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All Journal Program Kreativitas Mahasiswa - Penelitian Jurnal Teknologi Informasi dan Multimedia Jurnal Abdi Masyarakat Indonesia Melek IT: Information Technology Journal Jurnal Sains Terapan : Wahana Informasi dan Alih Teknologi Pertanian NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Penelitian Rumpun Ilmu Teknik Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Penelitian Teknologi Informasi dan Sains Current STEAM and Education Research Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Publikasi Teknik Informatika Jurnal Kendali Teknik dan Sains
Nur Aziezah
Department Of Software Engineering Technology, School Of Vocational Studies, IPB University, Jl. Raya Darmaga Kampus IPB, Jawa Barat 16680, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Physics Public Health Social Sciences Veterinary

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Penerapan Google Sites dan Apps Script Untuk Sistem Informasi Terintegrasi Andaman, Akhdan Ravi; Aziezah, Nur; Yulianti, Wina; Martini, Rina; Rusmiyati, Henny; Akhdan Ravi Andaman; Nur Aziezah; Wina Yulianti; Rina Martini; Henny Rusmiyati
Melek IT : Information Technology Journal Vol. 11 No. 2 (2025): Melek IT: Information Technology Journal
Publisher : Informatics Department-Universitas Wijaya Kusuma Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30742/melekitjournal.v11i2.411

Abstract

Transformasi digital dalam pendidikan mendorong perlunya sistem informasi yang efisien dan mudah diakses. Komisi Pendidikan Sekolah Vokasi IPB selama ini mengandalkan ekosistem Google, seperti Google Spreadsheet dan Google Form, namun menghadapi tantangan dalam integrasi dan visualisasi data. Penelitian ini bertujuan untuk mengembangkan sistem informasi pendidikan bernama MONIKA (Monitoring Informasi Komisi Pendidikan), yang dirancang menggunakan Google Sites dan Google Apps Script untuk mengintegrasikan data secara otomatis tanpa memerlukan hosting eksternal. Metode pengembangan yang digunakan adalah lean development dengan pendekatan iteratif melalui tahapan Build-Measure-Learn. Pengembang menguji sistem menggunakan metode black box testing untuk memastikan fungsionalitas sesuai dengan kebutuhan pengguna. Hasil menunjukkan bahwa semua fitur utama, seperti tampilan otomatis data dari Google Spreadsheet, pembatasan akses berbasis email, serta visualisasi data pada situs web, berfungsi dengan baik.
Analisis Pengaruh Kemudahan terhadap Tingkat Efektivitas Penggunaan Mesin Cetak Pelet Pakan Ternak Salsabila Diba Cahyani; Nur Aziezah; Hikmah Rahmah; Faldiena Marcelita; Inna Novianty
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.1976

Abstract

The pellet molding machine has high efficiency to make it easier to process animal feed pellets. The pellet processing process requires a series of activities such as grinding, mixing, pelleting and drying. Therefore, research was carried out to identify the effect of convenience on the level of effectiveness of using an animal feed pellet printing machine. The method used in this research is a quantitative method by distributing questionnaires via the Google Form platform. Validity tests, reliability tests and simple regression analysis are used to analyze the data obtained from filling out the questionnaire
Analisis Pengaruh Kemudahan Pengguna Terhadap Efektivitas Alat Kompresi Sampah Botol Plastik “Bottlepress” Berbasis IoT Shinta Arafah Hidayanti; Nur Aziezah; Hikmah Rahmah; Walidatush Sholihah; Inna Novianty
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.1991

Abstract

The purpose of this study was to determine the influence of users and the effectiveness of the Plastic Bottle Waste Compression Tool "Bottlepress" as an innovation in protecting the environment. The method used is a quantitative survey form using the Google Form platform in the form of a questionnaire to obtain a sample. Simple Linear Regression and Correlation methods were used as data analysis of this study.  The results of this study indicate that there is no influence between user convenience on compression tools with a greater significance α> 0.05, namely 0.373 and a regression coefficient of 0.167 units or 16.7% positive value.
Pengaruh Efektivitas Robot AI Berbasis Images Preprocessing Terhadap Kepuasan Pengguna Dalam Mendeteksi Kematangan Buah Tomat salsi kirana sya'bani; Nur Aziezah; Hikmah Rahmah; Ridwan Siskandar; Aep Setiawan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.2315

Abstract

This research aims to demonstrate the influence of the effectiveness of image preprocessing-based artificial intelligence technology in detecting the ripeness level of tomatoes on user satisfaction and to discover correlations between them. The applied research method is quantitative, with data collected through the distribution of questionnaires to attendees of the IT Festival 2023 Expo held on Sunday, August 27, 2023, at the Baranangsiang Campus, IPB. The data analysis methods used include Pearson correlation test, simple linear regression, coefficient of determination test, and T-test using SPSS 25.0 software. The test results indicate that the effectiveness of image preprocessing-based artificial intelligence technology has a positive and significant impact on detecting the ripeness level of tomatoes
Tingkat Kepuasan Pengguna Terhadap Kinerja Alat Kompressi Sampah Botol Plastik “Bottlepress” Berbasis IoT Yulanda Rizqi Ramadhini; Hikmah Rahmah; Nur Aziezah; Walidatush Sholihah; Inna Novianty
Jurnal Kendali Teknik dan Sains Vol. 2 No. 1 (2024): Januari: Jurnal Kendali Teknik dan Sains
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jkts-widyakarya.v2i1.2166

Abstract

The purpose of this research is to ascertain how satisfied users are with the functionality of the IoT-based “BottlePress” plastic bottle waste compression tool. This research uses a survey method with quantitative research with a sampling technique, namely distributing online questionnaires via Google Form. A simple regression test was used to analyze data obtained from filling out the questionnaire. According to the research findings, most users are satisfied with the performance of the IoT-based “BottlePress” plastic bottle waste compression tool.
Pengaruh Tingkat Kepuasan Pengguna Alat Simonair Terhadap Minat Pengguna Dalam Memonitoring Kualitas Air Dany Fadhilah; Hikmah Rahmah; Nur Aziezah; Walidatush Sholihah; Faldiena Marcelita
Jurnal Kendali Teknik dan Sains Vol. 2 No. 1 (2024): Januari: Jurnal Kendali Teknik dan Sains
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jkts-widyakarya.v2i1.2192

Abstract

Improving water quality is an important issue that governments and society must address. His one way to improve water quality is to monitor it regularly. Monitoring tools that are easy to use and accessible to the public can be a solution to improving water quality. The aim of this research is to assess how user satisfaction with Simonair affects their inclination towards monitoring water quality. The methodology involves conducting a survey with respondents utilizing the Simonair tool, and the gathered data is subjected to analysis through a straightforward linear regression examination.Top of Form The results show that users' satisfaction with the Simonair tool has a significant positive impact on their interest in water quality monitoring. The higher the user satisfaction, the more interested the user will be in  water quality monitoring with Simonair. Drawing from the findings of this investigation, it is possible to infer that users' satisfaction with the Simonair tool is an important factor influencing users' interest in water quality monitoring. Therefore, efforts are needed to increase user satisfaction with the Simonair tool and increase user interest in  water quality monitoring using Simonair.
Analisis Statistika Tingkat Kepuasan Pengguna Sistem Monitoring Mesin Cetak Pelet Pakan Ternak Berbasis IoT Khairunnisa Hayyu Kusnadi; Hikmah Rahmah; Nur Aziezah; Faldiena Marcelita; Inna Novianty
Jurnal Kendali Teknik dan Sains Vol. 2 No. 1 (2024): Januari: Jurnal Kendali Teknik dan Sains
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jkts-widyakarya.v2i1.2284

Abstract

The aim of this research is to analyze the processing of user satisfaction data on the IoT-based feed pellet machine monitoring system using the Blynk application among visitors of the IT Fest at the School of Vocational IPB University, majoring in Software Engineering Technology (TPL), Computer Engineering Technology, and Industrial Management from batches 57, 59, and 60. The research method employed in this study is quantitative research using descriptive statistics. The sampling technique utilized is a survey method, and the instrument for data collection is a questionnaire. Subsequently, the analysis of all data is conducted by performing testing stages using measures of central tendency, including mean, median, and mode. Using the Likert scale, conclusions can be drawn from the respondents' answers.
Artificial Neural Network-Based Classification of Water Quality Status in Ornamental Fish Farming Using IoT Sensor Data Nur Aziezah; Walidatush Sholihah; Faldiena Marcelita; Inna Novianty; Andri Hendriana; Ima Kusumanti
Current STEAM and Education Research Vol. 3 No. 3 (2025): Current STEAM and Education Research, Volume 3 Issue 3, December 2025
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.030302

Abstract

Water quality plays an important role in sustainable agriculture. Water quality also affects the quality and quantity of fishery production. In ornamental fish cultivation, water quality influences not only production, but also the shape and color of the fish. To achieve optimal results, water quality parameters need to be maintained. Manually monitoring water quality parameters faces many challenges such as being time-consuming and not providing real-time data. This study investigated the application of Artificial Neural Networks (ANNs) in classifying water quality status. This status is based on data collected using sensors in an Internet of Things (IoT)-based monitoring system. The dataset comprised five key parameters: pH, temperature, ammonia, total dissolved solids (TDS), and total suspended solids (TSS). This data was collected from aquariums cultivating the Denison barb (Sahyadria denisonii). Data preprocessing was performed using feature standardization. This aims to improve model performance. The ANN model was constructed with two hidden layers (32 and 16 neurons). This model was trained using the Adam optimizer, with categorical cross-entropy as the loss function. The dataset was divided into 80% for training and 20% for testing. The trained ANN model achieved an accuracy of 99.95%. It has low false-positive and false-negative rates. These results demonstrate the effectiveness of ANN in predicting water quality status using sensor-based data. This suggests its potential for real-time monitoring and decision-making support in small-scale ornamental fish aquaculture.
Digitalizing Scholarly Communication: Development and Functional Validation of a Web-Based Scientific Conference Management System Pandu Wicaksono; Nur Aziezah; Walidatush Sholihah
Current STEAM and Education Research Vol. 4 No. 2 (2026): Current STEAM and Education Research, Volume 4 Issue 2, August 2026
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.040202

Abstract

This study developed a standalone web-based system for managing scientific conferences, with a focus on manuscript submission and peer review. The work used the Waterfall model. Development moved through requirements analysis, system design, implementation, and functional validation. The requirements analysis identified four user roles: admin, reviewer, author, and guest. It also defined the main functions needed for manuscript submission, verification, reviewer assignment, review and feedback, status monitoring, and Letter of Acceptance (LoA) issuance. The system used separate frontend and backend components. Vue.js was used for the frontend, Laravel for the backend, and MySQL for the database. The components communicated through a JSON-based RESTful API. Functional validation was carried out with scenario-based black-box testing to check whether each function met its stated requirement without examining the source code. In total, 59 test scenarios were run. Every scenario produced the expected output, giving a 100% functional conformity rate. The results show that the system can perform the defined conference management functions within one digital platform for manuscript submission and peer review. It therefore provides a technical basis for a more structured process of research dissemination and scholarly communication. Further work is still needed to evaluate usability, performance, accessibility, security, and user satisfaction before its broader effectiveness can be assessed.
A Subject-Independent Comparison of EEGNet and CSP+LDA on EEGMMIDB: Implications for Assistive Educational Technology Nur Aziezah; Fajar Nur Hamzah; Walidatush Sholihah
Current STEAM and Education Research Vol. 4 No. 1 (2026): Current STEAM and Education Research, Volume 4 Issue 1, April 2026
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.040104

Abstract

Motor imagery (MI) electroencephalography (EEG) classification remains difficult in cross-subject settings because signals vary substantially between individuals. This study compares a compact deep learning model (EEGNet) with a classical Common Spatial Pattern and Linear Discriminant Analysis pipeline (CSP+LDA) for hands-versus-feet MI classification. Data came from the EEG Motor Movement/Imagery Dataset (EEGMMIDB) on PhysioNet. A leave-one-subject-out (LOSO) evaluation was conducted across 109 subjects using runs 6, 10, and 14. Preprocessing applied a 7-30 Hz band-pass filter, a 1-2 s post-cue window, and subject-wise z-score normalization. Because normalization used unlabeled statistics from each held-out subject, the setting is LOSO with unsupervised test-time normalization rather than a fully inductive calibration-free protocol. EEGNet reached a mean balanced accuracy of 0.660 ± 0.136 (macro-F1 0.640 ± 0.147; Cohen’s kappa 0.312 ± 0.271), whereas CSP+LDA reached 0.635 ± 0.141 (macro-F1 0.605 ± 0.164; kappa 0.270 ± 0.281). A descriptive paired comparison showed that EEGNet scored higher for 60 of 109 subjects, CSP+LDA scored higher for 47 subjects, and 2 subjects were tied. The aggregated EEGNet confusion matrix showed higher recall for hands than for feet (0.735 vs 0.574), and balanced accuracy varied widely across subjects. These results provide a reproducible subject-independent comparison on EEGMMIDB and show that inter-subject variability remains a major barrier to robust MI decoding. The reproducible pipeline also offers a practical neuroinformatics case for teaching biosignal preprocessing, leakage-aware validation, and model comparison, while the subject-level variability shows what must be addressed before assistive educational deployment.
Co-Authors Adelia Tri Aprilian Adelia Tri Aprilian Aditya Wicaksono Akhdan Ravi Andaman Andaman, Akhdan Ravi Anggi Mardiyono Anggi Mardiyono Arinda Choiris Dea Salsabela Ariya Pratama Adjie Nugroho Bayu Irianto BAYU WIDODO Dany Fadhilah Elka Firmanda Esa Ghanim Fadhallah Fajar Nur Hamzah Fami, Amata Hendriana, Andri Henny Rusmiyati Hikmah Rahma Hikmah Rahmah Hikmah Rahmah Hikmah Rahmah Ima Kusumanti Inna Novianty Inna Novianty Inna Noviyanti Irma Rasita Gloria Barus Irmansyah Khairunnisa Hayyu Kusnadi Marcelita, Faldiena Medhanita Dewi Renanti Mega Romadhona Nasir, Muhammad Nur Aziezah Pandu Wicaksono Ridwan Siskandar Rina Martini Rina Martini Rusmiyati, Henny Salsabila Diba Cahyani salsi kirana sya'bani Santoso Darmo Atmojo Saragih, Bennefit Christy Setiawan, Aep Sevia Dwi Yanti Shinta Arafah Hidayanti Sholihah, Walidatush Sofiyanti Indriasari Walidatush Sholihah Walidatush Sholihah Walidatush Sholihah Wina Yulianti Wina Yulianti Yulanda Rizqi Ramadhini