based on reviews of the Vidio application, it is known that many negative and low reviews related to the services provided have reduced in satisfaction and user acceptance. The aim of this study is to ascertain the extent of user acceptance by measuring the correlation between several variables. The approach to be utilized is Technology Acceptance Model by measuring the variables of perceived ease of use, perceived usefulness, behavioral intention to use, attitude towards using, and actual use with hypothesis test. The research was conducted on 100 Palembang city residents. Based on this research, there is a very strong positive correlation relationship between attitude towards using and behavioural intention to use. In addition, there is a strong positive correlation between the perceived usefulness variable and other variables except actual use. Overall from the results obtained, in the acceptance of users of the Vidio application, variable exhibits a notable and positive impact on this research.Vidio merupakan sebuah layanan Subscription video-on-demand (SVOD) yang memberikan layanan streaming video. Berdasarkan ulasan aplikasi Vidio, diketahui banyak ulasan yang negatif dan rendah terkait layanan yang diberikan membuat penerimaan dan kepuasan pengguna berkurang. Penelitian ini bertujuan untuk mengetahui tingkat penerimaan pengguna dengan mengukur korelasi antara beberapa variabel. Metode yang akan digunakan adalah Technology Acceptance Model dengan mengukur variabel perceived ease of use, perceived usefulness, behavioral intention to use, attitude toward using, dan actual use dengan uji hipotesis. Penelitian dilakukan terhadap 100 orang penduduk kota Palembang. Berdasarkan hasil penelitian ini, terdapat hubungan korelasi positif yang sangat kuat antara attitude toward using dan behavioral intention to use. Selain itu terdapat hubungan korelasi positif yang kuat antara variabel perceived usefulness dan variabel lainnya kecuali actual use. Secara keseluruhan dari hasil yang didapat, dalam penerimaan pengguna aplikasi Vidio masing-masing variabel berpengaruh signifikan dan positif pada penelitian ini
Sosialisasi dan Pelatihan Akuntansi Pesantren pada Ponpes Mu’allimin Muhammadiyah Sawah Dangka, Kab. Agam
Get PDF Blueprint pengembangan ekonomi dan keuangan syariah yang disusun oleh Bank Indonesia merangkum tiga pilar utama yang berperan penting dalam mendukung kemandirian ekonomi nasional, yaitu (1) pemberdayaan ekonomi syariah, (2) peningkatan efisiensi sistem keuangan syariah, dan (3) penguatan riset, asesmen dan edukasi. Pengembangan pesantren secara khusus telah pula menjadi salah satu target pengembangan ekonomi syariah mengingat perannya yang juga cukup strategis. Salah satu program untuk mendorong pengembangan pesantren adalah peningkatan tata kelola yang baik di lingkungan pesantren melalui tersedianya laporan keuangan yang memenuhi standar akuntansi yang diterima secara luas dan diterima berbagai pihak. BI dan IAI bekerja sama dalam penyusunan suatu panduan pelaporan keuangan bagi pondok pesantren yaitu Pedoman Akuntansi Pesantren. Namun, belum banyak pesantren yang memahami dan menggunakan pedoman ini, sehingga kami berharap dapat memperkenalkan pedoman akuntansi pesantren ini bagi pondok pengelola pondok pesantren tahfizh Al-Qur’an Muallimin Muhammadiyah Sawah Dangka, Kab. Agam, Sumatera Barat dalam rangka meningkatkan Tata Kelola Pondok Pesantren
Sosialisasi Pasar Modal “Investasi Cerdas di Era Digital” bagi Siswa/i SMK N 8 Kota Padang
Get PDFUnderstanding the investment society is needed by means of continuous socialization involving various parties so that understanding of capital market literacy to the community can continue to grow, namely by socializing to the public, especially the millennial generation that investing in the capital market is easy, planned, and cheap. The introduction of capital market literacy as a means of saving shares for vocational students aims to educate students as a millennial generation to be interested in capital market investment so that it is hoped that students can be interested in participating in capital market investment education and then be interested and interested in saving shares by opening a capital market account. The method of implementing community service activities in the form of providing learning to partners in the form of capital market socialization "Smart Investment in the Digital Age" material to students of SMK N 8 Padang Cit
Literasi Keuangan Syariah bagi Siswa Siswi Madrasah Tarbiyah Islamiyah (MTI) Dan SMA Pembina Bangsa, Bukitinggi, Kabupaten Agam, Sumatra Barat
Get PDFIndonesia has the potential to become a sharia financial and economic center at regional and global levels. Education related to sharia economics and finance has been carried out by Bank Indonesia, the Financial Services Authority, the Ministry of Religion and the Ministry of Education and Culture through their respective work units. However, this education has not touched more basic units such as families and individuals. According to OJK data, sharia financial literacy in Indonesia is still in the very low category. One of the causes of Sharia financial literacy is because the Indonesian Muslim population cannot directly experience the positive economic and financial impacts of Sharia. The fourth phase in Sharia economic and financial literacy material starts from the age of 16 to the age of 18 or the period of high school level education in Indonesia. This phase is the phase of learning advanced knowledge of Sharia economics and finance accompanied by practical training. It is hoped that this age group will be trained to have the ability to manage the economy and finances according to sharia. Therefore, we hope to increase the knowledge and understanding of high school level students, namely Madrasah Tarbiyah Islamiyah and Pembina Bangsa High School students regarding Sharia Finance so that it can be practiced in everyday life