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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.
JOB SATISFACTION AS A MEDIATOR OF THE RELATIONSHIP BETWEEN WORK FACTORS AND ORGANIZATIONAL COMMITMENT AMONG WOMEN IN MINING Mohd, Tengku; Abdullah, Khairal; Jeffry, Jeffry; Manazil, Qornul; Waluyo, Safril Rizki
SOSIOEDUKASI Vol 14 No 4 (2025): SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL
Publisher : Fakultas Keguruan Dan Ilmu Pendidikan Universaitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/sosioedukasi.v14i4.5883

Abstract

Women working in male-dominated industries such as mining often face distinctive organizational challenges related to work-life integration, job-role alignment, and inclusion. Drawing on theories of person-job fit and organizational commitment. This research delves into the connections between balancing work and personal life, matching individuals to suitable job roles, promoting diversity and inclusion, and how they all impact the job satisfaction and dedication to the organization amongst women working in the coal mining industry in Indonesia. Information was gathered from 169 female workers via a detailed online questionnaire and studied using PLS-SEM. Findings indicate that the compatibility of a person with their job has the most significant positive impact on job satisfaction, while work-life balance shows a negative correlation. Diversity and inclusion also exhibit a significant, though comparatively weaker, positive relationship with job satisfaction. Furthermore, job satisfaction fully mediates the effects of the independent variables on organizational commitment. These findings extend prior research on gendered work environments by highlighting the central role of job satisfaction as a mechanism linking contextual work factors to attitudinal outcomes in underrepresented female employee populations.
Performance Analysis of a Multisensor IoT System for Water Quality Surveillance at PDAM Makassar Syafaat, Muhammad; 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

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 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