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All Journal Jurnal SOLMA Jurnal Sistem Informasi dan Informatika (SIMIKA) Generation Journal Indonesian Community Journal Jurnal Algoritma Journal of Research Applications in Community Services AL-UMRON: Jurnal Pengabdian kepada Masyarakat Jurnal Informatika Polinema (JIP) COMPUTECH : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Almantiq Jurnal Teras Pengabdian Masyarakat
Zakki Alawi
Universitas Nahdlatul Ulama Sunan Giri
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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Aplikasi Administrasi Keuangan Pondok Pesantren Berbasis Web Menggunakan Metode Scrum: Web-Based Islamic Boarding School Financial Administration Application Using the Scrum Method Muhammad Yusuf Affandi; Farhan, Ahmad; Moh. Shohibul Wafa; Zakki Alawi
Computech : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Vol. 3 No. 1 (2023): January 2023
Publisher : AMIK

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Darul Ulum Islamic Boarding School in providing its services, especially in the field of financial administration, still adopts a conventional approach. In this method, hostel administrators manually record the flow of money both incoming and outgoing in traditional financial books. The preparation of financial reports is also only done once every three to six months. However, there is a risk that financial data may be erased when the registrar changes jobs. Various problems arise as a result of this approach, such as errors in recording the amount of money, limited access resulting in a lack of transparency and up-to-date financial information, the possibility of data being lost or damaged due to negligence or human error, lack of supervision which makes violations difficult to track and takes a long time to detect, unavailability structured financial records making it difficult to refer to previous years' budgets, and making financial reports that take up too much time. To overcome these problems, the authors have designed and built a web-based financial administration information system for this Islamic boarding school. The approach used is the Scrum method with an Agile framework, and utilizes the Laravel framework. The programming language used is native PHP, and the database system used is MySQL.
Peningkatan Kapasitas UMKM dan Kewirausahaan Melalui Inovasi Produk Lokal: Pelatihan Pembuatan Coklat Tempe dan Penguatan Koperasi di Desa Kalisumber Zakki Alawi; Sri Minarti
Jurnal Teras Pengabdian Masyarakat Vol. 2 No. 1: Januari (2026)
Publisher : PT. Teras Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64479/jtpm.v2i1.53

Abstract

UMKM merupakan fondasi kuat perekonomian Indonesia, namun seringkali menghadapi tantangan dalam pengelolaan manajerial dan inovasi produk. Tempe, sebagai produk tradisional yang kaya protein, memiliki keterbatasan daya simpan dan olahan yang masih sering bersifat tradisional, sehingga kurang diminati di beberapa daerah. Untuk mengatasi tantangan ini dan meningkatkan daya saing, kegiatan pengabdian masyarakat di Desa Kalisumber bertujuan meningkatkan kapasitas UMKM dan kewirausahaan melalui inovasi produk lokal, yaitu pelatihan pembuatan coklat tempe, serta penguatan kelembagaan Koperasi Merah Putih. Metode partisipatif diterapkan dengan melibatkan masyarakat secara aktif dalam setiap tahapan, meliputi persiapan, sosialisasi, pelatihan praktis pembuatan dan pengemasan coklat tempe, pendampingan, serta monitoring dan evaluasi. Hasilnya menunjukkan peningkatan pemahaman dan keterampilan masyarakat, khususnya pelaku UMKM dan ibu-ibu rumah tangga, dalam mengelola usaha berbasis potensi lokal. Sosialisasi koperasi berhasil meningkatkan pemahaman 30 pengurus dan anggota tentang manajemen profesional. Pelatihan juga sukses menciptakan produk coklat tempe yang unik dan berkualitas, membuka peluang pasar baru, dan meningkatkan pendapatan. Dengan demikian, program ini berkontribusi nyata terhadap peningkatan daya saing UMKM dan pengembangan ekonomi Desa Kalisumber berbasis inovasi produk.
PENGARUH KOMPOSISI SPLIT DATA PADA AKURASI KLASIFIKASI PENDERITA DIABETES MENGGUNAKAN ALGORITMA MACHINE LEARNING Febby Refindha Aftha Harianto; Zakki Alawi; Ita Aristia Sa’ida
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 1 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i1.3663

Abstract

The increasing number of people with diabetes is an international health problem. To prevent diabetic complications, early diagnosis and accurate classification are essential. This study looks at how the composition of split data affects the classification performance of diabetics with machine learning algorithms such as Random Forest, Naive Bayes, and Support Vector Machine (SVM). The research data is taken from Bojonegoro Regency Hospital, which consists of 128 samples that have 10 main features. To ensure the data is ready for use, the research method goes through a preprocessing stage. Next, the data was divided into training and testing data with a ratio of 90:10, 80:20, 70:30, 60:40, and 50:50 respectively. Using confusion matrix, the algorithm is assessed for accuracy, precision, recall, and F1 score. In this study we focus on the accuracy values obtained and the results show that the proportion of data sharing affects the performance of the algorithm. Random Forest achieved 100% accuracy in some scenarios. This algorithm also proved to be the most effective in the classification of diabetics. In conclusion, algorithm selection and data split composition are very important for model performance optimization. These results are important for the development of more accurate and efficient Machine Learning-based diagnosis systems. Further research can consider larger datasets and additional algorithms for better results.
KOMPARASI ALGORITMA DECISION TREE DAN SUPPORT VECTOR MACHINE (SVM) DALAM KLASIFIKASI SERANGAN JANTUNG Elok Fathiyatul Laili; Zakki Alawi; Roihatur Rohmah; Mula Agung Barata
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 1 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i1.3683

Abstract

The heart is one of the most important organs in the human body. According to the WHO, heart attacks are the most common cause of sudden death worldwide, with more than 17.8 million people dying from heart attacks. A heart attack occurs when blood flow to the coronary arteries stops, depriving the heart muscle of oxygen, and causing a heart attack. Detecting a heart attack is very difficult due to the various symptoms. The purpose of this research is to compare the performance of the accuracy values of two algorithms, namely Decision Tree and Support Vector Machine (SVM) in classifying heart attacks. The results of this study show that the Decision Tree algorithm achieves the highest accuracy results compared to the SVM algorithm. The accuracy of the Decision Tree algorithm using a 60:40 ratio data splitting is 98.11% with a negative precision of 98.01% and positive of 98.17% and a negative recall of 97.04% and positive of 98.77%. Meanwhile, the SVM algorithm using data splitting with the same ratio produces an accuracy value of 92.80% with a negative precision of 90.24% and a positive of 94.43% and a negative recall of 91.13% and a positive of 93.85%.
Co-Authors Ahmad Farhan, Ahmad APRILLIA, YUSIFA Aralia, Shafa Kirana Audytra, Hastie Ayuni, Intan Sri Barata, Mula Bassalam, Ahmad Nasih Ulwan Ceisa, Nirma Dirgantoro, Guruh Putro Elok Fathiyatul Laili Febby Refindha Aftha Harianto Hidayah, Nurul Hidayah Ifa Khoiria Ningrum Irfani, Ulfi Ita Aristia Sa'ida Jauhar Vikri, Muhammad Kartini, Alif Yuanita Lestari, Iin Widya Moh. Shohibul Wafa Muhammad Hilmi Khafabihi Muhammad Yusuf Affandi Mula Agung Barata Nilna Indriana Nugraha, Krisna Wahyu Nur Mahmudah Rheyna Anggri Setyani Roihatur Rohmah Roihatur Rohmah Sanjaya, Ucta Pradema Sri Minarti Vita Dwi Rahmawati Zayn, Afta Ramadhan