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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknologi Informasi dan Ilmu Komputer POSITIF RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) METIK JURNAL Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika JURNAL ILMIAH GLOBAL EDUCATION Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Minfo Polgan (JMP) Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Bangun Abdimas Variasi : Majalah Ilmiah Universitas Almuslim MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Journal of Deep Learning, Computer Vision and Digital Image Processing Journal of Advanced Computer Knowledge and Algorithms Journal Serambi Engineering (JSE) Jurnal Elektro dan Teknologi Informasi Bulletin of Engineering Science, Technology and Industry Jurnal Ragam Pengabdian Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Buletin Pengabdian
Zara Yunizar
Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Implementation of Horspool Algorithm on Book Search Application in Malikussaleh University Library Based on Mobile Android Gilang Wahyu Ramadhan Gilang; Zara Yunizar; Sujacka Retno
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

The development of information technology encourages innovation in library management systems, one of which is an efficient book search system. This thesis examines the application of the Horspool method in library book search applications to improve search speed and accuracy. The Horspool method is a pattern matching algorithm designed to speed up the text search process by utilizing a sliding table, which significantly reduces the number of comparisons required in pattern search. The developed application allows users to search for books based on title, author, or other keywords with fast and relevant results. An evaluation was conducted by comparing the search time between the Horspool method and the traditional search method. The evaluation results show that the Horspool method offers significant performance improvement, with faster search time and high accuracy.
Development of Portable IoT-Based Fish Pond to Enhance Freshwater Aquaculture Efficiency Rifkial Iqwal; M Ishlah Buana Angkasa; Nazwa Aulia; Subhan Hartanto; Tejas Shinde; Muhammad Fikry; Zara Yunizar
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This paper presents the development of iPooL, a portable Internet of Things (IoT)-based fish pond system designed to optimize freshwater fish farming, particularly in resource-constrained and urban environments. By integrating real-time monitoring of essential water parameters—such as pH, temperature, dissolved oxygen, and ammonia levels—iPooL ensures that optimal environmental conditions are maintained for fish health and growth. The system employs IoT sensors connected to an ESP32 microcontroller, which processes and transmits data to a cloud platform, enabling farmers to receive real-time alerts and manage their ponds via a mobile app. Field trials demonstrated that the iPooL system reduces fish mortality by 20% and improves fish growth rates by maintaining stable water conditions. Additionally, the automation of feeding schedules and water management reduces operational costs, particularly in labor and feed, resulting in a 30% increase in profitability. With an estimated return on investment (ROI) within one year, iPooL offers a cost-effective solution for both small- and medium-scale fish farmers. The system also promotes environmental sustainability by optimizing water usage and reducing the need for chemical additives. Its portability allows fish farming in non-traditional environments, such as urban rooftops, contributing to decentralized food production and reducing the environmental impact of transporting fish to urban markets. iPooL’s scalability, combined with future integration of artificial intelligence and renewable energy sources, positions it as a transformative tool for the aquaculture industry, supporting both economic development and sustainable farming practices.
Indonesian Sign Language (BISINDO) Alphabet Detection System Using YOLO (You Only Look Once) Algorithm Andra Munandar; Zara Yunizar; Sujacka Retno
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.952

Abstract

This research aims to develop an Indonesian Sign Language (BISINDO) alphabet detection system using the YOLOv5 algorithm, an efficient and fast deep learning-based object detection model. The dataset used consists of BISINDO alphabet images enriched through data augmentation techniques such as rotation, flipping, and brightness adjustment. The evaluation results show that the YOLOv5s model achieved very good performance, with an average precision of 85.2%, recall of 89.3%, F1-score of 87.2%, and mean average precision (mAP) of 87.1%. The confusion matrix also indicates the model's ability to differentiate each BISINDO alphabet with high accuracy. The training data testing showed the model successfully achieved consistent decreases in all loss components, such as a decrease in train box loss from 0.06 to 0.015, and validation loss converging towards 0.002 for object loss and class loss. The real time testing also shows that the YOLOv5-based BISINDO alphabet detection system can perform well and consistently, indicating the practical application potential of this system to facilitate communication between people with hearing/speech disabilities and the general public. Overall, this research has resulted in an accurate and realtime implementable BISINDO alphabet recognition system.
Optimization of low-density polyethylene (LDPE) in eco-paving block synthesis: A pathway toward community empowerment Fasdarsyah Fasdarsyah; Herman Fithra; Nura Usrina; Nanda Savira Ersa; Zara Yunizar; Muhammad Fauzan; Zulnazri; Febi Anriani; Maulida Yani Siregar
Buletin Pengabdian Bulletin of Community Services Vol. 6 No. 1 (2026): Bull. Community. Serv.
Publisher : LPPM Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/bulpen.v6i1.64

Abstract

Background and Aim: Blang Asan Village has economic potential in the brick production sector; however, production activities are still conventional and have not integrated innovations in construction material technology. In addition, unmanaged Low-Density Polyethylene (LDPE) plastic waste contributes to environmental problems. This community service activity aimed to implement a circular economy concept by transforming LDPE plastic waste into environmentally friendly construction materials in the form of eco-paving blocks. Methods: The program was implemented using an experimental and participatory approach involving local partners through socialization, technical training, and construction implementation assistance. Laboratory testing was conducted on six specimen variations molded using 3 kg hexagonal molds. The mixtures consisted of LDPE plastic waste, fine aggregate, coarse aggregate, cement, and varying amounts of used oil. Compressive strength tests were performed to determine the optimal composition. Results: The compressive strength test showed that the best composition was obtained with 15% LDPE without an oil mixture, producing a compressive strength value of 24.2 MPa. Based on SNI 03-0691-1996 standards, the product met the B Quality criteria, making it suitable for parking area applications. The program successfully transferred technology to local brick craftsmen, enabling them to independently produce eco-friendly construction materials. Conclusion: The application of LDPE-based eco-paving blocks effectively reduced plastic waste while creating value-added construction products with economic potential. This program also supported the development of sustainable green economy practices in Blang Asan Village.
SISTEM INFORMASI GEOGRAFIS REKOMENDASI SERVIS KOMPUTER BERBASIS ANDROID: METODE MULTI ATTRIBUTE UTILITY THEORY DAN ALGORITMA A-STAR: GEOGRAPHIC INFORMATION SYSTEM FOR COMPUTER SERVICE RECOMMENDATION BASED ON ANDROID: MULTI ATTRIBUTE UTILITY THEORY METHOD AND A-STAR ALGORITHM Walad Hidayat; Zara Yunizar; Nunsina
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.5997

Abstract

This study developed an Android-based Geographic Information System to recommend computer repair service shops in Lhokseumawe City, addressing the gap in previous studies that have not integrated recommendation and route-finding systems into a single mobile application. Data were collected through surveys of 17 active shops using weighted questionnaires and interviews. The Multi Attribute Utility Theory (MAUT) method is used to evaluate seven criteria, such as years of operation, repair coverage, spare part availability, service cost, warranty, number of technicians, and rating. The A-Star algorithm was applied to calculate the shortest route based on GPS coordinates. Results showed that “JCom” achieved the highest recommendation score (0.810), and the optimal route from the starting point (Informatics Engineering Building, Unimal) to the selected shop was 11,793.74 meters, based on node accumulation. The system proved effective in providing accurate recommendations and efficient navigation, assisting users in choosing the best service shop through a single Android application.
PREDIKSI PRODUKSI MINYAK MENTAH KELAPA SAWIT PT. BAKRIE PASAMAN PLANTATION MENGGUNAKAN METODE EXTREME LEARNING MACHINE (STUDI KASUS: DATA 2023-2024, SUMATERA BARAT) Reza Pratama; Dahlan Abdullah; Zara Yunizar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6456

Abstract

The production of crude palm oil (CPO) in Indonesia experiences fluctuations influenced by various factors such as rainfall, number of rainy days, and the quantity of fresh fruit bunches (FFB). This study aims to develop a predictive model for estimating crude palm oil production using the Extreme Learning Machine (ELM) method, applied to production data from PT. Bakrie Pasaman Plantations in West Sumatra. ELM was chosen due to its fast learning capability and high accuracy in non-linear regression tasks. The study utilizes historical production data from the past two years. The research process involves data normalization, model training, testing, and performance evaluation using the Mean Absolute Percentage Error (MAPE). The results show that the developed model achieves a good level of accuracy with a MAPE value of 12.07%, which is considered reliable. The predictive model is also implemented as a web-based application that displays forecast results and comparative graphs between actual and predicted data. It is expected that this system can support more effective and efficient production planning.
PENGEMBANGAN APLIKASI SURVEI ANDROID TERENKRIPSI DENGAN VALIDASI LOKASI UNTUK ASESMEN PSIKOLOGIS: DEVELOPMENT OF AN ENCRYPTED ANDROID SURVEY APPLICATION WITH LOCATION VALIDATION FOR PSYCHOLOGICAL ASSESSMENT Nanda Nan Arif H; Muhammad Fikry; Zara Yunizar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6461

Abstract

Digital data collection in psychological contexts requires systems that are not only efficient but also secure and context-aware. This study develops an Android-based survey application with layered security by integrating GPS-based location validation and AES-128 encryption. The system restricts access to predefined geographic areas, and all user data is encrypted exclusively on the server side (Laravel backend) to ensure confidentiality and integrity. Indoor testing of location validation showed high accuracy with a 50-meter tolerance and an average response time of 50 ms. Encryption was performed in 40–110 ms for data up to 19.7 KB. Communication between the mobile app and the server uses a REST API secured with HTTPS. The application was developed using the Waterfall model, which fits the structured and pre-defined system requirements. This study’s novelty lies in combining real-time location validation and server-side encryption in a single system—an approach often handled separately in prior research. Black-box testing confirmed that the system performs securely and reliably without burdening the device. This solution is suitable for mobile-based psychological assessments in controlled environments such as schools and is adaptable for other services requiring simultaneous data protection and location verification.
IMPLEMENTASI METODE PREFERENCE SELECTION INDEX (PSI) DALAM PEREKRUTAN MITRA KURIR J&T: IMPLEMENTATION OF THE PREFERENCE SELECTION INDEX (PSI) METHOD IN RECRUITING J&T COURIER PARTNERS Alfisyahrin; Zara Yunizar; Hafizh Al Kautsar Aidilof
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6492

Abstract

The recruitment process for courier partners is an important aspect in maintaining the quality of delivery services in logistics companies such as J&T Express. Selecting the right candidate requires an objective and systematic method so that the decisions taken can be accounted for. This study aims to apply the Preference Selection Index (PSI) method to assist the decision-making process in the selection of courier partners. The PSI method is used to evaluate and rank prospective partners based on a number of criteria, including work experience, communication skills, problem-solving skills, discipline, and teamwork skills. This research was conducted at J&T Bireun. The analysis process was carried out through the stages of normalization, calculation of preference deviations, and determination of the final preference index value. The data used amounted to 10 employee candidates with the highest ranking results, namely Ridwan with a score of 8.6, Zikra with a score of 8.55 and Syakir with a score of 8.55. The results of the study show that the PSI method is able to provide objective and efficient selection results, and makes it easier for companies to determine the best courier partner candidates. Thus, this method is worthy of consideration as a tool in a multi-criteria-based recruitment system in the logistics industry.The courier partner recruitment process is one of the important aspects of maintaining the quality of delivery services in logistics companies such as J&T Express. The selection of appropriate candidates requires objective and systematic methods for the decision to be taken accountable. The Preference Selection Index (PSI) method to assist the decision-making process on the selection of courier partners. PSI method is used to evaluate and rank prospective partners based on a number of criteria, including work experience, communication skills, problem solving capabilities, discipline, and teamwork capabilities. This study was conducted on J&T Bireuen. The analysis process is performed through the normalization stage, preference deviation calculation, and the determination of the final preference index value. The data sample used amounted to 10 candidates with the highest ranking results, namely Ridwan with value (8.6), Zikra with value (8.55), and Syakir with value (8.55). Research results in the application of PSI methods for labor selection in the logistics sector, especially in the operational position of courier partners indicate that it is able to provide objective and efficient selection results, and facilitate the company in determining the best courier partner candidates. Thus, this method is worth considering as an alterative tool in a proof-criterion-based recruitment decision support system in the logistics industry.
TINGKAT EFISIENSI PELAYANAN EKSPEDISI DI KOTA LHOKSEUMAWE MENGGUNAKAN METODE DATA ENVELOPMENT ANALYSIS: THE EFFICIENCY LEVEL OF EXPEDITION SERVICES IN LHOKSEUMAWE CITY USING THE DATA ENVELOPMENT ANALYSIS (DEA) METHOD Silvia Nanda; Dahlan Abdullah; Zara Yunizar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6531

Abstract

Lhokseumawe is one of the economic centers in Aceh that has a role in supporting distribution and services. With the development of e-commerce and the trading industry, the need for expedition services is increasing. Improved efficiency in the expedition service section is one way that can be done by the company to always meet customer satisfaction. The study implemented the CCR model Data Envelopment Analysis (DEA) method that aims to measure the efficiency of expedition services. There are four samples of companies: Shopee Express, J&T, JNT, and TIKI. The input variables used include the number of employees, number of vehicles, and operational costs, while the output variables include the number of delivered packages, the number of customers, and the number of timely delivery. The results showed that Shopee Express, J&T and JNE have an efficiency value of 1, which indicates that all three expeditions have utilized the input optimally to produce output. Meanwhile, TIKI has an efficiency value of 0.057, which indicates that it is still far from efficient conditions that require further evaluation to optimize input and output like all three other expeditions. This research not only contributes academically but also recommendations for expedition companies, so it can be the basis for strategic decision making to improve the competitiveness and quality of logistics services at Lhokseumawe.
Human Face Deepfake Detection Using the YOLO Algorithm Sutri Wandani; Zara Yunizar; Rizki Suwanda
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 2 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2026 (In Press)
Publisher : Universitas Malikussaleh

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Abstract

Deepfake technology has emerged as a significant challenge to digital security because it can generate highly realistic manipulated facial images and videos. The rapid spread of deepfake content has increased the risks of identity fraud, misinformation, privacy violations, and various forms of cybercrime. This study proposes an Android-based human face deepfake detection system using the YOLOv8 algorithm. The dataset consisted of authentic facial images collected from Universitas Malikussaleh students and deepfake facial images generated using artificial intelligence techniques. The research methodology included data collection, image preprocessing, annotation using Roboflow, YOLOv8 model training, model evaluation, TensorFlow Lite (TFLite) conversion, and Android application development. Experimental results demonstrated that the proposed model achieved 95% precision and 95% recall in detecting real and manipulated facial images from both images and videos, indicating reliable detection performance. Nevertheless, several limitations remain. The dataset does not fully represent real-world facial variations, including differences in ethnicity, illumination, facial expressions, head poses, and occlusion caused by masks, glasses, or other objects covering facial regions. These limitations may reduce the model's generalization capability when deployed in real-world environments outside the testing dataset. Furthermore, the deepfake dataset only includes several manipulation techniques and has not been evaluated using more recent deepfake generation methods, such as diffusion model-based face swapping or other advanced generative approaches. Consequently, the model's performance may decrease when encountering manipulation techniques that were not included during training. In addition, the evaluation has not comprehensively considered challenging imaging conditions, such as motion blur, image noise, low-bitrate video compression, and quality variations introduced by different mobile device cameras, which may affect the robustness of the proposed deepfake detection system in practical applications.
Co-Authors ,, Iqbal ,, Maulidasari ,, Zulaifani ., Yulisma Agil, Helvina Aidilof, Hafizh Al Kautsar Aidilof, Hafizh Al-Kautsar Aisah, Sri Purwani Alfisyahrin Amelia, Ulva Aminsyah, Ansharulhaq Andra Munandar Arief Fazillah Arif H., Nanda Nan Arnawan Hasibuan Asran Asran Ayu Suningsih Ayunda Putri Bariah, Hairul Bustami Bustami Cindy Rahayu Dahlan Abdullah Devi, Salma Dhyra Gibran Alinda Dr M Rajeswari Elma Fitria Ananda ERNAWITA ERNAWITA Ersa, Nanda Savira Eva Darnila Ezra Sasqia Syahna Fadlisyah Fadlisyah Fadlisyah Fajri, Riyadhul Fajri, Ryadhul Fajriana, Fajriana Fardiansyah, T. Fasdarsyah Fasdarsyah Fatimah Zuhra Fatimah Zuhra Fatimah Zuhra Febi Anriani Fuadi, Wahyu Gilang Wahyu Ramadhan Gilang Hafidh Rafif, Teuku Muhammad Hafiz Al Kautsar Aidilof Hafizh Al Kautsar Aidilof Hamdhana, Defry Harahap, Ilham Taruna Hasan, Phadlin HENDRA ZULKIFLI Herman Fithra Irshad Ahmad Reshi Johan, T. M. Juanda Pratama Kartika Kartika Kurnia Amanda, Destiara Lidya Rosnita M Ishlah Buana Angkasa M. Fauzan M.Cs, Iqbal, Maghfirah Maghfirah Maha, Dedi Torang P Mahara, Sabda Mahendra Febriliansyah Maizuar Maizuar Maryana Maryana Maulana Helmi, Fathan Maulana, O.K.Muhammad Majid Maulida Yani Siregar Melizar Meutia Rahmi Misbahul Jannah Muhammad Daud Muhammad Fatiha Assyfa Muhammad Fauzan Muhammad Fikry Muhammad Ikhwani Muhammad Muhammad Muharni Muharni Mukhlis Mukhlis Mukhlis Mulaesyi, Syibbran Munar, Munar Munirul Ula Mursyidah Mursyidah MUTHMAINNAH Muthmainnah Muthmainnah Nanda Nan Arif H Nazwa Aulia NinaUlfauza Nunsina, Nunsina Nur Mauliza Nura Usrina Nurdin Nurdin Nuryawan, Nuryawan OK Muhammad Majid Maulana Majid Putri, Riska Yolanda Ramadhana Juseva Reza Pratama Ridha, Ridha Rifkial Iqwal Rini Meiyanti Ritonga, Huan Margana Rizal S.Si., M.IT, Rizal Rizal Tjut Adek Rizki Suwanda Rizky Almunadiansyah Rizky Putra Fhonna Rizky, Rahmat Rizkya, Dini Dara Rozzi Kesuma Dinata Rusnani Rusnani Rusniati Rusniati Ruwaida Ruwaida Safwandi Safwandi Said Fadlan Anshari Savira Ersa, Nanda Silvia Nanda Siregar, Winda Ramadhani Sriana, Anis Subhan Hartanto Suci Fitriani, Suci Sujacka Retno Sutri Wandani Syintia, Icut Tarigan, Tasya Amelia Taufiq Taufiq Tejas Shinde Tjut Adek, Rizal Wahyu Fuadi Walad Hidayat Yanti, Winda Yesy Afrillia Zahratul Fitri Zalfie Ardian Zharif Athaya Andarfi Zulnazri Zulsuhendra, Edi