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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Sistem dan Informatika International Journal of Law Reconstruction Jurnal Pendidikan Informatika dan Sains Jurnal Khatulistiwa Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Al-Khidmah JURNAL EDUCATION AND DEVELOPMENT NUSANTARA : Jurnal Ilmu Pengetahuan Sosial CYBERNETICS BULETIN AL-RIBAATH JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) GERVASI: Jurnal Pengabdian kepada Masyarakat Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Teknika Jurnal Abdi Insani JIKA (Jurnal Informatika) Journal of Innovation Information Technology and Application (JINITA) Innovation in Research of Informatics (INNOVATICS) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) JUTECH : Journal Education and Technology Jurnal Pengabdian Masyarakat Nusantara Jurnal Media Informatika JUSTIN (Jurnal Sistem dan Teknologi Informasi) Joutica : Journal of Informatic Unisla Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Jurnal Ilmiah Teknik Informatika dan Komunikasi Kohesi: Jurnal Sains dan Teknologi SmartComp Jurnal Informatika Polinema (JIP) Journal of Multidiscipline and Collaboration Research Jurnal Ragam Pengabdian JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) KREATIF: Jurnal Pengabdian Masyarakat Nusantara TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Journal of Accounting Research, Utility Finance and Digital Assets (JARUDA)
Syarifah Putri Agustini Alkadri
Universitas Muhammadiyah Pontianak, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology 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 Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Penguatan Kelompok Tuna Rungu Gerkatin Kalbar Melalui Pelatihan Digital Marketing Untuk Inklusi Digital Arninda, Arninda; Putri Agustini, Syarifah; Istikoma, Istikoma; Aditya Saputra, Rangga; Aliya Supandih, Fathia; Roni, Roni
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 5 No. 2 (2025): Agustus 2025 - Januari 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v5i2.6098

Abstract

The Community Partnership Program (PKM) aims to strengthen the capacity of the West Kalimantan Gerkatin disability group through digital marketing training to support inclusive digital transformation. Implemented by the Muhammadiyah University of Pontianak, this activity addresses partner issues related to weak financial management and limited access to digital marketing. Solutions provided include training in financial management, product photography, social media marketing, AI-based copywriting, and assistance in creating an online store via WooCommerce. On September 13 and 20, 2025, 35 deaf participants participated in the training with the support of a Sign Language Interpreter. As a result, 60% of participants were able to prepare financial reports, 75% understood digital marketing, and 70% produced catalog-worthy product photos and descriptions. The implementation of the program encountered challenges associated with participants’ limited baseline digital literacy; however, these were mitigated through intensive mentoring and the application of accessible, disability-friendly technologies. The program also produced a prototype website for cacatjualan.com and various outputs such as journal articles, media publications, videos, posters, and training materials that support the achievement of activities, particularly poverty alleviation, decent work, inequality reduction, and support for the university's Key Performance Indicators in the field of community service. The impact is seen in improving digital skills, social inclusion, and the economic potential of disability groups.
Prediksi Harga Mobil Bekas Menggunakan Algoritma Support Vector Regression Herlangga, Herlangga; Pangestika, Menur Wahyu; Alkadri, Syarifah Putri Agustini
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.10545

Abstract

The growth of the automotive industry in Indonesia has contributed to high demand for used cars as a more economical alternative to new cars. However, determining the price of used cars is often a challenge for showrooms and prospective buyers because it involves many factors and is subjective. This study aims to develop a used car price prediction model using the Support Vector Regression (SVR) algorithm with a Radial Basis Function (RBF) kernel approach. A total of 1,000 entries were obtained through web scraping from the cintamobil.com website. The research methodology refers to the CRISP-DM framework, starting from business understanding to model deployment through a web application using Streamlit. The preprocessing process involves handling missing values, outliers, data duplication, and numerical and categorical feature transformations. The SVR model was evaluated using RMSE, MAPE, and MAE metrics to assess prediction accuracy. The results show that SVR is capable of providing fairly accurate price predictions, with parameters C=1, gamma=0.1, and epsilon=0.1 producing the best performance, namely an MAE value of IDR 6,472,572, an RMSE of IDR 8,958,555, and a MAPE of 3.41%. Referring to the prediction accuracy category based on the MAPE value, where a MAPE value ≤ 10% is categorized as high accuracy, it can be concluded that this model has high prediction accuracy. This shows that the SVR model used is capable of estimating used car prices with a low error rate and good accuracy.
Integrasi Metode Forward Chaining dan Teorema Bayes Untuk Identifikasi Diagnosa Penyakit Kulit Pada Kucing Anugerah, Ade; Sucipto, Sucipto; Agustini Alkadri, Syarifah Putri
JURNAL FASILKOM Vol. 15 No. 3 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v15i3.10288

Abstract

Skin diseases in cats are among the most common health issues, yet many cat owners still lack awareness of their symptoms. Limited access to veterinary services, especially in regions such as West Kalimantan, poses a significant challenge in early identification and treatment. This study aims to develop a web-based expert system capable of automatically diagnosing skin diseases in cats based on symptoms inputted by users. The system utilizes the Forward Chaining method for rule-based inference and the Bayes Theorem for probabilistic calculation to determine the likelihood of diseases. The system was built using the Laravel framework and MySQL database, based on a total of 83 case data obtained through direct interviews with veterinary experts. Testing using black-box and user acceptance methods showed that the system functions effectively and delivers accurate and informative diagnostic results. The system achieved an accuracy rate of 100% when tested on validated expert data. Therefore, this system can serve as an effective tool for cat owners to quickly and independently gain initial insights into their cat’s skin health before consulting a veterinarian.
Prediksi Jumlah Kasus Penyakit Demam Berdarah Dengue Menggunakan Metode Long Short-Term Memory (LSTM) Nurmelidia Larasati; Sucipto Sucipto; Syarifah Putri Agustini Alkadri
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 6 No. 1 (2026): Maret : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v6i1.2100

Abstract

Dengue Hemorrhagic Fever (DHF) an infectious disease with fluctuating case numbers that can suddenly increase, posing significant public health challenges. In Pontianak City, 106 cases with 1 death were recorded in 2019, decreasing from 195 cases with 3 deaths in 2018. In 2020, the number dropped further to 27 cases with no fatalities. This condition indicates the need for a prediction system capable of accurately estimating the number of cases to support decision-making processes. This study aims to develop a model for predicting daily DHF cases in Pontianak City using the Long Short-Term Memory (LSTM) method. The data used includes daily DHF cases, average temperature, average humidity, and rainfall from 2020 to 2025. The research stages included data cleaning, normalization using Min-Max Scaling, historical data formation, model training, and evaluation using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The best model employed a single LSTM layer with 64 neurons, 50 epochs, and a batch size of 32, yielding an RMSE of 0.87 and MAE of 0.63. These results indicate that the LSTM method is capable of generating predictions close to actual values and is reliable for estimating daily DHF cases in Pontianak City. The developed Streamlit-based application provides interactive visualization and accurate predictions, making it a valuable tool for health authorities in DHF prevention and control efforts.
Prediction of Students’ Major Selection Using the Fuzzy SugenoMethod Based on Report Card Grades Raihan Anugrah Fakhri; Alda Cendekia Siregar; Syarifah Putri Agustini Alkadri
Jurnal Ragam Pengabdian Vol. 3 No. 1 (Spesial Issue) (2026): "Dharma Samudera"
Publisher : Lembaga Teewan Journal Solutions

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62710/h96zxc86

Abstract

This study aims to develop a student achievement prediction system based on the Fuzzy Sugeno method using average report card scores to support science or social studies specialization recommendations. The data were obtained from student report cards at SMA 1 Toho in Microsoft Excel format and processed through fuzzification, inference, and defuzzification stages using triangular membership functions to produce crisp values and achievement categories. The system was implemented using the Python programming language and evaluated for result consistency. The findings indicate that the Fuzzy Sugeno method can objectively predict student achievement and support data-driven decision making in determining student specialization
SISTEM PAKAR DIAGNOSA PENYAKIT TANAMAN JERUK MENGGUNAKAN METODE CERTAINTY FACTOR Pirman Pirman; Barry Ceasar Octariadi; Syarifah Putri Agustini Alkadri
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 2 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i2.10197

Abstract

Jeruk adalah komoditas utama di Desa Tekarang, Kabupaten Sambas, Kalimantan Barat. Namun, dalam beberapa tahun terakhir, produksi jeruk mengalami penurunan akibat serangan penyakit seperti lalat buah, kutu loncat, diplodia basah, dan kering, yang mengakibatkan penurunan kualitas dan kerugian bagi petani. Penelitian ini mengembangkan Sistem Pakar Diagnosa Penyakit Jeruk menggunakan metode Certainty Factor untuk membantu Dinas Pertanian dalam mendiagnosa penyakit berdasarkan gejala yang terdeteksi. Certainty Factor digunakan untuk mengukur tingkat keyakinan diagnosis guna meningkatkan akurasi hasil. Uji coba menunjukkan akurasi sistem sebesar 78,57% dibandingkan dengan diagnosis pakar. Sistem ini diharapkan dapat menjadi alat bantu efektif bagi petani dan pihak terkait dalam mengenali penyakit jeruk dan mengambil langkah pengendalian yang tepat.
Rice Planting Time Prediction Using SARIMA-MFEP Integration in Kubu Raya Sinta Rama Dani; Syarifah Putri Agustini Alkadri; Sucipto
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3233

Abstract

Extreme climate change has increased uncertainty in rice planting schedules, threatening food security in Kubu Raya Regency, West Kalimantan, and causing significant economic losses due to inaccurate seasonal predictions. This study integrates the Seasonal Autoregressive Integrated Moving Average (SARIMA) method with the Multi-Factor Evaluation Process (MFEP) to generate rice planting time recommendations based on scientific climate forecasting and multi-criteria agroclimatic evaluation. SARIMA is employed to forecast monthly rainfall, temperature, and humidity, while MFEP evaluates the feasibility of twelve alternative planting months using weighted criteria determined by local agricultural experts. The objective of this research is to develop an objective, accurate, and validated planting time prediction system to support farmers’ decision-making. The results show that the SARIMA model achieves very high accuracy, with Mean Absolute Percentage Error (MAPE) values below 2% for both temperature and humidity, and successfully captures 68% of seasonal rainfall variability. October is identified as the optimal planting month with the highest feasibility score, consistent with historical peak harvest patterns in January and February and aligned with regional literature. This integrated approach provides an end-to-end solution from forecasting to empirically validated, actionable recommendations, offering strong potential to reduce crop failure risk and enhance rice production efficiency under climate uncertainty.
Travel application itinerary using the traveling salesman problem method and the held-karp algorithm Ade Zaldi Eureka Zendar Ade; Syarifah Putri Agustini Alkadri; Izhan Fakhruzi
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 11 No 1 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v11i1.682

Abstract

The Kapuas Hulu Regency is home to several fascinating tourist spots, yet finding directions inside the regency can be challenging for visitors. The Held-Karp Algorithm can be used to find the fastest route between any two cities with only one stop, which is known as the Traveling Salesman Problem (TSP). Bellman, Held, and Karp created this dynamic program in 1962 with the goal of minimizing travel time and expenses. The number of cities to be visited (forming nodes in the graph), the point of origin (the starting node in the graph), and the distances between the cities (weights between the nodes) must all be specified in the model of the TSP problem before the Held-Karp Algorithm can be applied. The focus of this study will be tourist destinations in West Kalimantan's Kapuas Hulu Regency. A system that uses the Held-Karp Algorithm to find the shortest paths between different tourist spots in Kapuas Hulu Regency will be built as part of this project. As a result, this technology will help tourists plan their trips effectively and minimize their expenditures for both time and transportation
IMPLEMENTASI PENCARIAN DOKUMEN ADMINISTRASI DI KANTOR CAMAT MENGGUNAKAN METODE BM25 Yanti Puspita Sari; Syarifah Putri Agustini Alkadri; Rachmat Wahid Saleh Insani
NUSANTARA : Jurnal Ilmu Pengetahuan Sosial Vol 13, No 7 (2026): NUSANTARA : Jurnal Ilmu Pengetahuan Sosial
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jips.v13i7.2026.1990-1998

Abstract

Penelitian ini mengembangkan sistem pencarian dokumen administrasi berbasis web pada Kantor Camat Sekadau untuk meningkatkan efisiensi proses temu kembali dokumen. Permasalahan yang dihadapi adalah pengelolaan arsip yang masih didominasi dokumen fisik serta dokumen digital yang tersebar tanpa sistem pengindeksan yang memadai sehingga pencarian menjadi lambat dan kurang efektif. Tujuan penelitian ini adalah membangun sistem pencarian dokumen yang mampu memberikan hasil pencarian secara cepat dan relevan. Sistem dikembangkan menggunakan bahasa pemrograman Python dengan MongoDB sebagai basis data serta dilengkapi modul ekstraksi teks menggunakan Tesseract-OCR. Tahapan pengolahan teks meliputi case folding, tokenisasi, penghapusan stopword, dan stemming. Metode pencarian menggunakan algoritma BM25 dengan parameter k1 = 1,5 dan b = 0,75 untuk menghitung tingkat relevansi dokumen terhadap query pengguna. Hasil pengujian menunjukkan sistem menghasilkan skor relevansi tertinggi sebesar 3,3084 pada query spesifik, dengan nilai precision 100,00%, recall 3,23%, dan F1-score 6,10%. Hasil User Acceptance Testing (UAT) memperoleh tingkat penerimaan sebesar 88,8% dengan kategori “Sangat Layak”, sehingga sistem dinilai layak diterapkan untuk meningkatkan efisiensi pengelolaan dokumen.
PENERAPAN METODE NAÏVE BAYES DALAM SISTEM PAKAR BIMBINGAN KONSELING KARIR SISWA Fara Darniva; Barry Ceasar Octariadi; Syarifah Putri Agustini Alkadri
NUSANTARA : Jurnal Ilmu Pengetahuan Sosial Vol 12, No 12 (2025): NUSANTARA : JURNAL ILMU PENGETAHUAN SOSIAL
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jips.v12i12.2025.4755-4761

Abstract

Bimbingan konseling karir adalah proses yang dilakukan oleh guru bimbingan konseling dengan memberikan bantuan kepada peserta didik untuk mengalami perkembangan, pencarian dan membuat keputusan karir yang rasional sepanjang hidupnya serta realistis berdasarkan potensi yang dimiliki dan peluang yang ada di lingkungan sekitar sehingga meraih kesuksesan. Keterbatasan waktu dan jumlah guru Bimbingan Konseling menjadi permasalahan yang terjadi di sekolah tersebut dalam proses layanan bimbingan konseling karir terkait memberikan rekomendasi karir kepada siswa. Tujuan utama dari penelitian ini adalah untuk membangun aplikasi sistem pakar berbasis website menggunakan metode Naïve Bayes untuk memberikan rekomendasi karir kepada siswa berdasarkan nilai probabilitas tertinggi. Hasil dari penelitian ini memperoleh nilai 90,90% berdasarkan pengujian akurasi sistem, maka dapat dikatakan aplikasi ini berhasil dan bisa digunakan oleh siswa untuk melakukan bimbingan konseling karir.
Co-Authors ., Damsar Acep Supriyanto Ade Zaldi Eureka Zendar Ade Aditya Saputra, Rangga Agustian Agustian Ajmi, Nur Dzakiyyah Alda Cendekia Siregar Alda Cendekia Siregar Aliya Supandih, Fathia Alkhairi, Muhammad Ghozy Anas Shohibunnuril Mufida Andalas Rivaldi Permana Anita Anugerah, Ade Arninda Arninda Arninda, Arninda Asrul Abdullah Asyari, Bisma Barry Caesar Octariadi Barry Ceasar Octariadi Chatarina Umbul Wahyuni Diky Pratama Dila Adellia Dini Oktaviani Dwika, Arya Sukma Putra Eko Julianto Enkan Feny Nopitasari Erik Mario Sihotang Fakhruzi, Izhan Fara Darniva Fathia Aliya Supandih Hafi Risandika Hasim, Wahyudi Hazilina, Hazilina Heni Kriswanti Herlangga, Herlangga Indrayani Isra Pebrianti Istikoma Istikoma Kalsum, Dayang Nur Kristin Damay Asmara Kurnia Diana Mardian Adma Gumilang Masroni Maysa, Ade Medi, Medi Menur Wahyu Pangestika, Menur Wahyu Mochamad Wahyudi Muammar Khaddafi Muhammad Dwi Ramadhianto Muhammad Dwi Ramadhianto Novianti, Novianti Nurmelidia Larasati Otafyani, Mega Pirman Pirman Putri Yuli Utami Rachmat Wahid Saleh Insani Raihan Anugrah Fakhri Rangga Aditya Saputra Ria Sapitri Rizka Amalia Rizki Akbar Pratama Rizky Wahyu Prasetio Roni Roni Roni, Roni Ruhama, Ufi Ryan Permana Ryani Yulian Setiaji, Wanda Primadita Sinta Rama Dani Sucipto Sucipto Sucipto Sucipto Sucipto Sucipto Sucipto Sucipto Sufi Vanitra Sumirah Sumirah Sumirah Sumirah Tiara Tri Anita vera vibiola Vika Ummu Hani Wahyu Nugroho Wiguna, Seftyan Yanti Puspita Sari Yulrio Brianorman Yusuf Marwan Zuhrie Alifiansyah