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All Journal EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis Warta Pendidikan : Jurnal Pendidikan dan Budaya Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics International Journal of Multidisciplinary Science and Applied Research (IJOMAS)
Maulana Abdul Rahman
Universitas Gajayana Malang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Social Sciences Other

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Studi Penerapan Digital Marketing Pada UKM Makanan Khas di Kota Malang Maulana Abdul Rahman; Ernani Hadiyati; Martaleni; Ahmad
Warta Pendidikan | e-Journal Vol. 4 No. 4 (2020): Warta Pendidikan
Publisher : Pusat Pengkajian dan Pengembangan Sumber Daya Manusia (P3SDM) Melati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0503/wp.v4i9.34

Abstract

Pelaku ekonomi UKM (Usaha Kecil Menengah) di Indonesia harus mengikuti perkembangan Era Revolusi Industri 4.0, termasuk pula UKM Makanan di Kota Malang. Tidak ada jalan pilihan lain bagi UKM Makanan di Kota Malang untuk aktif dalam ekonomi digital. Hanya dengan itu UKM Makanan di Kota Malang akan bisa bertahan dan melakukan akselerisasi ekonomi yang luas. Karenanya yang dibutuhkan UKM Makanan di Kota Malang, adalah bagaimana mereka memiliki pengetahuan terkait dengan ekonomi digital. Untuk itu penguasaan terhadap internet, kemampuan penggunaan media sosial, hingga kemampuan membangun jaringan harus diberikan. Menggunakan metode penelitian kualitatif, pada dimensi Social Media Markerting sebagaimana dijelaskan Kim & Ko, UKM Makanan di Kota Malang menggunakan media sosial pada variabel entertainment, interaction, trendiness, dan customization dengan baik. Pemanfaatan media sosial sebagai bagian dari media promosi dan pemasaran, menjadi pendukung peningkatan penjualan produk UKM di Kota Malang. Pada kenyataannya, UKM Makanan di Kota Malang yang telah memiliki nama besar dan terkenal, tidak serta- merta mengutamakan media sosial sebagai alat promosi. Hal itu disebabkan oleh keberadaan mereka telah dikenal dnegan baik oleh pelanggan maupun calon pelanggan baru. Penggunaan media sosial, diutamakan pada variabel trendiness,dan interaction saja. Sementara variabel konvensional word of mouth, masih menjadi andalan.
Panel Data Analysis With Mediating Variables In The Production Performance Model In Malang City Industry Meilina Retno Hapsari; Mitha Endah Aprilia; Maulana Abdul Rahman
EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis Vol 12 No 4 (2024): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/ekombis.v12i4.5845

Abstract

The development of the industrial sector is able to provide a strategic role in the economy. One of the efforts made to improve industrial performance is to find out the factors that influence production performance in industry. This research has a purpose to determine the effect of number of workers and production quantity on production performance as seen from production value in Malang City Industry, where production quantity is a mediating variable. This research is quantitative research. This data source is secondary data from Malang City Industrial data. The samples in this research were small and medium industries in Malang City for several years. Based on the panel data analysis result with mediating variables, show the number of workers has a significant effect on the amount of production. The number of workers does not have a significant effect on production performance. The amount of production has a significant effect on production performance. The number of workers has a significant effect on production performance through the amount of production. Therefore, it is hoped that industrial leaders need to increase the number of workers so that production increases, and the increased production will increase the performance of industrial production in Malang City.
Design of a Web-Based Salary Management Information System Using the Zachman Framework: A Case Study of Batu City Government Sabirina Ayu, Estrielita; Abdul Rahman, Maulana
International Journal of Multidisciplinary Applied and Science Research Vol. 1 No. 04 (2025): International Journal of Multidisciplinary Science and Applied Research (IJOMA
Publisher : oneamd.com

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

Abstract

Efficient salary management is crucial for ensuring transparency and accountability in government institutions. The Batu City Government currently faces challenges with its desktop-based salary management system, which is prone to delays, errors, and limited transparency. This study aims to design a web-based salary management information system using the Zachman Framework to address these issues. A qualitative research method with a case study approach was applied, focusing on the Batu City Government. The Zachman Framework was utilized to ensure that all perspectives of the system—from planning and user needs to technical design—were considered in the development process. The findings reveal that the proposed web-based system significantly improves efficiency by automating salary calculations, enhances transparency by providing real-time access to salary information, and simplifies monthly report generation. Furthermore, the system incorporates robust security features to protect sensitive employee data. The study concludes that the web-based salary management system, designed using the Zachman Framework, offers an effective solution for the Batu City Government, providing a more efficient, accurate, and transparent approach to salary management. The implementation of this system can serve as a model for other government institutions seeking to modernize their administrative processes.
Metaheuristic-Based Hyperparameter Optimization Analysis of Deep Neural Network for Cross-Project Defect Prediction in Mobile Applications Abdul Rahman, Maulana; Herteno, Rudy; Adi Nugroho, Radityo; Abadi, Friska; Wahyu Saputro, Setyo
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 8 No. 2 (2026): May
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v8i2.340

Abstract

Software Defect Prediction (SDP) plays a strategic role in identifying software defects during the early stages of development, thereby enabling more efficient allocation of testing resources, particularly in the rapidly evolving mobile application domain characterized by fast release cycles. The commonly used Within-Project Defect Prediction (WPDP) approach is often constrained by the limited availability of historical data, especially in projects at early stages of development. As an alternative, Cross-Project Defect Prediction (CPDP) leverages historical data from other projects as training sources. Moreover, the performance of the Deep Neural Network (DNN) used in SDP is highly dependent on accurate hyperparameter configurations, where manual tuning requires substantial time and computational resources without guaranteeing optimal results. To address this issue, this study analyzes and compares the effectiveness of three metaheuristic algorithms, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Grey Wolf Optimizer (GWO), in optimizing DNN hyperparameters within a CPDP framework. This study utilizes 14 open-source Android mobile application projects and employs the Leave-One-Out Cross-Validation technique. The performance of each combination is evaluated using ROC-AUC as the primary metric. The Wilcoxon Signed-Rank Test with a Bonferroni correction is used to assess the statistical significance of the observed performance differences. The experimental results demonstrate that GWO-DNN achieves the best performance, with an average ROC-AUC of 0.721, and is the only combination that remains statistically significant after Bonferroni correction, with a small effect size based on Cliff’s delta. Overall, the findings of this study indicate that metaheuristic-based hyperparameter tuning is a sufficiently effective approach for improving the capability of DNN in cross-project software defect prediction within the mobile application domain, although the observed improvements remain moderate.
Co-Authors Ahmad Ernani Hadiyati Friska Abadi Herteno, Rudy Martaleni - Meilina Retno Hapsari Mitha Endah Aprilia Radityo Adi Nugroho Sabirina Ayu, Estrielita Setyo Wahyu Saputro