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All Journal Jurnal Simantec ELINVO (Electronics, Informatics, and Vocational Education) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Nasional Komputasi dan Teknologi Informasi KOMPUTEK Journal of Information Systems and Informatics JATI (Jurnal Mahasiswa Teknik Informatika) International Journal of Science, Engineering and Information Technology Journal Of Information And Technology Unimor (JITU) Journal of Scientech Research and Development Keris: Journal of Community Engagement Insand Comtech : Information Science and Computer Technology Journal Innovative: Journal Of Social Science Research Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Yudha Dwi Putra Negara, Yudha
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Aerospace Engineering Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Neuroscience Public Health Social Sciences Transportation Other

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Analisis Pemanfaataan Webqual 4.0 Dan Customer Satisfaction Index (CSI) Dalam Menilai Kualitas Website Terhadap Kepuasan Pelanggan Pada Aplikasi Tokopedia Fikri, Muhammad; Herawati, Sri; Negara, Yudha Dwi Putra
KOMPUTEK Vol. 8 No. 2 (2024): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v8i2.3033

Abstract

Tokopedia's website is declining because customers complain about Tokopedia's service quality. The improvement of website services aims to increase the ranking and user satisfaction of the Tokopedia website has not yet achieved optimal results. With this, research was conducted to analyse the use of Webqual 4.0 and Customer Satisfaction Index (CSI) in assessing the quality of the website on customer satisfaction on the Tokopedia application. From the results of the Validity Test of the level of importance and satisfaction, the r table which has a significance level of 0.05 with respondents as many as 100 people is 0.1966. The results of the calculated r value > r table value as a result the entire attribute is valid and can be used in research and the results of the Reliability Test of interests and satisfaction are worth Cronbach's Alpha> 0.6 (Reliable requirement value), as a result the questionnaire can be declared Reliable. From the results of the CSI calculation, a value of 80.4% was obtained. The CSI value obtained lies in the 66% - 80.99% index with the description "satisfied". With this it is concluded that overall customers are satisfied with the quality of the website on the tokopedia application.
Klasifikasi Pemilihan Jenis Obat untuk Pasien menggunakan Algoritma K-Nearest Neighbor (K-NN) Uddin, Syah Rafi; Putra Negara, Yudha Dwi; Fatah, Doni Abdul
KOMPUTEK Vol. 9 No. 1 (2025): April
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v9i1.3174

Abstract

Memilih jenis obat yang sesuai dengan kebutuhan pasien merupakan salah satu aspek penting dalam dunia medis yang mempengaruhi efektivitas pengobatan dan keselamatan bagi pasien itu sendiri. Dengan semakin berkembang nya dunia teknologi informasi, pengambilan keputusan dalam pemilihan obat kini dapat didukung dengan menggunakan metode machine learning. Penelitian ini tentunya juga bertujuan untuk mengembangkan sistem klasifikasi pemilihan jenis obat menggunakan algoritma K-Nearest Neighbor (K-NN). Data yang digunakan dalam penelitian ini terdiri atas, umur pasien, jenis kelamin pasien, tekanan darah pasien, dan juga jenis obat. Algoritma K-NN dipilih karena kemampuannya dalam mengklasifikasikan data berdasarkan kedekatan atribut pasien dengan data yang telah terlabel sebelumnya. Parameter 𝑘 yang optimal ditentukan untuk memaksimalkan akurasi prediksi. Sistem ini tentunya sangat diharapkan untuk dapat membantu para tenaga medis dalam membuat keputusan yang lebih cepat dan tepat dalam pemilihan obat. Serta mengurangi resiko kesalahan dalam pemberian obat. Proses pengolahan data dalam penelitian ini mencakup tahapan data understanding, data cleaning, exploratory data analysis (EDA), data preparation, hingga modeling. Model K-Nearest Neighbors (K-NN) dengan parameter 𝑘 = 3 berhasil mencapai tingkat akurasi sebesar 78%, menunjukkan potensi pendekatan ini dalam analisis data yang dilakukan.
Analisis Sentimen Masyarakat Terhadap Penerima Beasiswa Kartu Indonesia Pintar Kuliah Dengan Metode Support Vector Machine Jannan, M Fahriz Zain; Dwi Putra Negara, Yudha
Journal of Information and Technology Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i2.7598

Abstract

Kartu indonesia pintar merupakan upaya pemerintah membantu para siswa berprestasi yang memiliki keterbatasan ekonomi untuk melanjutkan studi ke perguruan tinggi. Ramainya pembahasan kartu indonesia pintar di twitter membuat penulis tertarik untuk mengetahui sentimen masyarakat terhadap penerima beasiswa kartu indonesia pintar kuliah dengan keyword “KIPK”. Sentimen terdiri dari sentimen negatif, positif, dan netral. Metode yang di gunakan menganalisis pendapat masyarakat pada media sosial twitter mengunakan Support Vector Mechine ( SVM ). Term Frequency-inverce document Frequency ( TF-IDF ) kami gunakan untuk melakukan pengukuran seberapa penting kata dalan suatu data. Sedangkan untuk mengukur kinerja klasifikasi SVM menggunakan metode Confusion Matrix. Karnel linear merupakan karnel yang kami gunakan pada analisis data. Hasil evaluasi yang di dapat yaitu 81,82%, precession 80%, recall 82%, dan F1-score 78%, dapat di simpulkan bahwa sentimen masyarakat pada media sosial twitter terhadap penerima beasiswa kartu indonesia pintar kuliah lebih condong ke sentimen netral.
PREDIKSI KURS MATA UANG RIYAL KE RUPIAH MENGGUNAKAN METODE SUPPORT VECTOR REGRESSION (SVR) Andika Wahyudi; Wahyudi Setiawan; Yudha Dwi Putra Negara
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.3307

Abstract

Currency exchange rates have an important role in a country's development and economy, especially in international trade and investment. Currency exchange rate fluctuations can have a significant impact on various aspects of the economy. One example is the Rupiah exchange rate against the Saudi Arabian Riyal (SAR), which is important for many Indonesian citizens who undertake the Hajj and Umrah. Currency exchange rate prediction is a complex task because it is influenced by various economic, political, and social factors. Therefore, a method is needed that is able to accommodate the complexity and dynamics of the data. One potential method for predicting currency exchange rates is Support Vector Regression (SVR). SVR is a machine learning method that has demonstrated good performance in various prediction applications due to its ability to handle non-linear data and capture complex patterns in data. This research aims to apply the SVR method to predict the Riyal currency exchange rate against the Rupiah. Prediction accuracy will be measured using Mean Absolute Percentage Error (MAPE). This research is expected to contribute in providing an accurate and efficient tool for predicting the Riyal exchange rate against the Rupiah, providing insight into the application of SVR in currency exchange prediction, and providing practical guidance in implementing the SVR method for the purpose of predicting currency exchange rates. Based on 120 test analyses using the Support Vector Regression (SVR) method using data compositions of 90: 10, 80: 20, and 70: 30, the Mean Absolute Percentage Error (MAPE) value is 0.817317 in testing using a data composition of 90: 10.
Pendampingan Sertifikasi Produk Halal bagi Pelaku Usaha Mikro dan Kecil di Desa Tanjung Deykha Aguilika; Muh. Syarif; Muhammad Ersya Faraby; Yudha Dwi Putra Negara
Keris: Journal of Community Engagement Vol. 4 No. 1 (2024): KERIS: Journal of Community Engagement
Publisher : Institut Pesantren Sunan Drajat Lamongan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55352/keris.v4i1.737

Abstract

The number of MSMEs in Pamekasan Regency itself has increased from 2015-2020, in 2020 the number of MSMEs in Pamekasan Regency reached 9,441 MSMEs. The percentage of fostered MSMEs shows a fluctuating number from 2015-2020, in 2020 the percentage of fostered MSMEs in Pamekasan Regency reached 62.67%. The percentage of MSMEs that received capital assistance in Pamekasan Regency has increased from 2015-2020, in 2020 the percentage of MSMEs that received capital assistance in Pamekasan Regency reached 88%.To increase economic empowerment, the Abdimas team in collaboration with the Halal Center of Trunojoyo Madura University and students will hold training activities and assistance in registering halal certificates to support the marketability and commerciality of products produced by micro and small entrepreneurs in Tanjung Village, Pademawu District, Pamekasan Regency. The focus of this activity aims to: (1) Human resource development (2). Increase awareness of halal products and halal certification (3). Introducing digitalization of procedures and procedures for applying for a halal certificate to BPJP through SiHalal (4). Assisting in applying for halal certification to Bpjph (5) Verification and validation through the SiHalal system. Abdimas targets are micro and small businesses in the scope of food and beverages in Tanjung Village, Pademawu District, Pamekasan Regency. Activities are divided into 3 (three) stages, namely preparation, implementation, and evaluation.
Pemberdayaan Petani Muda melalui Pelatihan Pertanian Digital dan Pemasaran Online Hasil Tani Berbasis Syariah Abdul Fatah, Doni; Dwi Putra Negara, Yudha; Nasrulloh, Nasrulloh
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 2 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 2 (October 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i2.3584

Abstract

Desa Rosep, Kecamatan Blega, Kabupaten Bangkalan merupakan desa agraris yang sebagian besar penduduknya berprofesi sebagai petani, yang terletak di pulau Madura. Namun, produktivitas dan nilai jual hasil pertanian belum optimal karena kurang sadarnya potensi kemampuan petani muda dalam memanfaatkan teknologi digital. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberdayakan masyarakat khusunya para petani muda melalui pelatihan pertanian digital dan pemasaran digital hasil tani yang berlandaskan prinsip syariah. Metode pelaksanaan meliputi empat tahap utama, yaitu sosialisasi dan identifikasi kebutuhan mitra, pelatihan pertanian digital dan pemasaran digital, pendampingan penerapan teknologi, dan evaluasi hasil pelatihan. Hasil kegiatan menunjukkan peningkatan signifikan dalam kemampuan petani muda mengelola media sosial dan platform e-commerce untuk memasarkan produk pertanian. Selain itu, peserta juga memperoleh pemahaman mengenai prinsip-prinsip syariah dalam transaksi bisnis, seperti kejujuran, transparansi, dan keadilan harga. Luaran hasil kegiatan ini adalah website desa, publikasi media masa, HkI sederhana, Video Pengabdian, Dokumen kerjasama dan juga publikasi jurnal pengabdian, selain itu dari hasil kegiatan ini juga menjadi langkah awal dalam membangun ekosistem pertanian digital berbasis syariah yang berkelanjutan di Desa Rosep.
Penerapan SMOTE dan Chi-Square Feature Selection untuk Meningkatkan Akurasi Model Multinomial Naïve Bayes dalam Analisis Sentimen Video “Presiden Prabowo Menjawab” di YouTube M Ubaidillah; Doni Abdul Fatah; Yudha Dwi Putra Negara
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 5 (2025): Oktober 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i5.9807

Abstract

Abstrak - Perkembangan platform digital seperti YouTube telah menciptakan ruang publik baru untuk diskusi politik, dimana kolom komentar menjadi cerminan langsung tanggapan masyarakat terhadap konten politik. Penelitian ini menganalisis sentimen publik terhadap video Presiden Prabowo Menjawab di YouTube menggunakan algoritma Multinomial Naïve Bayes yang dioptimasi dengan seleksi fitur Chi-Square dan teknik SMOTE untuk penanganan ketidakseimbangan data. Data diperoleh melalui web scraping sebanyak 4.649 komentar dari tiga channel YouTube terkemuka. Preprocessing teks dilakukan melalui cleaning, case folding, normalisasi, tokenizing, stopword removal, dan stemming. Hasil penelitian menunjukkan bahwa model mencapai akurasi sebesar 67% dengan precision kelas positif 72% dan recall kelas negatif 81%. Hasil analisis mengungkapkan bahwa model lebih efektif dalam mengidentifikasi komentar negatif dibandingkan positif, yang merefleksikan karakteristik unik pola linguistik dalam diskusi politik di platform digital. Penelitian ini memberikan kontribusi dalam pengembangan sistem analisis sentimen otomatis untuk konten politik serta menjadi dasar untuk pemantauan opini publik di era digital.Kata kunci: Analisis Sentimen; Naïve Bayes; Chi-Square; SMOTE; Abstract - The development of digital platforms such as YouTube has created a new public space for political discussion, where comment sections directly reflect public responses to political content. This study analyzes public sentiment toward the video “Presiden Prabowo Menjawab” (President Prabowo Responds) on YouTube using a Multinomial Naïve Bayes algorithm optimized with Chi-Square feature selection and SMOTE technique for data imbalance handling. Data was obtained through web scraping of 4,649 comments from three leading YouTube channels. Text preprocessing was carried out through cleaning, case folding, normalization, tokenizing, stopword removal, and stemming. The results show that the model achieved an accuracy of 67% with a positive class precision of 72% and a negative class recall of 81%. The analysis results reveal that the model is more effective in identifying negative comments than positive ones, reflecting the unique characteristics of linguistic patterns in political discussions on digital platforms. This research contributes to the development of an automatic sentiment analysis system for political content and serves as a basis for monitoring public opinion in the digital era.Keywords: Sentiment Analysis; Naïve Bayes; Chi-Square; SMOTE;
Analisis Data Penjualan Sepatu Nike Tahun 2020-2021 Menggunakan Platform Business Intelligence Zoho Analytics Jefri Maulana Haq; Yudha Dwi Putra Negara; Doni Abdul Fatah
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 1 (2025): Februari 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i1.8714

Abstract

Abstrak - Dalam era digital yang berkembang pesat, data memiliki peran penting dalam mendukung pengambilan keputusan strategis, khususnya di industri ritel yang kompetitif. Nike, sebagai salah satu produsen sepatu olahraga terbesar di dunia, menghadapi tantangan besar selama pandemi Covid-19 pada periode 2020-2021, yang mendorong perubahan pola konsumsi masyarakat dari toko fisik ke platform online. Kondisi ini memerlukan analisis mendalam terhadap data penjualan guna memahami tren konsumen, produk terlaris, dan wilayah dengan performa terbaik. Penelitian ini bertujuan menganalisis data penjualan sepatu Nike pada periode 2020-2021 dengan menggunakan platform Business Intelligence (BI) Zoho Analytics. Zoho Analytics dipilih karena kemampuannya mengintegrasikan data dari berbagai sumber, memvisualisasikan data secara interaktif, serta menyediakan fitur analisis otomatis berbasis AI. Dataset yang digunakan meliputi 9.360 transaksi penjualan dari berbagai wilayah di Amerika Serikat, dengan rincian informasi seperti tanggal transaksi, jenis produk, metode penjualan, lokasi geografis, harga per unit, dan total penjualan.Hasil analisis menunjukkan tren penjualan bulanan selama 2020-2021, identifikasi produk terlaris, wilayah dengan performa penjualan tertinggi, dan performa retailer berdasarkan metode penjualan. Selain itu, ditemukan pengaruh signifikan harga per unit terhadap jumlah unit yang terjual. Penggunaan Zoho Analytics terbukti meningkatkan efisiensi pengolahan data, menghasilkan informasi akurat, dan memfasilitasi pengambilan keputusan yang cepat dan tepat. Penelitian ini memberikan wawasan strategis bagi Nike dalam mengoptimalkan pemasaran, pengelolaan stok, serta perencanaan produk di masa depan. Manfaat menggunakan Zoho Analytics, perusahaan dapat mengidentifikasi peluang pasar baru, meningkatkan efisiensi operasional, dan mempertahankan daya saing di pasar global.Kata kunci: Business Intelligence, Efisiensi Operasional,  Nike, Tren Konsumen, Zoho Analytics Abstract - In the rapidly evolving digital era, data plays an important role in supporting strategic decision-making, especially in the competitive retail industry. Nike, as one of the largest sports shoe manufacturers in the world, faced major challenges during the Covid-19 pandemic in the 2020-2021 period, which drove changes in people's consumption patterns from physical stores to online platforms. This condition requires an in-depth analysis of sales data to understand consumer trends, best-selling products, and regions with the best performance. This study aims to analyze Nike shoe sales data in the 2020-2021 period using the Zoho Analytics Business Intelligence (BI) platform. Zoho Analytics was chosen because of its ability to integrate data from various sources, visualize data interactively, and provide AI-based automatic analysis features. The dataset used includes 9,360 sales transactions from various regions in the United States, with detailed information such as transaction date, product type, sales method, geographic location, price per unit, and total sales. The results of the analysis show monthly sales trends during 2020-2021, identification of best-selling products, regions with the highest sales performance, and retailer performance based on sales methods. In addition, it was found that the price per unit had a significant effect on the number of units sold. The use of Zoho Analytics has been proven to increase data processing efficiency, produce accurate information, and facilitate fast and precise decision making. This study provides strategic insights for Nike in optimizing marketing, inventory management, and future product planning. By utilizing Zoho Analytics, the company can identify new market opportunities, improve operational efficiency, and maintain competitiveness in the global market.Keywords: Business Intelligence, Operational Efficiency, Nike, Consumer Trends, Zoho Analytics
Co-Authors Aeri Rachmad Al-Afghoni, J.M. Havidz Yasaf Anas Al Ayubi, Muhammad Andharini Dwi Cahyani Andika Wahyudi Budi Dwi Satoto Budi Soesilo Budi Soesilo Deykha Aguilika Doni Abdul Fatah Faisol Arif Efendi Farhan Reynaldi Valerian Farihatul Mahbubah Fifin Ayu Mufarroha Fifin Ayu Murfarroha Husni Husni Husni i Ifandia, Alfian Mahendra Ika Oktavia Suzanti Jannan, M Fahriz Zain Javier, Najamuddin Jefri Maulana Haq Khozaimi, Ach. M Ubaidillah M. Syarief Moh Jufriyanto Muh. Syarif Muhammad Ersya Faraby Muhammad Fikri Muhammad Rafidianto Nasrulloh Nasrulloh Novi Prastiti, Novi Radiah, Aisyatur Reza Airlangga Rochman, Eka Mala Sari Shofia Hardi Sri Herawati Syakur, Muhammad Ali Uddin, Syah Rafi Umam, Khotibul Vina Angelina Savitri Wahyudi Setiawan