Abstract:Abstract: YouTube is one of the most popular video streaming platforms, but it has constraints that can cause problems when clients have difficulty finding content according to their wishes. The main objective of this study…
udy is to increase user capacity in viewing content specifically in the field of women's empowerment. By using content-based filtering techniques, the system will analyze user preferences and interests through recommendations for women's empowerment content. The data source is via the YouTube API and is analyzed using PHP programming content-based filtering techniques. The system's recommendations provide a list of women's empowerment content with a user request display. The results of the research evaluation obtained a precision value of 62%, meaning that the recommendations match the topic being searched for, namely women's empowerment. The recall value of 84% indicates that the system has succeeded in finding relations from the database. The f1-score value of 72% indicates that there is a balance between precision and recall, meaning that a system is needed that is not only accurate but also complete. While the cosine value shows a score of 0.7071 approaching the maximum value (1.0). The recommendation of the content-based filtering method produces quite effective women's empowerment content.
Keywords: content-based filtering, recommendations, women Empowerment, youtube
Abstract:Abstract: Hospitals play an important role in examining the scan results of patient data infected with the Covid 19 virus. However, there are problems when processing the scan results, namely that sometimes errors occur…
in the scan data, causing many failures and delays in sending data to the Health Office. The purpose of this study is to build a Desktop-based decision support system application that can facilitate hospitals in selecting the eligibility of the scan results of Covid 19 patient data. The urgency in examining the scan results of Corona patient data is a very pressing public health issue, because the long-term impact is very significant for patients. Thus, a scientific discipline is needed that can support the decision-making process, namely the Decision Support System using the Preference Selection Index (PSI) method. PSI is a simple and easy calculation method, based on statistical concepts without having to determine attribute weights. The results of this method are clear and firm values based on the level of strength of the rules applied. The results of the research conducted on the PSI process can be concluded that valid Covid 19 patient data is Recap File I with a value of 0.2042 which is declared valid and accepted.
Keywords: covid-19; decision support system; PSI
Abstract:Abstract: Non-performing loans remain one of the main challenges faced by cooperatives, particularly when the loan eligibility assessment process is still conducted manually. This traditional approach tends to be time consuming,…
nsuming, subjective, and prone to inaccurate decisions. This study aims to develop a predictive model for borrower eligibility using the Support Vector Machine (SVM) algorithm as a more efficient and objective machine learning-based solution. A total of 1,000 loan history records were processed using RapidMiner software, taking into account variables such as salary, years of employment, loan amount, monthly installment, employment status, monthly expenses, number of dependents, housing status, age, and collateral value. The model’s performance was evaluated using a confusion matrix and classification metrics including accuracy, precision, recall, and kappa. The results indicate that the SVM model achieved an accuracy of 90.05%, precision of 90.13%, recall of 90.05%, and f1 score of 90,08%, reflecting a strong performance in classifying borrower eligibility. The application of this method makes a significant contribution to the development of data driven decision support systems within cooperative environments. This finding expands the scientific understanding in the field of microfinance and supports the implementation of artificial intelligence technologies in making decisions that are more precise, rapid, and accurate.
Keywords: cooperative; eligibility prediction; machine learning; non-performing loan; SVM
Abstrak: Kredit macet merupakan salah satu permasalahan utama yang dihadapi koperasi, terutama ketika proses penilaian kelayakan peminjam masih dilakukan secara manual. Pendekatan ini cenderung lambat, subjektif, dan berisiko menghasilkan keputusan yang kurang akurat. Penelitian ini bertujuan untuk membangun model prediksi kelayakan peminjam menggunakan algoritma Support Vector Machine (SVM) sebagai solusi berbasis machine learning yang lebih efisien dan objektif. Sebanyak 1.000 data riwayat pinjaman diolah menggunakan tools RapidMiner dengan mempertimbangkan variabel: gaji, lama bekerja, besar pinjaman, angsuran per bulan, status pegawai, pengeluaran bulanan, jumlah tanggungan, status rumah, umur, dan nilai jaminan. Evaluasi model dilakukan menggunakan confusion matrix dan metrik klasifikasi seperti akurasi, presisi, recall, dan kappa. Hasil menunjukkan bahwa model SVM mencapai akurasi 90,05%, presisi 90,13%, recall 90,05%, dan f1 score 90,08%, yang mencerminkan performa model yang sangat baik dalam mengklasifikasikan kelayakan peminjam. Penerapan metode ini memberikan kontribusi penting dalam pengembangan sistem pendukung keputusan berbasis data di lingkungan koperasi. Temuan ini memperluas wawasan keilmuan di bidang keuangan mikro dan mendukung penerapan teknologi kecerdasan buatan dalam pengambilan keputusan yang lebih tepat, cepat, dan akurat.
Kata Kunci: koperasi; kredit macet; machine learning; prediksi kelayakan; SVM
Abstract:Abstract: Face recognition based on deep learning has become an important technology in many areas. However, these systems often face challenges in real-world conditions, such as when the face is partially covered by accessories…
essories such as masks or glasses. This study aims to evaluate the effect of data augmentation by adding facial accessories (masks, glasses, and a combination of both) and geometric augmentation on the accuracy of face recognition systems. There are three types of datasets used in this method: the original dataset (category 1), the dataset with facial accessories augmentation (category 2), and the dataset with geometric augmentation (category 3). Data augmentation was performed on the training dataset to increase diversity, followed by the face detection process using SCRFD and feature extraction with ArcFace. The model was then trained using Multi-Layer Perceptron (MLP). Based on the results, adding face accessories (category 2) made the model a lot more accurate, hitting 99% accuracy. In category 3, adding geometric features improved accuracy to 91%. Other evaluation metrics, such as precision, recall, and F1-score, also showed improvement after augmentation. This study concludes that facial accessories augmentation is more effective in improving the accuracy and robustness of face recognition models compared to geometric augmentation.
Keywords: augmentation; deep learning; face recognition; glasses.
Abstrak: Pengenalan wajah berbasis deep learning telah menjadi salah satu teknologi penting dalam berbagai aplikasi. Namun, sistem ini sering kali menghadapi tantangan dalam kondisi dunia nyata, seperti saat wajah tertutup sebagian oleh aksesori seperti masker atau kacamata. Penelitian ini bertujuan untuk mengevaluasi pengaruh augmentasi data dengan menambahkan aksesori wajah (masker, kacamata, dan kombinasi keduanya) serta augmentasi geometris terhadap akurasi sistem pengenalan wajah. Metode yang digunakan melibatkan tiga kategori dataset: dataset asli tanpa augmentasi (kategori 1), dataset dengan augmentasi aksesoris wajah (kategori 2), dan dataset dengan augmentasi geometris (kategori 3). Augmentasi data dilakukan pada dataset pelatihan untuk meningkatkan keberagaman, diikuti dengan proses deteksi wajah menggunakan SCRFD dan ekstraksi fitur dengan ArcFace. Model kemudian dilatih menggunakan Multi-Layer Perceptron (MLP). Hasil penelitian menunjukkan bahwa augmentasi aksesoris wajah (kategori 2) memberikan peningkatan signifikan pada akurasi model, mencapai 99%, sedangkan kategori 3 dengan augmentasi geometris mencapai akurasi 91%. Metrik evaluasi lainnya, seperti precision, recall, dan F1-score, juga menunjukkan peningkatan setelah augmentasi. Penelitian ini menyimpulkan bahwa augmentasi aksesoris wajah lebih efektif dalam meningkatkan akurasi dan ketahanan model pengenalan wajah dibandingkan dengan augmentasi geometris.
Kata kunci: augmentasi; deep learning; kacamata; pengenalan wajah.
Abstract:Abstract: The implementation of Geographic Information Systems (GIS) within organizations has become essential in accomplishing work activities in the modern era. Sideak Motor is a financing company in Kisaran City, Asahan…
an Regency, that provides loans using motorcycle registration certificates (BPKB) as collateral, with a customer base reaching 6,052. Sideak Motor faces difficulties in data management. During meetings concerning customer locations, data communication with owners and office staff is often problematic. Additionally, when duties are transferred, new field officers struggle to locate customers because the previous officers could only provide textual information. As a result, office staff have no precise knowledge of customer locations—only the field officers do. This study aims to design a web-based customer mapping system to facilitate information storage, reduce costs, save time, and produce an information system that enhances the efficiency and accuracy of customer data management. The resulting system presents the distribution of customer locations and provides accessible information such as personal data, addresses, route details, and photos of customers’ homes, thereby simplifying the operations of Sideak Motor.
Keywords: customer distribution mapping; geographic information system (GIS); sideak motor.
Abstrak: Penerapan sistem informasi geografis dalam organisasi menjadi hal utama untuk menyelesaikan suatu aktivitas pekerjaan pada era sekarang ini. Sideak Motor merupakan salah satu perusahaan pembiayaan dengan agunan BPKB sepeda motor di Kota Kisaran Kabupaten Asahan yang memiliki nasabah mencapai 6.052, Sideak Motor kesulitan dalam pengelolaan data, saat melakukan rapat mengenai lokasi nasabah sulit dilakukan komunikasi data dengan pemilik dan petugas kantor lainnya, serta pada saat pergantian tugas, petugas lainnya kesulitan mencari lokasi nasabah, karena petugas lapangan hanya bisa memberikan informasi berupa teks, dengan begitu petugas kantor tidak mengetahui lokasi pasti nasabah Sideak Motor, jadi yang mengetahui lokasi mengenai tempat tinggal nasabah hanya petugas lapangan. Penelitian ini memiliki tujuan untuk merancang sebuah sistem pemetaan nasabah berbasis web yang dapat mempermudah dalam penyimpanan informasi, mengurangi biaya, menghemat waktu serta menghasilkan sistem informasi yang dapat meningkatkan efisiensi dan akurasi pengelolaan data nasabah. Hasil sistem ini menyajikan sebaran pemetaan lokasi nasabah menyediakan informasi berupa biodata, alamat, rincian rute, dan gambar rumah nasabah yang dapat diakses secara cepat dan akurat sehingga dapat mempermudah pihak sideak motor.
Kata Kunci: pemetaan sebaran nasabah; sistem informasi geografis (SIG); sideak motor
Abstract:Abstract: Due to the successful conversion from LPG stoves to electric stoves, which are unsupported by the village’s electricity supply—averaging 450 watts—while government-provided stoves have a power rating of 900…
wer rating of 900 watts, making them unsuitable for use in Tomuanhollbung Village. To address this issue, the research team designed a stove that uses waste oil (35,000 kJ/kg) and incorporated embedded system technology, utilizing the French design research method. The research results indicated that by using a DC motor with specifications of 12VDC/3A, 3800 rpm, and a valve diameter of 9.7 x 9.5 x 3.3 cm, a power output of 36W was achieved, with a pressure of 288.7 Pa or 0.00289 bar and an angular velocity of 398.1 rad/s. When the burner stove was first ignited, the flame appeared yellow. With a voltage of 3.7VDC/3A, it produced a rotation of 3795 rpm, a yellow flame, a flame height of 8 cm from the stove, and a flame width diameter of approximately 18 cm. At a voltage of 3.7VDC, the pressure measured 0.000964 bar, with a flame temperature of 275°C (as measured by an infrared sensor). A voltage of 7.4VDC resulted in a pressure of 0.0192 bar and a flame temperature of 350°C, while a voltage of 11.8VDC produced a pressure of 0.0289 bar with a maximum flame temperature of 420°C. For fuel consumption over 10 minutes at 3.7VDC/3A, the flame height reached 7-10 cm, with a wind pressure of 0.000964 bar and a fuel consumption of 0.237 grams.
Keywords : embedded system burner stove; microcontroller; snail dc motor.
Abstrak: Dilatar belakangi masalah kelangkaan elpiji didesa tomuanhollbung, serta tidak berhasilnya konversi kompor elpiji menuju kompor listrik karena daya listrik rumah masyarakat berdaya 450wat, daya kompor pemerintah 900watt, sehingga tidak bisa digunakan. Dari masalah tersebut, tujuan utama penelitian ini merancang kompor berbahan bakar oli bekas, yang mampu mengatasi masalah kelangkaan gas elpiji dan tidak terpakainya kompor dari pemerintah psat. Metode penelitian ini menggnakan metode prototype sehingga menghasilkan satu produk kompor burner dengan mengatur kecepatan motor DC. Hasil penelitian mendapati data pengujian mendapati bahwa dengan menggunakan motor DC Keong spesifikasi tegangan 12VDC/3A, 3800 rpm, dengan diameter katup 9,7 x 9.5 x 3.3cm menghasilkan daya 36W, dengan tekanan 288.7Pa atau 0.00289bar kecepatan sudut 398.1 rad/s. Ketika kompor burner pertama kali dinyalakan, warna api berwarna kunig. Jika tegangan 3.7VDC/3A akan menghasilkan putaran 3795rpm nyala api kuning, tinggi api 8cm dari tunggku kompor, dan diameter lebar keluarnya api dari tungku berkisar 18cm. Tegangan 3,7VDC maka menghasilkan tekanan 0.000964bar, nyala api 275 0C (pembacaan sensor infrared). Tegangan 7.4VDC menghasilkan tekanan 0.0192 bar, nyala api 350 0C, dan Tegangan 11.8 VDC tekanan 0.0289 bar, nyala api maksimal 420 0C. Untuk konsumsi bahan bakar selama 10 menit, dengan tegangan 3.7VDC/3A mendapati nyala api setinggi 7-10 cm, tekanan angin senilai 000964 bar dan konsumsi bahan bakar 0.237 gram. Kesimpulan penelitian ini mendapati bahwa nyala api kompor burner bisa di atur seperti nyala api kompor elpiji pada umum nya.
Kata kunci: kompor burner embedded system, microcontroller, motor dc keong.
Abstract:Abstract: The development of AI assistants such as Gemini and ChatGPT can significantly assist in daily human tasks. In the field of Sentiment Analysis, AI assistants can be utilized as an automated labeling alternative…
to provide positive, negative, or neutral sentiments within a dataset. This research aims to enhance the performance of AI assistants in automated labeling processes by employing the Feature Selection algorithm, specifically Forward Selection. The methodology involves utilizing the Naïve Bayes and K-NN algorithms, and subsequently improving accuracy through the Feature Selection algorithm. The evaluation is conducted using K-Fold Cross Validation. Research findings indicate an improvement in the accuracy of the best model, which is ChatGPT, when using the Naïve Bayes algorithm and Shuffled Sampling technique. The initial accuracy of 79.09% increased to 87.18% after Feature Selection was applied. This demonstrates the effectiveness of Feature Selection, particularly Forward Selection, in enhancing the accuracy performance of the model.
Keywords: ai; assistant; chat gpt; feature selection; gemini.
Abstrak: Pekembangan Asisten AI seperti Gemini dan Chat GPT dapat membantu pekerjaan manusia sehari-hari. Dalam bidang Analisis Sentimen, Asisten AI dapat digunakan sebagai alternatif pelabelan otomatis untuk memberikan sentimen positif, negatif atau netral dalam suatu dataset. Penlitian ini bertujuan untuk meningkatkan performa yang dihasilkan oleh Asisten AI dalam proses pelabelan otomatis menggunakan Algortima Feature Selection yaitu Forward Selection. Metode yang digunakan adalah dengan menggunakan Algoritma Naïve Bayes dan K-NN kemudian hasil akurasi akan ditingkatkan menggunkan Algoritma Feature Selection. Evaluasi yang digunakan adalah K-Fold Cross Validation. Hasil penelitian menunjukkan peningkatan akurasi model terbaik berada pada Chat GPT dengan menggunakan Algoritma Naïve Bayes dan Teknik Shuffled Sampling, dari nilai akurasi awal sebesar 79.09%, setelah ditingkatkan menggunakan Feature Selection, maka nilai akurasinya meningkat menjadi 87.18%. Hal ini membuktikan peran Feature Selection, dimana yang digunakan adalah Forward Selection dalam meningkatkan akurasi ternyata memang efektif dalam meningkatkan performa akurasi model.
Kata kunci: ai; assisten; chat gpt; feature selection; gemini
Abstract:Abstract: Mobile phones, as essential telecommunication devices today, are equipped with numerous features. The plethora of mobile phone models, especially gaming phones, requires consumers to be discerning in choosing a…
phone for everyday use. The problem is that many consumers do not understand how to purchase a phone that meets their specific criteria. The specifications that must be considered when selecting a gaming phone that fits within a budget and meets criteria include performance or specifications, screen quality, battery life, RAM, network connectivity, and price. A decision support system is a part of information systems designed to facilitate decision-making processes based on data or common everyday problems. The Weighted Product (WP) method is typically used in decision-making that involves multiple criteria to be considered simultaneously. Based on the WP method calculations, it was found that the recommended smartphone alternative is determined by the highest vector value (V) ranking according to user-defined criteria. The analysis results indicate that the recommended smartphone alternative is Alternative 1 with a score of 0.376, which is the Infinix GT 10 Pro, due to its comparable specifications to other models but with a more affordable price."
Keywords: decision support systems ; gaming cellphone; recommendation
Abstrak: Handphone sebagai perangkat telekomunikasi yang menjadi kebutuhan utama saat ini sudah dilengkapi dengan banyak fitur. Banyaknya keluaran jenis handphone khususnya handphone untuk game membuat konsumen harus pintar memilih handphone yang dapat digunakan setiap harinya Permasalahannya adalah konsumen banyak yang tidak paham bagaimana membeli handphone sesuai kriteria yang cocok. Adapun spesifikasi yang harus di saat akan memilih jenis handphone game yang sesuai dengan budget dan kriteria diantaranya adalah perfoma atau spesifikasi, tingkat kualitas layar, daya tahan batrai, RAM, koneksi jaringan, dan harga. Sistem pendukung keputusan merupakan bagian dari sistem informasi yang digunakan untuk memudahkan proses pengambilan keputusan berdasarkan data atau permasalahan yang sering ditemui dalam kehidupan sehari-hari. Metode Weighted Product umumnya digunakan dalam pengambilan keputusan yang melibatkan banyak kriteria yang harus dipertimbangkan secara bersamaan. Berdasarkan proses perhitungan dengan metode WP maka didapatkan bahwa alternatif smartphone yang direkomendasikan untuk dipilih adalah smartphone yang ditentukan berdasarkan peringkat nilai vektor (V) tertinggi sesuai dengan kriteria yang ditetapkan oleh pengguna. Hasil analisis menunjukkan bahwa alternatif smartphone yang direkomendasikan adalah Alternatif 1 dengan skor 0.376, yaitu Infinix GT 10 Pro karena memiliki spesifikasi yang hampir setara dengan yang lain namun dengan harga yang lebih terjangkau.
Kata kunci: handphone game; sistem penunjang keputusan; rekomendasi
Abstract:Abstract: Information, modeling, and data manipulation systems are called decision support systems (DSS). When there is uncertainty about the best course of action in semi-structured or unstructured situations, the system…
m is utilized to support decision-making. There are various approaches available for producing decision support systems, one of which is the Weighted Product (WP) Method. With the Weighted Product (WP) approach, attribute ratings are connected by multiplication; however, each attribute's rating must first be increased to the power of the attribute's weight. The normalizing process is same to this one. SPK procedure to choose the winners of the scholarships. Scholarship information from MTS Swasta Alwasliyah Simpang Merbau can be saved in the Decision Support System using this method. This way, in the event that an error arises when entering grades or scholarship information, the wrong information can be fixed without requiring the scholarship information to be re-input. Scholarships are presents to individuals in the form of financial aid intended to be utilized toward their ongoing educational pursuits.
Keywords : decision support system; students; weighted product method
Abstract: Sistem informasi, pemodelan, dan manipulasi data disebut sistem pendukung keputusan (DSS). Ketika terdapat ketidakpastian mengenai tindakan terbaik dalam situasi semi-terstruktur atau tidak terstruktur, sistem digunakan untuk mendukung pengambilan keputusan. Terdapat berbagai pendekatan yang tersedia untuk menghasilkan sistem pendukung keputusan, salah satunya adalah Metode Weighted Product (WP). Dengan pendekatan Weighted Product (WP) memiliki konsep yang sederhana untuk menentukan pembobotan terhadap kriteria yang memiliki nilai hampir sama sehingga dalam penentuan penerima beasiswa dapat mudah dilakukan walaupun dengan data yang banyak. Metode Weighted Product (WP) dengan kriteria penilaian akademik, sikap dan tanggung jawab dan hasil perhitungan tertinggi menggunakan sistem yaitu 0.27. Sehingga dapat diterapkan untuk menyeleksi siswa-siswi berprestasi dan untuk menerapkan pemilihan siswa-siswi berprestasi secara online dengan disebarkan kedalam kelas.
Keywords: metode weighted product; sistem pendukung keputusan; siswa
Abstract:Abstract: The current development of technology has successfully met various societal needs, one of which is the buying and selling activities. This development has led people to engage in online transactions, where buyers…
rs do not necessarily have to meet sellers in person. Tokopedia is one of the most popular e-commerce platforms used in Indonesia. Security issues arose when in 2020 Tokopedia experienced a breach, with data from around 91 million accounts being compromised by hackers. Consequently, Tokopedia needed to establish a Data Protection and Privacy Office (DPPO) to protect and safeguard user data privacy.This research addresses how perceptions of security and privacy can influence users' trust in transacting on Tokopedia. Using multiple linear regression analysis, the study evaluates the relationship between perceptions of data security and privacy with trust in transacting on Tokopedia. Based on the calculations of the multiple linear regression model using previously collected respondent data, it was found that perceptions of data security do not directly affect trust in transactions. However, perceptions of privacy are considered to have a significant influence and can increase trust in transactions among students in Pekanbaru.
Keywords: data security; e-commerce; tokopedia; transaction trust; user perceptions
Abstrak: Perkembangan teknologi saat ini telah sukses mencapai berbagai kebutuhan masayarakat salah satunya kegiatan jual beli, perkembangan ini membawa manusia untuk dapat melakukan jual beli secara online dimana tidak mengharuskan pembeli bertemu penjual secara langsung. Tokopedia menjadi salah satu platform e-commerce yang sangat popular digunkanan diindonesia. Masalah keamaan terjadi dimana pada tahun 2020 tokopedia mengalami peretasan dengan sekitar 91 juta akun berhasil diperoleh datanya oleh peretas, sehingga Tokopedia perlu membentuk data protection and privacy office (DPPO) guna melindungi dan menjaga privasi data pengguna Tokopedia.terkait hal tersebut penelitian ini mengangkat bagaimana persepsi keamanan dan privasi dapat mempengaruhi kepercayaan pengguna dalam bertransaksi ditokopedia. Dengan menggunakan metode regresi linear berganda, evaluasi dilakukan untuk menjelaskan hubungan antara persepi keamanan data dan privasi terhadap kepercayaan bertransaksi ditokopedia. Berdasarkan perhitungan model regresi linear berganda menggunakan data responden yang telah dilakukan sebelumnya didapat persepsi keamanan data terhadap kepercayaan bertransaksi tidak berpengaruh secara langsung. Namun pada persepsi privasi terhadap kepercayaan bertransaksi dinilai sangat berpengaruh dan dapat meningkatkan kepercayaan bertransaksi di kalangan mahasiswa di pekanbaru.
Kata kunci: e-commerce; keamanan data; kepercayaan transaksi; persepsi pengguna; tokopedia