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All Journal Dinamik Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Mahasiswa Sistem Informasi dan Komputer Akuntansi (JIMASIKA) CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA)
Ikbal Yasin
Universitas Teknokrat Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Implementation of Moving Average for Forecasting Inventory Data Using CodeIgniter Fikri Hamidy; Ikbal Yasin
Journal of Data Science and Information Systems Vol. 1 No. 1 (2023): Volume 1 Number 1 February 2023
Publisher : Journal of Data Science and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/dimis.v1i1.17

Abstract

The purpose of this study is to be able to apply a manual inventory forecasting system with the moving average method in order to speed up the decision-making process and be able to minimize the error rate in calculating stock in the warehouse. The results of inventory forecasting in 2023 have an average of 192 for 116 BR animal feed items. Based on the results of calculating the average amount, a satisfaction level of 3,825 was obtained and if you follow the reference of Kaplan and Norton satisfaction level, the conclusion that can be drawn is that the level of user satisfaction with the inventory application is included in the satisfied category. So that the indications shown are positive from the PIECES model, namely users are satisfied with this inventory application.
Digitalisasi Sistem Perpustakaan Menggunakan Restful Web Service Ketut Risma Febi Kusuma; A Ferico Octaviansyah P; Yuri Rahmanto; Angga Bayu Santoso Angga; Fadhila Shelly Amalia; Ikbal Yasin
Jurnal Ilmiah Sistem Informasi Akuntansi Vol. 5 No. 1 (2025): Volume 5, Nomor 1, June 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jimasia.v5i1.551

Abstract

Perkembangan teknologi informasi telah mendorong berbagai institusi, termasuk instansi pemerintahan, untuk bertransformasi menuju sistem digital yang efisien, terstruktur dan terintegrasi. Salah satu aspek yang terdampak adalah sistem pengelolaan perpustakaan, yang menuntut kemudahan akses, kecepatan layanan dan interoperabilitas lintas platform. Penelitian ini bertujuan untuk mengembangkan sistem perpustakaan digital dengan mengimplementasikan RESTful Web Service sebagai solusi penghubung antara sisi klien dan server. Studi kasus dilakukan pada perpustakaan internal DPRD Provinsi Lampung yang masih menggunakan sistem semi-manual dengan keterbatasan pada integrasi dan akses data. Sistem yang dibangun menyediakan fitur input data buku, transaksi peminjaman, serta menggunakan format data JSON dan metode HTTP (GET, POST, PUT, DELETE) untuk pertukaran informasi. RESTful API memberikan keunggulan dalam hal modularitas kode serta kemudahan integrasi dengan aplikasi eksternal. Hasil implementasi menunjukkan sistem lebih efisien, dapat diakses secara luas melalui berbagai perangkat, dan memiliki tingkat reusabilitas yang tinggi. Penelitian ini menyimpulkan bahwa RESTful Web Service merupakan pendekatan yang tepat dalam membangun sistem perpustakaan digital yang modern, scalable dan aman.
Rancang Bangun Sistem Informasi Penggajian Karyawan Berbasis Web Menggunakan Framework CodeIgniter pada Bostown Coffee Fira Rizki Amalia; Ikbal Yasin
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 3 No. 2 (2025): Volume 3 Number 2 June 2025
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v3i2.200

Abstract

Pengembangan sistem perhitungan gaji karyawan adalah langkah penting dalam meningkatkan efisiensi dan akurasi pengelolaan sumber daya manusia dalam perusahaan. Penelitian ini membahas tahapan implementasi sistem perhitungan gaji karyawan dengan fokus pada pemilihan alat dan teknologi yang sesuai. Visual Studio Code digunakan sebagai lingkungan pengembangan, XAMPP berperan sebagai server lokal, dan CodeIgniter sebagai kerangka kerja pengembangan web. Menu login yang diimplementasikan pada sistem memberikan lapisan keamanan tambahan, memastikan akses yang tepat ke data yang sensitif. Penggunaan server lokal dengan XAMPP memungkinkan pengujian yang lebih baik sebelum aplikasi diterapkan di lingkungan produksi. Hasilnya adalah sistem yang efisien, akurat, dan aman dalam mengelola data gaji karyawan, dengan potensi untuk meningkatkan produktivitas dan efisiensi dalam perusahaan. Dengan menggunakan alat dan teknologi yang tepat, implementasi sistem ini memberikan landasan yang kuat untuk pengelolaan sumber daya manusia yang efektif dan terkendali.
Implementasi Sistem Informasi Data Kas Kecil Menggunakan Metode Web Engineering Ikbal Yasin; Fikri Hamidy
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 1 No. 1 (2023): Volume 1 Number 1 January 2023
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v1i1.3

Abstract

Permasalahan yang terjadi pada PT. XYZ yaitu sulitnya mengolah data accounting, admin, dan jenis pengeluaran dikarenakan jumlah transaksi yang semakin padat, belum adanya aplikasi untuk mengolah data pengisian dan pengeluaran kas kecil, sehingga perhitungannya tidak akurat, serta sulitnya menyajikan laporan pencairan dan laporan pengeluaran kas kecil dengan waktu yang singkat. Aplikasi sistem informasi data kas kecil pada PT. XYZ dapat mempermudah pencatatan data permintaan, pengisian, pengeluaran secara mudah dan cepat. Dalam hal sistem informasi data kas kecil pada PT. XYZ dapat memperoleh laporan secara realtime. Hasil pengujian mendapatkan hasil yaitu 100% sesuai dengan pengujian fungsionalitas sistem menggunakan blackbox testing. Hasil pengujian menggunakan ISO 25010 aspek Performance Efficiency, Aspek Operability, dan Aspek Functional Efficiency maka didapatkan skor total yaitu 85,47%. Berdasarkan hal tersebut maka ISO 25010 prototype Sangat Baik untuk aplikasi pengelolaan kas kecil.
Penerapan Metode Moving Average Dalam Penentuan Harga Pokok Penjualan Barang Berbasis Web Fikri Hamidy; Ikbal Yasin
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 2 No. 2 (2024): Volume 2 Number 2 April 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v2i2.115

Abstract

Cost of Goods Sold (COGS) is the cost incurred by the company to produce or acquire goods which are then sold to customers. The main components in COGS include raw material costs, direct labor costs, and factory overhead costs required to produce goods. One of the problems in determining the cost of goods sold is the difficulty in estimating production costs accurately, which can result in selling prices that are not in accordance with the expected profit margin. In addition, another problem in determining the cost of goods sold is the lack of accurate data or information about costs related to product production and distribution, thus making the pricing process less efficient and less precise. The application of the moving average method in determining the cost of goods sold (COGS) of web-based goods offers an efficient and integrated solution for companies in managing their production costs. Using a web-based application, users can easily access and utilize moving average analysis features to even out fluctuations in raw material or production prices in real-time. The test results using blackbox testing by 100% show that all test scenarios that have been designed have been successfully passed by the application without any failures or malfunctions. A 100% test result gives the development team additional confidence that the app is ready to launch and is widely used by users.
Prediksi Risiko Kehamilan dengan Machine Learning: Penanganan Imbalanced Class dan Evaluasi Multi-Model pada Data Maternal Health Rindah Okta Renza; Ikbal Yasin; Erliyan Redi Susanto
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10484

Abstract

Maternal mortality rates are a significant global health challenge, especially in developing countries that lack adequate medical resources. Early detection of pregnancy risks is crucial to prevent serious complications. This study developed a predictive model for pregnancy risks using four machine learning techniques: Support Vector Machine (SVM), Random Forest, XGBoost, and Gaussian Naive Bayes. The data set, taken from sources such as Kaggle and the UCI Repository, includes seven physiological indicators. Data preprocessing includes data cleaning, feature normalization, and label encoding. To address class imbalance in the Low Risk, Mid Risk, and High Risk categories, the Synthetic Minority Oversampling (SMOTE) technique is used. Model evaluation used metrics such as accuracy, precision, recall, F1 score, ROC-AUC, and processing time. The results showed XGBoost as the best model, with an accuracy of 0.8566, precision of 0.8567, recall of 0.8566, F1 score of 0.8554, and ROC-AUC of 0.9633. Random Forest produced comparable results, while Gaussian Naive Bayes was the fastest but least effective. The use of SMOTE with various metrics improved the model's ability to identify high- risk cases. Ultimately, XGBoost and Random Forest are recommended for integration into medical decision support systems aimed at early detection of pregnancy risks.
Co-Authors Aidil Akbar Alvinan Virgilia Angga Bayu Santoso Angga Auliya R. Isnain Cici Dian Paramita Dedi Darwis Dinda Ayu Prasticha Elvano Delisa Mega Erliyan Redi Susanto Fadhila Shelly Amalia Fikri Hamidy Finki Gusmiadi Fira Aulia Fira Rizki Amalia Heni Sulistiani Isnain, Auliya Rahman Ketut Risma Febi Kusuma Nopiah Alpiana Parjito Parjito Pasaribu, A. Ferico Octaviansyah Rika Mersita Rindah Okta Renza Yasinta Ismi Yunita Yunita Yuri Rahmanto