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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Advanced in Information and Industrial Technology (JAIIT) IICS Jurnal Pengabdian Masyarakat dan aplikasi Teknologi
Mustafa Kamal
Universitas Telkom
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Other

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Risk Management for New Student Admission Information Systems at Higher Education using the Octave Allegro Approach Titus Kristanto; Riza Akhsani Setyo Prayoga; Muhammad Nasrullah; Mustafa Kamal; Wahyuddin S
IAIC International Conference Series Vol. 4 No. 1 (2023): SEMNASTIK 2023
Publisher : IAIC Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/conferenceseries.v4i1.637

Abstract

In the current digital era, especially in the world of education, the use of information and communication technology (ICT) is growing rapidly to meet needs. Universities rely on information systems, especially in managing new student admissions. The new student admission selection information system contains sensitive and dangerous prospective student data, as well as the risks that arise in the information system, limited to data processing during the new student admission process and the administration process, thus causing problems. The New Student Registration Information System is one of the services provided by the university as part of the new student registration process. Therefore, risk management is needed to minimize the impact of risks on maintaining data integrity, confidentiality, and availability. The aim of the research is to identify, analyze, and evaluate risks when using information systems for new student admission procedures. The approach used in risk management is Octave Allegro, and Octave Allegro is used to help evaluate information assets. The method used is data collection by conducting interviews with related sources. Based on the findings on the New Student Admissions site, there are 5 risk areas; 9 IT risks were identified as a result of potential risk analysis; and 4 IT risks were mitigated based on recommendations.
Application of Naïve Bayes Method for Assessing Student Performance Riza Akhsani Setyo Prayoga; Fauzan Nusyura; Fiddin Yusfida A’la; Mustafa Kamal; Farhanna Mar'i
Journal of Advances in Information and Industrial Technology Vol. 8 No. 1 (2026): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v8i1.771

Abstract

Every school has pupils with varying levels of achievement. These differences in achievement can be influenced by several factors, such as the parents’ level of education and the pupils’ readiness for examinations. Furthermore, they can also be influenced by pupils’ abilities in mathematics, writing, and reading. The aim of this study is to classify student performance so that the performance of students at an adequate level or below average can be improved. The method used in this study is Naïve Bayes as a classification method. There are 150 training data points and 50 test data points. Five metrics were evaluated: precision at 94.4%, recall at 94.4%, specificity at 50%, accuracy at 90%, and the F1 score at 94%. This indicates that the model performs well in providing accurate positive predictions. Furthermore, the model is capable of detecting the majority of positive cases effectively.
Robust Aggregation Strategies in Federated Learning for Credit Risk Assessment Sulthonika Mahfudz Al Mujahidin; Michael Angello Qadosy Riyadi; Adinda Mariasti Dewi; Mustafa Kamal
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 6 (2025): December 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i6.7133

Abstract

Financial institutions face challenges in credit risk assessment due to fragmented data and strict privacy regulations, which hinder predictive modeling and increase financial risks. Federated Learning (FL) enables privacy-preserving collaborative modeling without sharing raw data. This study evaluates five FL aggregation methods—Federated Averaging (FedAvg), Weighted Average, Median Aggregation, Federated Proximal (FedProx), and Stochastic Controlled Averaging (SCAFFOLD)—using logistic regression on the Credit Approval dataset (690 records, five clients) with non-IID label and feature distributions. Local models were trained and aggregated over 50 rounds. Median Aggregation outperformed the other methods, achieving an F1-score of 97.85% and a recall of 80.6% (vs. 72.3% for others), demonstrating robustness against data skewness. However, global model performance (85.22% for FedAvg, Weighted Average, FedProx, SCAFFOLD; 85.80% for Median) remained static across rounds, indicating limited convergence due to rapid local model convergence and non-IID challenges. The high communication cost of 50 rounds highlights a trade-off between accuracy and efficiency, necessitating optimized strategies like adaptive regularization or client sampling. This study advances theoretical understanding of FL under heterogeneity and provides practical guidance for secure, regulation-compliant credit risk modeling in financial institutions. Future work should explore larger datasets, multi-round convergence, and privacy mechanisms like differential privacy to mitigate risks such as model inversion attacks while ensuring compliance
Penerapan Teknologi Ekstruder Filamen untuk Daur Ulang Botol Plastik sebagai Alternatif Anyaman Kreatif Abduh Sayid Albana; Mochammad Zulfikar Alfany; Benazir Imam Arif Muttaqin; Adi Candra; Mustafa Kamal; Agoes Windarto; Ega Mawarni Ayuningtyas; Annisa Sofia Albana
Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Vol 05 No 02: Oktober 2026 (in progress)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.adipati.2026.v5i2.8587

Abstract

Permasalahan sampah botol plastik di kawasan perkotaan seperti Kota Surabaya terus meningkat seiring dengan pertumbuhan konsumsi masyarakat, sementara kapasitas daur ulang masih terbatas dan sebagian besar limbah plastik berakhir di tempat pembuangan akhir. Di sisi lain, ketersediaan bahan baku rotan sebagai material utama kerajinan anyaman semakin terbatas dan mahal, sehingga menghambat keberlanjutan usaha kerajinan masyarakat. Program pengabdian ini bertujuan menerapkan teknologi ekstruder filamen untuk mengolah botol plastik bekas menjadi filamen plastik sebagai bahan alternatif pengganti rotan sekaligus memberdayakan masyarakat Desa Gading Watu, Kabupaten Gresik. Metode pelaksanaan meliputi edukasi ekonomi sirkular, pembuatan alat ekstruder, pelatihan pengolahan botol plastik menjadi filamen, pelatihan anyaman, pendampingan produksi, serta persiapan pemasaran produk. Hasil kegiatan menunjukkan bahwa teknologi ekstruder filamen dapat dioperasikan secara mandiri oleh masyarakat dan mampu menghasilkan filamen plastik yang layak digunakan sebagai bahan anyaman. Masyarakat berhasil memproduksi berbagai produk kerajinan seperti keranjang, pot tanaman, dan kotak serbaguna dengan bahan filamen plastik. Program ini berkontribusi dalam mengurangi limbah plastik, meningkatkan keterampilan dan pendapatan masyarakat, serta mendorong penerapan ekonomi sirkular berbasis komunitas.
Co-Authors Abduh Sayid Albana Adi Candra Adinda Mariasti Dewi Agoes Windarto Annisa Sofia Albana Benazir Imam Arif Muttaqin Ega Mawarni Ayuningtyas Farhanna Mar'i Fauzan Nusyura Fiddin Yusfida A’la Michael Angello Qadosy Riyadi Mochammad Zulfikar Alfany Muhammad Nasrullah Riza Akhsani Setyo Prayoga Sulthonika Mahfudz Al Mujahidin Titus Kristanto Wahyuddin S