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All Journal International Journal of Electrical and Computer Engineering Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Almana : Jurnal Manajemen dan Bisnis AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Jurnal Teknologi Terpadu Journal of Applied Engineering and Technological Science (JAETS) Journal of System and Computer Engineering Jurnal Informatika Terpadu Indonesian Journal of Intellectual Publication (IJI Publication) Global Abdimas: Jurnal Pengabdian Masyarakat Publikasi Riset Mahasiswa Manajemen Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Journal Pharmacy and Application of Computer Sciences Journal of Innovative and Creativity Advances in Computer System Innovation Journal (ACSI Journal) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Indonesian Journal of Intellectual Publication (IJI Publication)
Jeffry Jeffry
Prodi Ilmu Komputer, Institut Teknologi Bacharuddin Jusuf Habibie
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Rancang Bangun Aplikasi Tes Minat dan Bakat Berbasis Web dengan Pendekatan Scrum Jeffry, Jeffry; Marcel, Marcel
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 2 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i2.8896

Abstract

The selection of majors that align with students' interests and talents plays a crucial role in determining their academic success and future careers. However, the Faculty of Psychology faces significant challenges related to the efficiency of the interest-aptitude testing process and the quality of counseling services. Conventional approaches relying on manual forms and booklets have proven to be ineffective and time-consuming. Therefore, this research introduces an innovative solution in the form of a web-based interest test application designed using the agile scrum method. This application is designed to implement the RIASEC theory (Realistic, Investigative, Artistic, Social, Enterprising, and Conventional), which helps identify students' interests based on various types of interests and talents. The RIASEC theory offers a comprehensive framework for understanding students' interest tendencies, subsequently facilitating more accurate major selection. The agile scrum method was chosen to ensure the iterative development of the application and responsiveness to user feedback, thereby making it adaptable to the specific needs of the Faculty of Psychology. In initial testing, this application has shown the potential to improve the efficiency of the interest-aptitude testing process and the quality of counseling services. Features such as an intuitive user interface, automated data processing, and detailed test result reports are expected to reduce the time and resources required in the conventional process. Additionally, this application also allows easier access for students to take interest-aptitude tests anytime and anywhere, thus expanding the reach of counseling services. With this solution, it is hoped that the Faculty of Psychology can address existing constraints and provide more effective and efficient services in assisting students in selecting majors that align with their interests and talents. This application not only provides technological solutions but also contributes to improving the quality of education and career development for students in the future.
Optimizing short-term energy demand forecasting: a comprehensive analysis using autoregressive integrated moving average method Aziz, Firman; Jeffry, Jeffry; Buang, Misbahuddin; La Wungo, Supriyadi; Nasruddin, Nasruddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5924-5933

Abstract

This study addresses the critical gap in short-term electricity demand forecasting in South Sulawesi, where inconsistencies between projected and actual peak loads hinder daily operational planning, system stability, and investment efficiency. While previous studies have applied approaches such as fuzzy logic, ARIMA-ANN, and hybrid models, few have focused on simple, robust ARIMA-based models validated across different time spans for daily operational use. To address this, the autoregressive integrated moving average (ARIMA) model is implemented within the Box-Jenkins framework, using automated model selection through the pmdarima library and Akaike’s information criterion (AIC) to identify optimal parameter configurations. The study analyzes daily peak load data from 2018 to 2023, producing realistic forecasts with high accuracy. The selected ARIMA model achieves a mean absolute percentage error (MAPE) of 1.91% and a root mean square error (RMSE) of 38.123, demonstrating its effectiveness in capturing short-term load trends. These results confirm the suitability of ARIMA for short-term forecasting in energy systems and its potential to enhance operational decision-making, reduce forecasting errors, and improve investment planning. The study also establishes a methodological foundation for future development, including the integration of ARIMA with machine learning and the use of extended datasets to support strategic energy management.
Pemanfaatan Data Pengguna untuk Sistem Rekomendasi dalam Aplikasi Pemesanan Tiket Event Berbasis Android Yunendar, Wakhid; Jeffry, Jeffry
Journal of System and Computer Engineering Vol 5 No 2 (2024): JSCE: Juli 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i2.2369

Abstract

Penelitian ini bertujuan untuk memanfaatkan data pengguna pada aplikasi pemesanan tiket event berbasis Android sebagai dasar dalam pengembangan sistem rekomendasi event. Sistem ini dirancang agar dapat memberikan saran event yang relevan berdasarkan preferensi pengguna sebelumnya. Metode penelitian yang digunakan adalah metode deskriptif kuantitatif dengan pendekatan prototyping dalam pengembangan perangkat lunak. Data diperoleh melalui observasi, wawancara, dan kuesioner terhadap pengguna aplikasi di Kota Makassar. Hasil penelitian menunjukkan bahwa sistem rekomendasi berbasis content-based filtering mampu menyesuaikan daftar event dengan minat pengguna, meningkatkan kenyamanan serta efisiensi dalam proses pencarian dan pemesanan tiket. Berdasarkan uji persepsi terhadap 21 responden, sebanyak 90% menyatakan fitur rekomendasi memudahkan mereka menemukan event yang relevan.
Penerapan Metode Certainty Factor dan Forward Chaining pada Sistem Pakar Untuk Mendiagnosa Penyakit Ginjal Jeffry, Jeffry; Usman, Syahrul
Indonesian Journal of Intellectual Publication Vol. 1 No. 1 (2020): Nopember 2020, IJI Publication
Publisher : Unit Publikasi Ilmiah Perkumpulan Intelektual Madani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51577/ijipublication.v1i1.35

Abstract

Ilmu komputer yang mempelajari kemampuan komputer untuk bertindak dan memiliki kecerdasan seperti manusia dikenal sebagai kecerdasan buatan, yang termasuk dalam kecerdasan buatan antara lain: penglihatan komputer, pengolahan bahasa alami, robotika, jaringan syaraf tiruan, sistem pakar (expert system). Penelitian ini bertujuan untuk membuat suatu sistem pakar yang digunakan untuk mendiagnosa penyakit ginjal, dimana pengguna bisa mendiagnosis sendiri (skrining mandiri) berdasarkan gejala yang dirasakannya. Pengetahuan pada sistem direpresentasikan dalam bentuk aturan dan metode penalaran yang digunakan adalah metode runut maju (forward chaining) sedangkan nilai kepastian terhadap penyakit menggunakan metode certainty factor yaitu diperoleh dari kombinasi nilai dari user dan pakar. Hasil penelitian menunjukkan bahwa sistem ini mampu mendiagnosa kemungkinan jenis penyakit ginjal yang diderita oleh user dengan menampilkan besaran kepercayaan dari tiap-tiap penyakit. Dari hasil percobaan diperoleh bahwa nilai certainty factor pada Nefritis tubulointerstisial sebesar 0,7502, untuk Sistitis Interstisial sebesar 0,7308, Kanker Kandung Kemih sebesar 0,6429. Sehingga nilai CF terbesar merupakan keputusan dari sistem pakar ini. Besarnya nilai kepercayaan tersebut merupakan hasil perhitungan dengan menggunakan metode certainty factor.
Sistem Deteksi Kekeruhan Air Berbasis Citra Digital Menggunakan Gaussian Filtering dan Thresholding jeffry, jeffry
Indonesian Journal of Intellectual Publication Vol. 5 No. 2 (2025): Maret 2025, IJI Publication
Publisher : Unit Publikasi Ilmiah Perkumpulan Intelektual Madani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51577/ijipublication.v5i2.696

Abstract

Penelitian ini bertujuan untuk mengidentifikasi tingkat kekeruhan air menggunakan metode pengolahan citra digital berbasis MATLAB. Sebanyak 10 sampel air dengan tingkat kekeruhan yang bervariasi dianalisis menggunakan dua pendekatan, yaitu pengukuran manual menggunakan TDS meter dan pengolahan citra digital melalui tahapan konversi RGB, Gaussian filtering, thresholding, serta analisis histogram nilai piksel. Hasil pengukuran menunjukkan pola hubungan berbanding terbalik antara nilai intensitas piksel citra dan tingkat kekeruhan air dalam satuan PPM. Misalnya, pada Sampel 1 dengan tingkat kekeruhan 52 PPM diperoleh nilai piksel sebesar 56,821, sedangkan pada Sampel 10 dengan kekeruhan tertinggi yaitu 83 PPM, nilai piksel turun menjadi 11,749. Secara umum, tren ini konsisten pada seluruh sampel, menunjukkan bahwa semakin tinggi tingkat kekeruhan air, semakin rendah nilai piksel yang dihasilkan. Temuan ini membuktikan bahwa pendekatan berbasis pengolahan citra digital dapat digunakan sebagai metode alternatif yang efisien dan praktis untuk mendeteksi tingkat kekeruhan air secara kuantitatif
Performance Analysis of a Multisensor IoT System for Water Quality Surveillance at PDAM Makassar Muhammad Syafaat; Jeffry Jeffry
Journal of Innovative and Creativity Vol. 5 No. 3 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i3.4885

Abstract

IoT-Based Water Monitoring System with Case Study of Makassar City PDAM is a tool made to provide convenience to PDAM (Regional Drinking Water Company) employees, especially at Makassar City PDAM, to determine the pH value of water, TDS value and NTU level value in water reservoirs using a water pH sensor, TDS sensor and LDR sensor which will be displayed on a website application via an internet network in the form of a graph. If the pH value read on the water pH sensor is pH 6.5-8.5, it can be declared that the water is in proper condition, if the ppm value read to the TDS sensor is 0-300 ppm, the water is declared proper and if the ppm value read to the LDR sensor is 0-25 NTU, the water is declared proper. the parameter accuracy rate of the pH Sensor is 94.74%, the TDS Sensor is 93.70%, while the Water Turbidity sensor has an accuracy rate of 85.31% so that the overall accuracy rate of this consumable water monitoring system is 91.25%.
Penerapan Tesseract OCR untuk Validasi Pembayaran Otomatis dalam E-Commerce Wijaya, Annisa Salsabila Apriliya; Auliyah, A Inayah; Jeffry, Jeffry; Aziz, Firman; Usman, Syahrul
Journal of System and Computer Engineering Vol 7 No 2 (2026): JSCE: April 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i2.2625

Abstract

The rapid expansion of e-commerce in Indonesia has resulted in a significant increase in digital transactions, necessitating expedited and precise payment verification. Administrators at the SweetJab hijab e-commerce platform must manually verify bank transfer receipts, a process that is time-consuming and susceptible to errors. This study utilises Optical Character Recognition (OCR) with the Tesseract engine as a supplementary approach for verifying transfer payments on the SweetJab website. The methodology encompasses image preprocessing (resizing to 200%, converting to greyscale, and enhancing contrast), employing Tesseract OCR with PSM 6 and an LSTM model for character recognition, and utilising regular expressions (regex) to extract structured transaction data. We employed Black Box Testing and Character Error Rate (CER) computations on 40 preliminary test samples and 40 post-implementation samples to assess the system. The initial test demonstrated an accuracy of 89.5%, which increased to 92.5% upon complete system integration. This study demonstrates that OCR is an effective method for extracting information from payment receipts, while maintaining security through a final manual verification by the administrator.
Spatio-Temporal Graph Neural Network Based on Nonlinear Time–Frequency Features for Mu-ERD Classification in Multi-Session EEG Motor Imagery Firman Aziz; Jeffry Jeffry; Syahrul Usman; Rahmat Fuadi Syam; Muhammad Nur Arafah; Nurul Fathanah Mustamin
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 2 (2026): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i2.8679

Abstract

Mu rhythm event-related desynchronization (ERD) is a key indicator of motor imagery activity based on EEG signals. However, accurate classification of ERD remains challenging due to the nonlinear nature of EEG signals and inter-session variability. This study proposes a motor imagery classification approach using a Spatio-Temporal Graph Neural Network (ST-GNN) model that leverages nonlinear time-frequency features extracted via Variational Mode Decomposition (VMD) and Synchrosqueezing Transform (SST). The dataset was collected from a single healthy subject across five separate sessions, each consisting of two conditions: relaxation and motor imagery. After preprocessing and segmentation, features were extracted and represented as spatio-temporal graphs to be processed by the ST-GNN. The model was evaluated using metrics such as accuracy, F1-score, AUC-ROC, and the Session Stability Index (SSI). The results show that the ST-GNN achieved an accuracy of 94.2%, F1-score of 94.1%, and AUC-ROC of 96.1%, along with high prediction stability across sessions. This performance outperformed baseline models including CNN, CSP+SVM, and STFT+MLP.These findings support the hypothesis that ERD is a distributed brain network phenomenon and demonstrate that the ST-GNN approach with VMD/SST-derived features is a promising strategy for developing adaptive and accurate BCI systems.
Co-Authors A Suyuti, Muh Zulfadli Abasa, Sustrin Adriani, Ika Reskiana Aljabar, Andi Almuhajir Haris, Almuhajir Andi Taufiqurrahman Akbar Andri Dwi Utomo Anirwan Anirwan Anwar Arafah, Muhammad Nur Auliyah, A Inayah Ayu Asrhi, Nur Azminuddin I. S. Azis Batau, Radus Binti Mamluatul Karomah Buang, Misbahuddin Enal Wahyudi, Abdi Fadliana, Nurul Firman Aziz Ishak, Pertiwi Iskandar, Imran Ismail Ismail Ispanti Zaman Kahar Gani Kandakon, Elisabeth Tri Juliana Kurniyan Sari, Sri La Wungo, Supriyadi M Rezky Armansyah Marcel Marcel Mardewi Mardewi Mardewi, Mardewi Mon, Muhammad Donal Muhammad Nur Arafah Muhammad Syafaat Nasruddin Nasruddin Nipsa Asdiana Supak Nur Ayu Asrhi Nur Ayu Asrhi Nurdyansa Nursalim Nurul Ahyana Nurul Fathanah Mustamin Nyimas Artina Panggabean, Benny Leonard Enrico Putra Yuzi Bachmid, Fadel Muhammad Qamal Qamal Rahmat Fuadi Syam Rijal, Muhammad Rimalia, Watty Santoso, , Budy Sari, Sri Kurniyan Sasmita, Dhilan Sentoso, Antony Sukarno Abby Sumardi Sumardi Susi Handayani Syafaat, Muhammad Syahrul Usman Syam, Rahmat Fuadi Syam, Rahmat Fuady Tarisafitri, Nahla Velayaty, Ali Akbar Wahyudi, Andi Enal Wibowo. K, Trisno Wijaya, Annisa Salsabila Apriliya Wungo, Supriyadi La Yeti Kule Yunendar, Wakhid