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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Sistem Komputer & Kecerdasan Buatan Infotek : Jurnal Informatika dan Teknologi Jurnal Sistem Informasi dan Sistem Komputer ABSYARA: Jurnal Pengabdian Pada Masyarakat Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat)
Harianto Harianto
Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Other

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Pendampingan LMS Berbasis Outcome-Based Education dan Conditional Access pada Dosen PGSD Universitas Hamzanwadi Hirmayanti; Harianto; Zaenul Amri
Jurnal Teknologi Informasi untuk Masyarakat Vol. 4 No. 1 (2026): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v4i1.35087

Abstract

The advancement of digital technology in higher education has encouraged the utilization of Learning Management Systems (LMS) not only as platforms for delivering learning materials but also as tools for supporting competency-based and adaptive learning. However, LMS implementation in the Elementary School Teacher Education Program at Hamzanwadi University has primarily focused on basic learning features and has not fully utilized adaptive learning functionalities such as conditional access. This community service program aimed to enhance lecturers’ competencies in developing and managing an Outcome-Based Education LMS integrated with conditional access features to support adaptive learning. The program was conducted through several stages, including needs assessment, training material development, workshops, digital course design practices, LMS implementation mentoring, and activity evaluation. The results indicated that all participants successfully developed Outcome-Based Education courses within the LMS, while 15 lecturers successfully implemented the conditional access feature in their courses. In addition, 85% of participants reported that the mentoring activities improved their ability to develop digital assessments, design adaptive learning activities, and utilize LMS features more effectively. The implementation of the Outcome-Based Education LMS also facilitated more systematic and measurable monitoring of student learning outcomes. Therefore, the mentoring program contributed positively to strengthening lecturers’ digital competencies and supporting the development of adaptive learning environments oriented toward student learning outcomes
Pengembangan Aplikasi Web Pembelajaran Matematika Terintegrasi Fitur Evaluasi Otomatis Zaenul Amri; Harianto; Handayani; M. Nurul Wathani
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.35281

Abstract

The current development of information technology provides a significant opportunity for digital transformation in the education sector, particularly to address difficulties in understanding concepts in Mathematics at the elementary school level. Based on observations at SDN Loang Tuna, the material delivery process is still dominated by conventional teaching methods utilizing textbooks and whiteboards. The limitations of these teaching aids result in low levels of interactivity and independent learning interest among students. The purpose of this study is to design and develop an information system in the form of a web-based Mathematics e-learning application that comprehensively integrates interactive material modules with an automatic evaluation feature. The software development methodology used in this study adopts the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. The stages of this methodology include the identification of system requirements, the design of interface and database architectures, programming with multi-user access rights management, and software functionality testing using the Black-Box Testing method. The results of the study indicate that the application was successfully built according to the specifications. Based on the Black-Box Testing, the system demonstrates a functionality success rate of 88%, which is categorized as highly feasible. The automatic evaluation feature is proven to have high accuracy in processing real-time grade calculations, which significantly reduces the administrative workload of teachers and provides instant feedback for students. Therefore, the interactive interface of this application is effective in increasing user engagement, making it an innovative and measurable technological solution to advance the quality of Mathematics learning.
Prediksi Kegagalan Build Real-Time Pada Pipeline CI/CD Menggunakan Pendekatan Machine Learning Berbasis Data Streaming Hirmayanti Hirmayanti; Harianto Harianto; Rooy Marthen Thaniket
Jurnal Sistem Informasi dan Sistem Komputer Vol 11 No 2 (2026): Vol 11 No 2 - 2026
Publisher : STIMIK Bina Bangsa Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51717/simkom.v11i2.1414

Abstract

Kegagalan proses build pada lingkungan Continuous Integration/Continuous Deployment (CI/CD) dapat menghambat rilis perangkat lunak, meningkatkan biaya perbaikan, dan menurunkan efisiensi pengembangan. Hal ini menunjukkan perlunya sistem prediksi yang cepat, adaptif, serta mampu menangani data yang terus mengalir secara real-time. Penelitian ini bertujuan untuk menganalisis dan membandingkan kinerja beberapa algoritma online machine learning dalam memprediksi kegagalan build pada pipeline CI/CD. Dataset yang digunakan berasal dari TravisTorrent yang mencakup aktivitas repositori, perubahan kode, metrik pengujian, serta riwayat build. Tahapan penelitian meliputi preprocessing data, pembentukan skema data streaming, penerapan model Hoeffding Tree, Adaptive Random Forest (ARF), dan Online Logistic Regression, serta evaluasi menggunakan metrik accuracy. Hasil eksperimen menunjukkan model terbaik mencapai accuracy 97,35%, lebih tinggi dibandingkan penelitian sebelumnya sebesar 95,9%. Peningkatan absolut sebesar 1,45 poin persentase atau sekitar 1,51% ini membuktikan bahwa pendekatan yang digunakan lebih efektif dalam mengenali pola kegagalan build pada lingkungan CI/CD berbasis streaming data.
Improving Imbalanced Polycystic Ovary Syndrome Classification Using a Leakage-Free Machine Learning Pipeline Baiq Andriska Candra Permana; Zulkipli; Muhammad Wasil; Harianto
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.16752

Abstract

Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder affecting women of reproductive age and poses challenges for early diagnosis due to heterogeneous clinical presentations and imbalanced clinical datasets. This study aims to develop a data leakage–free machine learning pipeline to enhance the accuracy and reliability of PCOS classification using clinical data. The dataset underwent preprocessing and normalization, followed by stratified data splitting with an 80:20 ratio to maintain class proportions. The proposed pipeline was implemented within a unified computational framework integrating feature selection based on the ANOVA F-test, class imbalance handling using the Synthetic Minority Over-sampling Technique (SMOTE), and classification using a Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel. Hyperparameter tuning was performed using GridSearchCV combined with K-Fold Cross-Validation to ensure model robustness and consistency. The experimental results indicate that the proposed model achieved an accuracy of 0.9074, with precision, recall, and F1-score values of 0.8378, 0.8857, and 0.8611, respectively. Furthermore, ten dominant clinical features were identified, primarily related to hormonal profiles and ovarian morphology. These results demonstrate that the data leakage–free pipeline improves the validity and stability of PCOS prediction. The findings suggest that this approach may serve as a supportive tool for clinical decision-making, particularly in facilitating early and objective identification of PCOS.
Perbandingan Performa Sensor DHT11, DHT22, dan 808H5V5 terhadap Pengukuran Kelembapan Udara Berbasis Internet Of Things Jumawal; Harianto; Mahpuz; Muhammad Wasil
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 1 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i1.33069

Abstract

This study aims to compare the performance of three air humidity sensors—DHT11, DHT22, and 808H5V5—integrated with an ESP8266 microcontroller based on the Internet of Things (IoT). The system was designed to monitor air humidity in real-time through a web server that displays measurement data from the three sensors along with a hygrometer as a reference. Data collection was conducted every hour from 08:00 to 17:00 under stable environmental conditions. The results show that the DHT22 sensor achieved the highest accuracy, with an average deviation of 0.3% compared to the hygrometer. The 808H5V5 sensor demonstrated the fastest response with an average deviation of 0.6%, while the DHT11 sensor had an average deviation of 1.1% and slower response time. All three sensors successfully transmitted real-time data through an accessible web server. Based on these findings, the DHT22 is recommended as the most accurate sensor for IoT-based humidity monitoring systems, while the DHT11 and 808H5V5 remain suitable for simpler applications requiring moderate precision and lower cost.
Co-Authors Aris Sudianto Bahtiar, Hariman Baiq Andriska Candra Permana Hamzan Ahmadi Handayani Hirmayanti Indra Gunawan Jumawal, Jumawal Lalu Kerta Wijaya M. Nurul Wathani Mahpuz Moh. Farid Wajdi Muhammad Sadali Muhammad Wasil Nur, Amri Muliawan Rooy Marthen Thaniket RR. Ella Evrita Hestiandari Sadali, Muhamad Suhartini, Suhartini Zaenul Amri Zulkipli