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All Journal Jurnal Informatika dan Teknik Elektro Terapan SISFOTENIKA Jurnal Teknologi dan Informasi Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika Jurnal ICT : Information Communication & Technology Infotekmesin INTI Nusa Mandiri Santika : Jurnal Ilmiah Sains dan Teknologi Infotek : Jurnal Informatika dan Teknologi Journal Of Regional Public Administration (JRPA) Simpatik: Jurnal sistem Informasi dan Informatika Jurnal Interkom : Jurnal Publikasi Ilmiah Bidang Teknologi Informasi dan Komunikasi TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Journal of Information System Exploration and Research Infomans: Jurnal Ilmu-ilmu Informatika dan Manajemen Jurnal Informatika: Jurnal Pengembangan IT Jurnal Intelek Dan Cendikiawan Nusantara Jurnal Intelek Insan Cendikia Riau Jurnal Teknik Informatika Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan JIMT: Jurnal Informatika, Multimedia dan Teknik
Mahardika, Fathoni
Fakultas Teknologi Informasi Universitas Sebelas April
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Analisis Kebutuhan Pengguna untuk Perancangan Antarmuka Aplikasi Layanan Pengantaran Menggunakan User-Centered Design Shofwatunnisa, Nida; Fathoni Mahardika; Dani Indra Junaedi; Agun Guntara
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp350-355

Abstract

Delivery services are one type of service that is widely used by the public to facilitate the process of delivering goods and orders. However, the current delivery system is still not running optimally because the use of digital technology has not been maximized. This study aims to analyze user needs in the design of a delivery service application using the User-Centered Design (UCD) method. The UCD approach was chosen because it focuses on users by placing their needs and experiences as the main aspects in the system design process. This study was conducted up to the second stage, which was to understand the context of use and identify user needs. Data collection was carried out by distributing questionnaires to ten respondents consisting of customers, business owners, and couriers. The results of the study show that users need key features such as service ordering, real-time delivery tracking, automatic notifications, and direct communication between customers and couriers. In addition, users also want an application that is easy to use, secure, and has stable performance. The results of this analysis form the basis for the application design in the next stage to produce a system that meets user needs.
Analisis Perbandingan Algoritma Random Forest, SVM, dan Neural Network untuk Klasifikasi Risiko Keamanan E-Learning Nugraha, Rahmat Taufik; Hidayat, Deden; Mahardika, Fathoni
Jurnal Teknologi dan Informasi (JATI) Vol 16 No 1 (2026): Jurnal Teknologi dan Informasi (JATI)
Publisher : Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jati.v16i1.17191

Abstract

Akselerasi adopsi platform e-learning akibat pandemi COVID-19 telah memperluas permukaan serangan siber di sektor pendidikan, menuntut solusi deteksi ancaman yang lebih canggih. Machine learning (ML) menawarkan pendekatan proaktif untuk mengatasi tantangan ini, namun belum terdapat konsensus mengenai algoritma yang paling optimal. Studi ini bertujuan melakukan analisis komparatif empiris terhadap tiga algoritma ML terkemuka Random Forest (RF), Support Vector Machine (SVM), dan Neural Network (NN) dalam mengklasifikasikan risiko keamanan pada lingkungan e-learning. Menggunakan dataset sintetik Classroom Data Security Threats, penelitian ini menerapkan metodologi kuantitatif yang mencakup pra-pemrosesan data dan evaluasi model menggunakan metrik accuracy, F1-score, dan ROC-AUC. Hasil eksperimen menunjukkan kinerja yang sangat terbatas dari ketiga model. NN mencapai akurasi tertinggi, namun hanya sebesar 33.5%, sedikit di atas SVM (32.5%) dan RF (29.5%). Secara signifikan, skor ROC-AUC untuk semua model berada di sekitar 0.5, yang mengindikasikan kemampuan prediktifnya tidak lebih baik dari tebakan acak. Kegagalan serempak ini menyiratkan bahwa tantangan utama bukan terletak pada pemilihan algoritma, melainkan pada kualitas prediktif dataset dan ketiadaan optimisasi hyperparameter. Temuan ini menggarisbawahi pentingnya kualitas data dan rigor metodologis sebagai prasyarat fundamental untuk pengembangan sistem keamanan siber berbasis ML yang efektif.
Explainable Artificial Intelligence-Based Model for Student Academic Performance Prediction Hidayatulloh, Wildan; Mahardika, Fathoni; Junaedi, Dani Indra
Journal of Information System Exploration and Research Vol. 4 No. 1 (2026): January 2026
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v4i1.624

Abstract

This study focuses on predicting student academic performance while emphasizing model interpretability through Explainable Artificial Intelligence (XAI). The main objective is to identify potential academic risks using machine learning models and provide transparent explanations for their decisions. Historical student academic data were used to train and evaluate two classification models: Random Forest and XGBoost. The results show that both models exhibit strong predictive performance. Random Forest achieved an accuracy of 90.77% and a precision of 0.7500 for the risk class, while XGBoost attained a higher recall of 0.7000 with an accuracy of 89.23% and a precision of 0.6364. Both models achieved an identical F1-score of 0.6667 for the risk class. The application of XAI methods, namely SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations), revealed the main features influencing the predictions. Globally, G2 (previous period’s final grade), failures (number of failed courses), and absences were identified as the most critical factors. Local interpretations from SHAP and LIME also clarified individual predictions, both correct and misclassified. The study contributes to developing an accurate and transparent decision-support system to enable more personalized, effective, and data-driven academic interventions.
Systematic Literature Review Sistem Pemilah Sampah Otomatis Berbasis Sensor Proximity dengan Notifikasi Kapasitas Penuh Anjelina Mentari Rustandi; Fathoni Mahardika; Dani Indra Junaedi
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 4 No. 2 (2026): April : Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v4i2.847

Abstract

Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.
Co-Authors Abdah Syakiroh Gustian Agun Guntara Ajar Basyar Tsani Anjelina Mentari Rustandi Aprilyawan, Muhamad Rian Asep Saeppani Assidiq, Muhamad Luthfi Chozin Choirurroziqien CYNTHIA PETRA HAUMAHU Dani Indra Junaedi Dian Budiana Dian Hermawan Dimitri Octaviana Fatimah, Siti Ainun Fidi Supriadi Fina Nur'aeni Guntara, Agun Hendrawan, Fauzi Bayu Hidayat, Deden Hidayatulloh, Wildan Huslan, Anisa Pebriyani Indriyani Surachman, Revaliana Irfan Fadil Lusi Sugiarti Lestari Lusi Tsulutsiah Nur F Martanto . Maulana, Rifki Muhamad Deni Ramdani Muhammad Agreindra Helmiawan Muhammad Irsan Muhammad Yusuf Zulfikar Nova Nurhidayat Nugraha, Rahmat Taufik Nur F, Lusi Tsulutsiah Nur'aeni, Fina Octaviana, Dimitri Purnama, Yulian Puspanagara, Amanda Listiana Rangga Sanjaya, Rangga Rearizth Muhammad Daffaa Rizki, Rifky Septiana Santika, Deris Shofwatunnisa, Nida Siti Ainun Fatimah Ummiyati Ummiyati Vini Octaviani, Eneng Yopi Hidayatul Akbar