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All Journal Journal of System and Computer Engineering Jurnal Pengabdian Mandiri Knowbase : International Journal of Knowledge in Database Jurnal Bahasa Rupa
Mursalim Mursalim
Universitas Teknologi Akba Makassar
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media Social Sciences Other

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Application of Case Based Reasoning Using The K-Nearest Neighbor Algorithm in an Expert System for Diagnosing Pests and Diseases of Sugarcane Plants Andi Maulidinnawati Abdul Kadir Parewe; Mursalim Mursalim; Titis Sari Putri; Hermawati Hermawati
Knowbase : International Journal of Knowledge in Database Vol 2, No 2 (2022): December 2022
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v2i2.5959

Abstract

Sugarcane pests and diseases are still diagnosed manually, which can lead to errors such as data loss or inaccurate data. The goal of this research is to develop an expert system for identifying plant pests and diseases that affect sugarcane yield and quality. This data was obtained through literature study, observation, and interviews. The Case Based Reasoning method is used to find cases by comparing previous cases with recent cases using similarity calculations with the K-Nearest Neighbor algorithm to find the best solution from the identified cases. The results of this study indicate that the expert system for diagnosing sugarcane pests and diseases is easy to use, the appearance is easy to reach, and the diagnostic process does not take a long time. Based on testing the accuracy of the system to diagnose according to the expert's mind, it got an accuracy of 96% from 50 cases tested with the system and got a percentage result of 87.33% from 10 respondents including very feasible criteria.
SOSIALISASI IMPLEMENTASI SISTEM KEHADIRAN KARYAWAN TERINTRAGRASI GEOTAGGING PADA PT. KOOKMIN CARD FINANSIA MULTI FINANCE Markani Pato; Ramlah P; Nurnaningsih Nurnaningsih; Syaharullah Disa; First Wanita; Neneng Awaliah; Asnimar Asnimar; Mursalim Mursalim; Amran Amiruddin
JURNAL PENGABDIAN MANDIRI Vol. 2 No. 2: Februari 2023
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Employees of PT Kookmin Card Finansia Multi Finance, still uses traditional methods is fingerprint where are have various limitations and weaknesses such as making a marketing employee assigned outside the company to come to the office first to make kehadiran. This study aims to create a Geotagging Integrated Attendence System at PT Kookmin Card Finansia Multi Finance to make it easier for marketing employees to do kehadiran and documentation by providing gps access to find out the location. And the company can monitor employees on duty outside the company. The system development method used in this research is the Rapid Application Development (RAD) method. The RAD method is a system development method with a relatively short processing time. This data was obtained through, 1) Field Research, 2) Direct interviews with marketing, 3) Documentation. The system development method used in this research is the Rapid Application Development (RAD) method. The RAD method is a system development method with a relatively short processing time. Based on the test results using the UAT (User Acceptance Tens) testing technique, 84% of the 21 respondents obtained results, so it was declared feasible based on the tests carried out
Konstruksi Storyline Sebagai Strategi Komunikasi Company Profile PT. Aliyah Perdana Wisata Muhammad Rizal H; Butsiarah Butsiarah; Ahmad Nur Ikhsan; Mursalim Mursalim
Jurnal Bahasa Rupa Vol. 6 No. 1 (2022): Jurnal Bahasa Rupa Oktober 2022
Publisher : Prahasta Publisher (manage by: DRPM Institut Bisnis dan Teknologi Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/bahasarupa.v6i1.777

Abstract

PT. Aliyah Perdana Wisata is a company engaged in organizing Hajj and Umrah. PT. Aliyah Perdana Wisata since its inception has focused on the field of organizing Hajj and Umrah, and has dispatched thousands of pilgrims each year and provided the best service to pilgrims while in the holy land. In order for Aliyah Wisata to be better known by the wider community, a promotional media in the form of video motion graphics is needed so that the delivery of interesting information and able to convey information well to potential customers. This study aims to design a company profile video for PT. Aliyah Perdana Wisata through motion graphic animation to be better known by the wider community, especially in Makassar City. This study uses the MDLC (Multimedia Development Life Cycle) method which consists of 5 phases, namely the concept phase (concept), the design phase (design), the material collecting phase (material collection), the assembly phase (manufacture), the testing phase (testing) and distribution phase. The final result of this research is an animated motion graphic video as a company promotion media regarding the implementation of hajj and umrah.
Augmented Reality and Virtual Reality in English Learning: Bibliometric Analysis of Research Trends, Citation Patterns, and Future Directions Tamra Tamra; Wisda Wisda; Muhammad Rizal H; First Wanita; Mursalim Mursalim
Journal of System and Computer Engineering Vol 7 No 1 (2026): JSCE: January 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i1.2472

Abstract

This study conducts a comprehensive bibliometric analysis to map the development of research on Augmented Reality (AR) and Virtual Reality (VR) in English language learning (ELL) from 2010 to 2025. Using 386 Scopus-indexed documents, the analysis examines publication growth, citation performance, influential authors and countries, core sources, and the thematic evolution of immersive learning research. The findings show a sharp increase in scientific production after 2020, reflecting the global rise of digital and immersive technologies in education. China, Korea, and Malaysia emerge as dominant contributors, demonstrating Asia’s leading role in AR/VR-driven language innovation. Citation trends reveal the coexistence of foundational highly cited works and rapidly influential recent publications. Source impact analysis confirms the interdisciplinary character of the field, spanning educational technology, linguistics, psychology, and computer science. Trend-topic analysis indicates a shift from general pedagogical themes toward AI-enhanced AR applications, deep learning, virtual reality environments, and interactive vocabulary learning systems. Despite significant growth, gaps remain in long-term studies, cross-country collaboration, and research on advanced language competencies. Overall, the study provides a data-driven understanding of how AR and VR have evolved as transformative tools for English language learning and offers strategic insights for guiding future research agendas in immersive educational technologies.
Implementation of Fisher-Yates Shuffle Algorithm in Mobile-Based Vocabulary Learning Game for Children with Disabilities khaidir rahman nasir; Tamra Tamra; Muhammad Rizal H; First Wanita; Mursalim Mursalim
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.v7i2.2479

Abstract

Children with disabilities face significant challenges in vocabulary acquisition, necessitating the development of specialized educational technologies that accommodate their unique learning characteristics. This study aims to implement the Fisher-Yates shuffle algorithm in a mobile-based vocabulary learning game specifically designed for children with disabilities, ensuring unbiased randomization of educational content to promote authentic vocabulary comprehension. This research employed the Multimedia Development Life Cycle methodology, encompassing concept definition, design, material collection, assembly, testing, and distribution phases. The Fisher-Yates shuffle algorithm was implemented following the modern Durstenfeld variant, operating through backward iteration, generating random indices, and performing in-place element swapping. Algorithm validation was conducted through simulation calculations and chi-square goodness-of-fit statistical testing across ten thousand randomization trials. The application "Tebak Kosakata" successfully integrates the randomization algorithm with an accessible user interface, featuring multimodal content presentation, immediate positive feedback mechanisms, and cumulative scoring systems. Simulation calculations confirmed that each vocabulary item maintains an equal probability for occupying any position in the final sequence. Statistical validation yielded a chi-square value of 8.47 with nine degrees of freedom and a probability value of 0.487, confirming uniformly distributed randomization without detectable bias. The algorithm achieves optimal computational efficiency with linear time complexity and constant auxiliary space complexity. The randomization of question sequences and answer option positions effectively prevents pattern-based response strategies, encouraging authentic vocabulary learning rather than positional memorization. This study establishes that the Fisher-Yates shuffle algorithm constitutes an effective mechanism for implementing unbiased randomization in educational games for children with disabilities, bridging computational algorithm theory with special education pedagogy while providing a replicable methodological framework for future development.
Explainable Machine Learning for Long-Term Monthly Hydroclimatic Forecasting and Extreme-Event Detection Arif Fadillah; Markani Pato; Nuraida Latif; Benny Leornard Encrico Panggabean; Muhammad Rizal; Mursalim Mursalim; Muhajirin Muhajirin
Journal of System and Computer Engineering Vol 7 No 3 (2026): JSCE: July 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i3.2741

Abstract

Long-term hydroclimatic prediction in arid urban environments remains methodologically demanding because monthly records are often intermittent, highly seasonal, zero-inflated, and dominated by rare but consequential extreme events. Using a 121-year monthly hydroclimatic record for Makkah, Saudi Arabia, spanning January 1901 to December 2021, this study develops an explainable hybrid machine-learning framework for monthly forecasting, seasonal diagnostics, and extreme-event detection. The dataset contains 1,452 monthly observations with a mean value of 6.19, median of 3.00, standard deviation of 8.05, and maximum of 52.00, indicating a strongly skewed distribution. Exploratory analysis reveals pronounced seasonality: November, December, and January exhibit the highest hydroclimatic values, whereas June is consistently dry across the full record. A temporal feature set was constructed using lag variables, rolling statistics, annual seasonal memory, cyclical month encodings, and trend indicators. Several predictive models were evaluated, including Random Forest, Extra Trees, Histogram Gradient Boosting, XGBoost, and a hybrid SARIMA–Random Forest residual-correction model. Extra Trees achieved the best forecasting performance on the holdout period, with MAE = 2.997, RMSE = 5.603, sMAPE = 57.669%, and R² = 0.518. Extreme-event detection was performed using a 90th-percentile threshold of 17.68, identifying 146 extreme months over the full record. The best classification trade-off was obtained by Histogram Gradient Boosting, while Random Forest produced the highest ROC-AUC. SHAP-based interpretation demonstrates that seasonal phase variables and annual memory features dominate model behaviour, especially month_cos, month_sin, same_month_last_year, and lag_12. The findings show that interpretable ensemble learning can provide a more transparent and operationally relevant framework than accuracy-only forecasting for arid-region hydroclimatic risk assessment.
Co-Authors - STMIK AKBA Makassar, Wisda Ahmad Nur Ikhsan Amran Amiruddin Andi Maulidinnawati Abdul Kadir Parewe Arif Fadillah Arif Fadillah Asnimar Asnimar Benny Leornard Encrico Panggabean Butsiarah First Wanita Hermawati Hermawati Khaidir Rahman Nasir Latif, Nuraida Markani Markani Muhajirin, Muhajirin Muhammad Rizal H Neneng Awaliah Nurnaningsih Nurnaningsih Ramlah P Syaharullah Disa, Syaharullah Tamra Tamra Titis Sari Putri