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All Journal Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika Infotek : Jurnal Informatika dan Teknologi Simpatik: Jurnal sistem Informasi dan Informatika Infomans: Jurnal Ilmu-ilmu Informatika dan Manajemen Jurnal Intelek Dan Cendikiawan Nusantara Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Modem : Jurnal Informatika dan Sains Teknologi JIMT: Jurnal Informatika, Multimedia dan Teknik
Deris Santika
Universitas Sebelas April
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Other

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Desain Sistem Internet Of Things untuk Monitoring Kebocoran Gas Berbasis Website dengan Notifikasi Real-Time Deris Santika; Muhamad Rian Aprilyawan; Fathoni Mahardika
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 5 No. 1 (2025): Juni 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v5i1.7668

Abstract

Kebocoran gas LPG (Liquefied Petroleum Gas) menjadi salah satu ancaman serius bagi keselamatan rumah tangga. Penelitian ini bertujuan untuk mengembangkan sistem berbasis Internet of Things (IoT) yang mampu mendeteksi kebocoran gas secara real-time menggunakan mikrokontroler ESP32, sensor MQ2 untuk mendeteksi konsentrasi gas, dan sensor DHT11 untuk memantau suhu serta kelembapan. Sistem ini dirancang untuk mengirimkan notifikasi otomatis melalui aplikasi WhatsApp dan dapat dikontrol dari jarak jauh melalui website. Metode pengembangan yang digunakan adalah pendekatan Waterfall, yang memastikan setiap tahap dikerjakan secara terstruktur. Hasil pengujian menunjukkan bahwa sistem memiliki akurasi tinggi dalam mendeteksi kebocoran gas dan merespons dengan cepat ketika konsentrasi gas mencapai ambang batas berbahaya. Sistem ini juga menawarkan potensi integrasi dengan teknologi smart home untuk pengembangan lebih lanjut. Dengan fitur notifikasi real-time dan kontrol jarak jauh, sistem ini memberikan solusi yang inovatif dan efisien untuk meningkatkan keamanan rumah tangga. Penelitian ini diharapkan dapat membantu masyarakat menciptakan lingkungan yang lebih aman, nyaman, dan cerdas.
School Website Design for SLB ABC Muhammadiyah Sumedang Using the Design Thinking Method Rayhan Fauzan Wahyu Hidayat; Fathoni Mahardika; Deris Santika
Infoman's : Jurnal Ilmu-ilmu Informatika dan Manajemen Vol. 20 No. 1 (2026): Infoman's
Publisher : LPPM & Fakultas Teknologi Informasi UNSAP

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Abstract

The development of information technology requires educational institutions to adapt to the digital era, including in the dissemination of information to stakeholders. SLB ABC Muhammadiyah Sumedang still relies on conventional methods such as bulletin boards and WhatsApp in disseminating school information, which are considered ineffective and not well documented. This research aims to design a user-centered school website design using the design thinking method in order to meet the needs of digitizing school information optimally. The research method used is design thinking with five main stages: empathize, define, ideate, prototype, and test. Data collection was carried out through in-depth interviews with teachers and school staff as the main users. The data is then analyzed using affinity diagrams, user personas, user journey maps, pain points analysis, and priority matrix to identify the needs and priorities of feature development. The prototype website was designed using Figma with four main pages: Home, Profile, Extracurricular, and Gallery. The prototype evaluation was carried out using the System Usability Scale (SUS) and User Experience Questionnaire (UEQ) instruments involving 20 respondents. The results of the study show that the website prototype successfully meets the needs of users very well. The SUS evaluation showed an average score of 74 in the "Good to Excellent" category, while the UEQ evaluation resulted in an average score of 1.98 with an interpretation of "Excellent" that was in the top 10% of results based on international benchmarks. The resulting website design has clear navigation, responsive display, and structured content according to the needs of teachers and staff in managing school information. This research proves that the design thinking approach is effective in producing school website designs that are truly based on user needs. The iterative process in design thinking ensures that every feature and appearance of the website is developed based on empirical data from real users, resulting in a human-centered digital solution that can improve the effectiveness of communication and documentation of activities in the educational environment.
Analisis Komparatif Algoritma Machine Learning untuk Klasifikasi Tingkat Stres Mahasiswa Berdasarkan Data Kuesioner DASS-21 Satria Kamal Fikhriyadi; Maya Suhayati; Deris Santika
Jurnal Intelek Dan Cendikiawan Nusantara Vol. 3 No. 04 (2026): AGUSTUS - SEPTEMBER 2026
Publisher : PT. Intelek Cendikiawan Nusantara

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Abstract

Tingkat stres yang tinggi di kalangan mahasiswa menjadi isu penting yang memerlukan solusi deteksi dini berbasis teknologi. Penelitian ini bertujuan untuk mengevaluasi dan membandingkan performa tiga algoritma machine learning Logistic Regression, Random Forest, dan Gradient Boosting dalam mengklasifikasikan tingkat stres mahasiswa berdasarkan data kuesioner DASS-21. Penelitian menggunakan pendekatan kuantitatif dengan data yang dikumpulkan melalui survei daring. Data diproses melalui tahapan normalisasi dan transformasi fitur sebelum diterapkan pada masing-masing model. Evaluasi performa dilakukan menggunakan metrik akurasi, presisi, dan F1-score. Hasil analisis menunjukkan bahwa mayoritas mahasiswa (59%) berada pada tingkat stres sedang hingga sangat parah. Dari sisi performa, Logistic Regression menunjukkan kinerja paling baik dengan akurasi sebesar 60%, mengungguli Random Forest (45%) dan Gradient Boosting (30%). Hasil confusion matrix memperkuat temuan ini, menunjukkan bahwa model linear lebih mampu membedakan antar kelas dalam dataset kecil. Studi ini menegaskan bahwa Logistic Regression adalah pilihan paling efektif untuk klasifikasi stres dalam konteks data terbatas, serta menunjukkan potensi penerapan machine learning dalam sistem deteksi dini kondisi mental mahasiswa di lingkungan akademik
Perbandingan Xgboost dan Logistic Regression dalam Memprediksi Credit Card Customer Churn Rearizth Muhammad Daffaa; Deris Santika; Fathoni Mahardika
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 3 No. 3 (2025): Mei : Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v3i3.807

Abstract

With the times, cash transactions that used to use cash are now turning to credit cards. However, the increasing use of credit cards presents challenges, especially in maintaining customer loyalty. Customer churn is the loss of customers within a certain period for various reasons. Logistic Regression is a machine learning algorithm that studies the relationship between a dependent variable and several independent variables and Extreme Gradient Boosting (XGBoost) is a Gradient tree-boosting algorithm that offers out-of-core learning and sparsity awareness.The purpose of this study is to compare the performance between Logistic Regression and Extreme Gradient Boosting (XGBoost) algorithms in predicting customer churn in credit card services using evaluation metrics such as accuracy, precision, recall, and F1-score. Based on the research results, it can be concluded that XGBoost has better performance in all evaluation metrics, both in terms of precision, recall, F1-score, and accuracy. Based on the research, XGBoost shows superior performance compared to Logistic Regression in all evaluation metrics.
Co-Authors Ajar Basyar Tsani Assidiq, Muhamad Luthfi Dani Indra Junaedi Fathoni Mahardika Gilang Abdul Rahman Hendrawan, Fauzi Bayu Mahardika, Fathoni Maya Suhayati Muhamad Rian Aprilyawan Nova Nurhidayat Rangga Sanjaya, Rangga Rayhan Fauzan Wahyu Hidayat Rearizth Muhammad Daffaa Santi Papiyani Satria Kamal Fikhriyadi