Claim Missing Document
Check
Articles

Found 20 Documents
Search

Penerapan Metode AHP Dan MFEP Dalam Menentukan Penerima Bantuan Benih Padi Nur Jamiyyah; M. Fakhriza; Muhammad Dedi Irawan
Jurnal Ilmiah Sistem Informasi (JISI) Vol. 4 No. 2 (2025): OKTOBER
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jisi.v4i2.10066

Abstract

Penyaluran bantuan benih padi merupakan salah satu program pemerintah dalam meningkatkan produktivitas pertanian dan ketahanan pangan. Namun, proses seleksi penerima bantuan sering mengalami kendala karena keterbatasan kuota dan banyaknya kelompok tani yang mengajukan permohonan. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan (SPK) yang dapat membantu menentukan penerima bantuan secara objektif dan tepat sasaran. Metode yang digunakan adalah kombinasi Analytical Hierarchy Process (AHP) untuk menentukan bobot setiap kriteria, dan Multi Factor Evaluation Process (MFEP) untuk menghitung skor dan peringkat setiap alternatif. Kriteria yang digunakan meliputi terdaftar di simluhtan, mengajukan proposal, produktivitas lahan, luas lahan, dan status penerimaan bantuan sebelumnya. Hasil pengujian menunjukkan bahwa sistem mampu memberikan rekomendasi yang sesuai dengan kebijakan penyaluran bantuan. Sistem ini dibangun menggunakan bahasa pemrograman PHP dan basis data MySQL. Implementasi sistem ini diharapkan dapat meningkatkan transparansi, efisiensi, dan keadilan dalam proses pemberian bantuan benih padi.
Random Forest Regression Algorithm in Predicting Coconut Plantation Yields Nadia, Cut Mirna; M. Fakhriza
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1736

Abstract

Oil palm is one of Indonesia’s leading commodities with a significant contribution to the national economy. Production fluctuations caused by environmental and technical factors require an accurate predictive model. This study aims to predict Fresh Fruit Bunch (FFB) production using the Random Forest Regression algorithm based on data from PT Perkebunan Nusantara IV Regional 1, Bandar Selamat Unit (2022–2024). The research employed historical data including land area, number of trees, plant density, bunch count, and planting year. The model underwent preprocessing, training, testing, and evaluation using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and coefficient of determination (R²). Results show that Random Forest Regression achieved excellent accuracy with R² = 0.9846, MAE = 31,889.58 kg, and RMSE = 55,164.62 kg. The most influential factors were planting year, number of trees, and land area. In conclusion, Random Forest Regression is highly effective for predicting oil palm production and captures complex non-linear relationships among variables.
Classification of Hijab Types Based on Gray Level Co-occurrence Matrix Features and the K-Nearest Neighbor (KNN) Algorithm Faradita, Nazwa Alya; M. Fakhriza
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1737

Abstract

This study aims to build an automatic classification system to address the challenge of visually identifying hijab types by utilizing digital image processing technology. The research scope is limited to two categories: pashmina and instant hijabs. The applied method involves the Gray Level Co-occurrence Matrix (GLCM) to extract texture features in four angular directions, which yields four primary feature values: Contrast, Energy, Correlation, and Homogeneity. These features are subsequently classified using the K-Nearest Neighbor (KNN) algorithm with the Euclidean Distance metric. The dataset used consists of 60 image samples, divided into 48 training data and 12 test data. Testing was conducted with varying K-values (1, 3, 5, and 7). The results show that the classification system using the GLCM and KNN combination is effective, achieving a peak accuracy of 83.33% at K-values of 3, 5, and 7. This outcome confirms the capability of GLCM-extracted texture features to distinguish between the two hijab types and highlights the potential application of this system in the field of Muslim fashion.
Sistem Informasi Manajamen Persediaan Barang pada Toko Bangunan UD. Alnas Menggunakan Eqonomic Order Quantity (EOQ) Amiruddin Alnas; M. Fakhriza
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 2 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i2.38714

Abstract

This study aims to optimize inventory management at UD. Alnas Building Store by implementing the Economic Order Quantity (EOQ) method. The main problem faced by this store is the uncertainty in the quantity of orders that will come, which can result in excess or shortage of inventory. One effective way to manage inventory is by using an inventory management information system. This article discusses the use of an inventory management information system in UD Alnas Building Store. This system is used to collect, store, and process information related to the store's inventory. Several features in the information system, such as recording stock items, monitoring sales, determining inventory needs, calculating Cost of Goods Sold (COGS), and generating reports, greatly assist in effective inventory management. Although it has some drawbacks, the use of inventory management information systems has helped UD Alnas Building Store managers in monitoring stock items, calculating, determining inventory needs, and generating accurate and timely reports.
Implementasi Metode Smart Pada Analisis Penerimaan Bantuan Covid-19 Untuk Usaha Mikro Kecil Dan Menengah Kabupaten Labuhanbatu Utara Alviah Maeylani; M. Fakhriza
Journal of Computers and Digital Business Vol. 1 No. 2 (2022)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (546.767 KB) | DOI: 10.56427/jcbd.v1i2.10

Abstract

Bantuan Covid-19 merupakan bentuk kepedulian pemerintah terhadap masyarakat di masa pandemi seperti ini. Terutama bagi para pedagang yang mengalami banyak penurunan pendapatan dan menutup paksa dagangannya. Hal ini menjadi pertimbangan Pemerintah untuk membantu para pedagang bangkit kembali dengan memberikan bantuan keuangan. Dalam memberikan bantuan, masyarakat harus menyediakan dokumen persyaratan yang diminta oleh Dinas Perdagangan dan Koperasi Usaha Kecil dan Menengah. Dalam rangka pemberian bantuan diperlukan strategi yang bijak dan tepat agar bantuan yang diberikan tepat sasaran kepada pedagang yang berhak atas haknya. Penelitian ini membahas bagaimana menentukan komunitas yang tepat untuk mendapatkan bantuan dengan menganalisis data yang ada berdasarkan kriteria yang telah ditentukan. Penelitian ini bertujuan untuk membantu Dinas Perdagangan dan Koperasi Usaha Kecil Menengah Kabupaten Labuhanbatu Utara dalam mengevaluasi dan mengembangkan strategi yang lebih efektif dan efisien dengan memperhatikan setiap data yang diperoleh dari hasil proses analisis. Metode yang digunakan untuk menentukan kelayakan penerima bantuan COVID-19 adalah metode SMART. Hasil implementasi pada aplikasi menunjukkan bahwa metode SMART mampu menentukan kelayakan pedagang dalam menerima bantuan COVID-19.
Perbandingan Metode SMART, SAW, MOORA pada Pembangunan Sistem Pendukung Keputusan Pemilihan Calon Mitra Statistik Afsha Zahara; Samsudin; M. Fakhriza
Journal of Computers and Digital Business Vol. 1 No. 2 (2022)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.064 KB) | DOI: 10.56427/jcbd.v1i2.17

Abstract

Perkembangan dari teknologi kini telah memungkinkan pengambilan keputusan untuk dapat dilakukan dengan cepat, mudah dan akurat sehingga dapat diterapkan di dalam sebuah instansi. Salah satunya BPS, yaitu Badan Pusat Statistik yang memiliki tanggung jawab dalam menyediakan kebutuhan data yang dapat digunakan oleh masyarakat dan pemerintah. Untuk pengumpulan dan pengelolaan data, BPS selalu mengharapkan kinerja dari mitra statistik yang berkompeten agar menghasilkan kualitas data terbaik. Untuk tercapainya tujuan dalam pemilihan calon mitra statistik berkompeten maka dapat didukung oleh teknologi sistem pendukung keputusan. Dalam pembangunan sistem pemilihan calon mitra statistik ini akan menerapkan tiga metode sistem pendukung keputusan yaitu metode SMART, SAW, dan MOORA. Penggunaan dari ketiga metode ini yaitu bertujuan membandingkan sistem dengan tiap metode untuk mendapatkan sistem dengan metode mana yang lebih akurat, relevan dan mudah diterapkan. Untuk pembangunan sistem berbasis website ini penulis menggunakan bahasa pemrograman PHP dan basis data MySQL. Sedangkan metode pengembangan sistem yang digunakan yaitu metode RAD. Hasil penelitian dan pengujian terhadap 100 data calon mitra statistik diperoleh nilai akurasi dari metode SMART sebesar 100%, metode SAW 97%, dan metode MOORA 37%.
Design and Development of a Mobile Based Reservation System for Muslims in Medan Atika, Rindi; M. Fakhriza; Muhamad Alda
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5098

Abstract

Salon Muslimah Dina is a privately owned business offering a variety of beauty treatments specifically for women. Operationally, the salon still uses a manual system, requiring customers to visit in person or contact them via WhatsApp to make reservations or inquire about services. The high volume of inquiries slows down the service process, as the salon must respond to messages individually. Furthermore, the lack of transaction data records often results in long wait times for walk-in customers and inconsistencies in service delivery. Important information such as operating hours, service types, prices, and locations are also not communicated effectively to potential customers. To address these issues, an online reservation system was developed to disseminate information and facilitate service bookings. This system utilizes the FCFS (First Come, First Served) scheduling method, where services are processed in the order of arrival and completed one by one. This method is considered fair because the entire process is handled in the order in which they arrived. The development results demonstrate that the reservation system has been successfully developed, with features that simplify customer bookings without having to visit in person, saving time and money. This system also helps the salon manage service data, schedules, and reservation information more optimally and efficiently.
Penerapan Metode Collaborative Filtering untuk Rekomendasi Pemilihan Bibit Herbal Temulawak Inneke Putri; M. Fakhriza
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9352

Abstract

Budidaya tanaman obat di Indonesia menunjukkan perkembangan signifikan seiring meningkatnya industri obat tradisional dan tren masyarakat terhadap gaya hidup alami. Temulawak (Curcuma xanthorrhiza) merupakan salah satu tanaman herbal unggulan yang memiliki nilai ekonomi tinggi serta manfaat kesehatan karena kandungan kurkuminoid, minyak atsiri, dan senyawa bioaktif lainnya. Namun, pemilihan bibit temulawak berkualitas masih sering dilakukan berdasarkan pengalaman subjektif petani, sehingga berpotensi menghasilkan ketidaktepatan dalam budidaya. Penelitian ini bertujuan menentukan bibit temulawak terbaik dengan menerapkan metode Collaborative Filtering sebagai sistem rekomendasi berbasis preferensi pengguna. Metode yang digunakan adalah pendekatan kuantitatif dengan model pengembangan sistem Rapid Application Development (RAD). Data diperoleh melalui observasi, wawancara, studi pustaka, serta pengumpulan rating bibit dari petani di Desa Pulo Bandring, Kabupaten Asahan. Proses perhitungan rekomendasi dilakukan menggunakan Item-Based Collaborative Filtering yang menghasilkan skor prediksi untuk setiap alternatif bibit. Hasil penelitian menunjukkan bahwa metode Collaborative Filtering mampu memberikan rekomendasi bibit secara lebih objektif. Bibit dengan nilai rekomendasi tertinggi diperoleh oleh Bibit 1 (C1) dengan skor 4,349, sedangkan nilai terendah diperoleh oleh Bibit 4 (C4) dengan skor 1,533. Sistem rekomendasi yang dibangun dapat membantu petani memilih bibit temulawak terbaik secara terukur dan efektif, serta berpotensi meningkatkan hasil panen dan pendapatan.
Pengenalan E-Commerce: Peluang dan Tantangan bagi UMKM Desa Sikeben Kecamatan Sibolangit Kabupaten Deli Serdang Cahaya Aqila; Dewi Santri; Muhammad Abdillah; Luthfiah Mianda; M. Fakhriza
Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Vol. 6 No. 1 (2026): Maret: Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan (JIMEK)
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jimek.v6i1.9818

Abstract

MSMEs in Sikeben Village have the potential to sell their products widely because the quality of their products is competitive with those of other MSMEs. Currently, MSMEs in Sikeben Village face limitations in accessing wider markets due to their conventional marketing systems. This condition has resulted in the potential of local products, which actually have high selling value, being less known to consumers outside the Sikeben village area. This is evidenced by the fact that, to date, no MSMEs in Sikeben Village have utilized e-commerce to sell their products. Through this activity, the people of Sikeben Village were introduced to the use of e-commerce as a medium for online promotion and sales, while also identifying obstacles that arise in the introduction of e-commerce websites. This community service program was carried out through direct training in Sikeben Village. This community service program was carried out through direct training in Kampai Village using the Participatory Action Research (PAR) method. As a result of this activity, MSMEs began to learn how to use Facebook to market their products. Participants were taught how to create business pages, upload products, and promote them in order to reach buyers outside Sikeben Village.
Strategi Pemasaran Digital untuk UMKM Desa: Meningkatkan Keberlanjutan Usaha Mikro melalui Platform Media Sosial di Desa Sikeben Asrifah Nabila; Muhammad Haikal Amril Tanjung; Wahyu Pinastia Ningrum; Zahra Safira; M. Fakhriza
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 6 No. 2 (2026): Mei : NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v6i2.8392

Abstract

This research aims to identify and design relevant digital marketing strategies for Micro, Small, and Medium Enterprises (MSMEs) in Sikeben Village, with the goal of enhancing business sustainability through the utilization of the village’s social media platforms. The study employs a descriptive qualitative approach using interviews, observations, and documentation analysis involving MSME entrepreneurs, village officials, and social media managers of the village. The findings indicate that leveraging the village’s social media can expand market reach, improve customer interaction, and construct a positive image of local products. However, challenges remain, such as limited digital literacy, internet infrastructure issues, and a lack of systematic content strategies. As a result, the study proposes a community-based digital marketing model, which includes market segmentation, strengthening local content, stakeholder collaboration, and data-driven evaluation.