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All Journal Jurnal Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) INFORMAL: Informatics Journal ITEj (Information Technology Engineering Journals) Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ILKOM Jurnal Ilmiah Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JOISIE (Journal Of Information Systems And Informatics Engineering) INFOKUM Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Multica Science and Technology jeti Jurnal Minfo Polgan (JMP) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Journal of Information Technology (JINTECH) International Journal of Information System & Innovative Technology Jurnal Pengabdian Masyarakat Bangsa Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Gameology and Multimedia Expert International Journal of Information System and Innovative Technology Smatika Jurnal : STIKI Informatika Jurnal Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Sujacka Retno
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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Evaluating The Quality of K-Medoids Clustering on Crime Data in Indonesia Sujacka Retno; Rozzi Kesuma Dinata; Novia Hasdyna
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp274-280

Abstract

This study evaluates the quality of K-Medoids clustering applied to criminal incident data in Indonesia from 2000 to 2023. The analysis compares the clustering performance on both original and normalized datasets using various evaluation metrics, including the Davies-Bouldin Index (DBI), Silhouette Score (SS), Normalized Mutual Information (NMI), Adjusted Rand Index (ARI), and Calinski-Harabasz Index (CH). The findings reveal that the original dataset consistently outperforms the normalized dataset across all metrics. The optimal clustering was achieved in the seventh iteration of the original data, with the lowest DBI (0.438), the highest SS (0.683), NMI (0.916), ARI (0.984), and CHI (57.418). In contrast, the normalized data exhibited higher DBI values and, in some cases, negative Silhouette Scores, indicating less distinct clusters. These results suggest that for this dataset, K-Medoids clustering performs more effectively on the original data without normalization, providing more accurate and well-defined clusters of criminal incidents. This insight is crucial for future research and practical applications in crime data analysis, emphasizing the importance of dataset preprocessing in clustering methodologies.
Implementation of Simple Additive Weighting and Profile Matching Methods to Determine Outstanding Students at Universitas Malikussaleh Nurdin, Nurdin; Fikran, Rifzan; Retno, Sujacka
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4176

Abstract

Decision support system (DSS) is a computer-based system used to support data analysis and decision modeling, with the aim of increasing the effectiveness of decisions taken. In this research, SPK is needed to determine Outstanding Students. Through this research, it is hoped that the selection process for outstanding students can be optimized by choosing the evaluation method that best suits the student's characteristics and institutional goals. The results of this research also have the potential to improve the quality of graduates by providing fairer and more objective awards to those who excel. The aim of this research is to design and implement the concept of the Simple Additive Weighting (SAW) and Profile Matching methods in a system for determining outstanding students at Universitas Malikussaleh and to find out the ranking results of the two methods (SAW and Profile Matching) in selecting outstanding students at Universitas Malikussaleh. The research methodology used was literature study, data collection, Simple Additive Weighting and Profile Matching calculations, application design, testing and evaluation. The results obtained from this research are the application of the SAW and Profile Matching methods to determine outstanding students resulting in preferences with the highest score of 1 for the SAW method and the highest score of 5 for the Profile Matching method. These two methods can be applied in selecting outstanding students to help decision making because both this method produces the same best alternative
PKM Strategi Pemanfaatan Teknologi Informasi untuk Menghadapi Cyberbullying di Kalangan Siswa Retno, Sujacka; Maida, Eka; Fhonna, Rizky Putra; Afrillia, Yesy; Fachrurrazi, Sayed; Yusuf, Edi
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 9 (2025): November
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i9.3469

Abstract

Perkembangan teknologi informasi membawa dampak positif terhadap kemajuan pendidikan, namun di sisi lain juga menimbulkan fenomena negatif seperti cyberbullying yang semakin marak di kalangan siswa. Cyberbullying sebagai bentuk kekerasan psikologis berbasis digital dapat mengganggu kesehatan mental, motivasi belajar, hingga prestasi akademik peserta didik. Pengabdian ini bertujuan untuk menganalisis strategi pemanfaatan teknologi informasi dalam mengidentifikasi, mencegah, dan menanggulangi cyberbullying di lingkungan sekolah melalui integrasi pendekatan teknologi dan edukatif. Metode pengabdian yang digunakan adalah studi literatur dengan mengkaji hasil pengabdian terdahulu, jurnal terakreditasi, serta laporan lembaga pendidikan nasional maupun internasional. Hasil kajian menunjukkan bahwa pemanfaatan artificial intelligence (AI) untuk deteksi ujaran kebencian, penggunaan learning management system (LMS) yang dilengkapi fitur pelaporan anonim, serta penerapan sistem pengawasan berbasis machine learning dapat membantu mengurangi insiden cyberbullying. Namun, efektivitas teknologi tersebut sangat bergantung pada kesadaran etika digital dan kemampuan literasi siber siswa. Oleh karena itu, kolaborasi antara sekolah, guru, dan orang tua dalam memberikan edukasi literasi digital menjadi aspek krusial. Sinergi antara inovasi teknologi dan program pendidikan karakter mampu membangun lingkungan digital yang aman, inklusif, dan mendukung kesejahteraan psikologis siswa.
A Web-Based Decision Support System Implementation for Evaluating Premier Smartphone Brands Using Weighted Product Method Novia Hasdyna; Rozzi Kesuma Dinata; Sujacka Retno
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 02 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i02.939

Abstract

In the current modern era, smartphones have become an indispensable part of daily life, extensively utilized across a multitude of activities, particularly through online platforms. This underscores the imperative of aiding individuals in making precise decisions regarding the smartphone that aligns most with their needs. To address this exigency, the development of a Decision Support System (DSS) employing the Weighted Product method assumes paramount significance in this research. This DSS empowers users to select the most fitting smartphone by assigning weight values to various performance metrics. The criteria used in this research are price, RAM, ROM, battery capacity, and Android version. The successful implementation of this system streamlines the smartphone selection process, enabling users to make judicious choices that perfectly cater to their requirements while optimizing performance metrics.. In this research, Poco X3 Pro has the highest Vector V value of 0.255441, making it the best-recommended smartphone.
Sistem Informasi Pelayanan Cuti Berbasis Web Pada PT Pupuk Iskandar Muda Menggunakan PHP dan MySQL Retno, Sujacka; Rosnita, Lidya; Anshari, Said Fadlan
TECHSI - Jurnal Teknik Informatika Vol. 14 No. 1 (2023)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v14i1.12076

Abstract

Pada era-globalisasi ini teknologi informasi menjadi alat dasar yang dibutuhkan oleh setiap perusahaan yang ada. Dengan menggunakan teknologi informasi keakuratan dan kecepatan akses data akan lebih mudah di jalankan. PT Pupuk Iskandar Muda merupakan pabrik pupuk urea ke-11 di Indonesia dan pabrik ke-2 di Provinsi Aceh. Proses pengelolaan cuti pada PT Pupuk Iskandar Muda saat ini masih dilakukan secara manual. Proses pengelolaan cuti tersebut memiliki beberapa kelemahan. Karyawan tidak bisa mengetahui sisa hak cuti pribadi dan pengambilan cuti oleh rekan kerja secara langsung, sehingga karyawan tidak bisa melakukan manajemen cuti dengan baik.Pimpinan juga belum dapat mengambil keputusan cuti berdasarkan prinsip pemerataan hak cuti karyawan. Kelemahan yang lain adalah proses pengurusan cuti karyawan kurang efektif dan efesien. Dalam menyelesaikan masalah tersebut, penulis merancang sebuah sistem dengan menggunakan pemodelan ERD dan DFD, Personal Home Page (PHP) dan menggunakan basis data MySQL. Dengan adanya sistem pelayanan cuti di PT Pupuk Iskandar Muda ini, karyawan akan bisa lebih mudah untuk mengakses masalah percutian.
Comparison of the Results of Double Exponential Smoothing Method with Triple Exponential Smoothing for Predicting Chili Prices Nadia Saphira; Munirul Ula; 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

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

Abstract

Double Exponential Smoothing (DES) is a forecasting method that combines two components level and trend, used for data with a trend pattern that tends to increase or decrease over time. In contrast, Triple Exponential Smoothing (TES) incorporates three components: level, trend, and seasonality, making it suitable for data with trend and seasonal patterns. This study uses historical chili price data from 2020 to 2023, obtained from the Bank Indonesia website, managed by the National Strategic Food Price Information Center (PIHPS), to compare the effectiveness of DES and TES in predicting chili prices in Medan City. Prediction accuracy was evaluated using MAPE (Mean Absolute Percentage Error) and MAE (Mean Absolute Error). The study results show MAPE values for DES as follows: Large Red Chili 1.25%, Curly Red Chili 1.39%, Green Bird’s Eye Chili 1.14%, and Red Bird’s Eye Chili 1.13%. TES produced slightly lower MAPE values: Large Red Chili 1.25%, Curly Red Chili 1.38%, Green Bird’s Eye Chili 1.12%, and Red Bird’s Eye Chili 1.10%. The MAE values for DES are as follows: Large Red Chili 447.9, Curly Red Chili 494.83, Green Bird’s Eye Chili 430.92, and Red Bird’s Eye Chili 423.36. TES showed better accuracy with MAE values of Large Red Chili at 447, Curly Red Chili at 493.02, Green Bird’s Eye Chili at 416.2, and Red Bird’s Eye Chili at 409.36. The results conclude that Triple Exponential Smoothing performs better than Double Exponential Smoothing in predicting chili prices.
Predictive Analysis of Retail Promotion Strategies in the Context of Consumer Shopping Behavior Ima Pratiwi; Muhammad Fikry; 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

In this paper, we examine the impact of various promotional strategies on consumer shopping interest, focusing on the Alfamart retail chain in Lhokseumawe City, Indonesia, which saw rapid expansion from five to fifteen stores between 2017 and 2023. Despite this growth, expected sales increases have not been met, raising concerns about the effectiveness of current promotional tactics. Utilizing multiple linear regression analysis, we investigate the influence of three specific strategies, Promo Spesial Mingguan, Serba Gratis, and Tebus Murah on shopping interest across the 15 stores. Findings reveal that Tebus Murah is the most effective strategy in boosting shopping interest, showing the smallest error margin between predictive and actual sales figures. This study provides comprehensive insights into the broader effects of promotional strategies on consumer interest, highlighting the need for Alfamart to focus on optimizing the Discounted Redemption approach to maximize sales. The predictive system developed serves as a strategic tool for identifying effective promotions, forecasting sales, calculating return on investment, and analyzing consumer behavior. Our results underscore the value of predictive analysis in refining promotional strategies, enabling Alfamart to adopt a more targeted and efficient marketing approach to enhance sales performance.
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.
Enhancing Academic Security with RFID-Based Smart Locks and Real-Time Attendance Tracking System Muhammad Al Imran; Muhammad Fikry; 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

In this study, we propose a novel RFID-based smart lock system integrated with real-time attendance tracking to enhance academic security. Traditional security methods such as mechanical locks and manual attendance systems are prone to various limitations, including lost keys, falsification, and lack of automatic tracking. Our system utilizes E-KTP cards as RFID identification tools, supported by Internet of Things (IoT) technology, to provide automated door access and efficient attendance monitoring. The implementation results demonstrate a high accuracy rate of 99.5% in reading E-KTP cards, with an average response time of 850 Ms and a 99.5% uptime during a 30-day testing period. The system can handle up to 40 access requests per minute during peak hours. Additionally, it reduces access time by 91%, lowers errors from 5% to 0.2%, cuts operational costs by 60%, and decreases maintenance time by 75%. Security is reinforced through dual encryption using the Vigenère and Bcrypt algorithms, ensuring no security breaches over six months. The dashboard provides real-time monitoring, and the automated attendance system reduces human error, integrating seamlessly with academic databases for user verification and schedule management. This research demonstrates the effectiveness of RFID and IoT technologies in modernizing and securing academic environments.
Identification of Environmental Security in Relation to Crime Rates in Simeulue Regency Using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Method Yopy Anfelia; Munirul Ula; 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

Criminal offenses are acts that violate criminal law and are punishable by the state, either through imprisonment, fines, or other sanctions. These offenses cause significant distress and harm to the general public, individuals, and the state. In Simeulue Regency, the number of criminal cases has been increasing annually, driven by social, economic, environmental, cultural, legal, technological, and psychological factors. This study aims to analyze the relationship between environmental security and the level of criminal cases in Simeulue Regency using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The data used includes criminal cases from 2019 to 2023 across 10 districts, along with environmental information such as population density, public facilities, and socioeconomic indicators. The research methodology involves data collection and cleaning, Euclidean distance calculation, parameter selection for DBSCAN, and the application of validation formulas to determine the vulnerability to criminal offenses in Simeulue Regency. The analysis results, using an epsilon parameter of 5 and MinPts of 3, yielded clusters 0, -1, and 1. Cluster 0 includes Salang and Teluk Dalam districts; cluster -1 includes Alafan, Simeulue Tengah, Simeulue Timur, Simeulue Barat, Teupah Barat, and Teupah Selatan districts; and cluster 1 includes Simeulue Cut and Teupah Tengah districts. The validation formula indicates that the highly vulnerable area is in Simeulue Timur district, while the at-risk areas are Teupah Tengah, Teluk Dalam, and Teupah Barat districts. The areas classified as not at risk are Alafan, Salang, Simeulue Tengah, Simeulue Cut, Simeulue Barat, and Teupah Selatan districts. This study provides insights into areas that require increased attention in efforts to address and prevent criminal offenses. Keywords: environmental security, criminal offenses, DBSCAN, clustering, Simeulue Regency
Co-Authors Abdul Azis Alfika, Selly Angga Pratama Ardi Wirya Indarto Asmaul Husna Asrianda Asrianda Aulia, Faizul Azrai Putra Barumun Daulay Bustami Bustami Bustami Cut Agusniar Devi, Salma EDI YUSUF, EDI Fadlisyah Fadlisyah Fahrizal, Effan Fajri, T Irfan Fiasari, Fiasari Fikran, Rifzan Fortilla, Zeny Arsya Gadis Ayu Sofiana Gilang Wahyu Ramadhan Gilang Hakimi, Musawer Haried Novriando Hidayatsyah Hidayatsyah ilham - sahputra Ilham Sahputra Ima Pratiwi Irvan Na’syakban Lidya Rosnita Lubis, Syahrul Andika Maghfirah, Riezka Mahsa, Masithah Maida, Eka Maryana Maryana Maryana Maryana Maryana, Maryana Muhammad Al Imran Muhammad Daud Muhammad Fikry Muhammad Ikhwanus Muhammad Nurfahmi Muhammad, Muhammad Munirul Ula Mutammimul Ula Mutasar Nadia Saphira Nasrul ZA, Nasrul Nisa Ul Fadila Nisa, Hayatun Novia Hasdyna Nur Faliza Nurdin Nurdin Panjaitan, Cherlina Helena Purnamasari Putra Barumun Daulay, Azrai Rahma Fitria, Rahma Reza Pahlevi Ginting Richki Hardi Rijal, Himmatur Rini Meiyanti Rizky Putra Fhonna Rizkya, Dini Dara Rozzi Kesuma Dinata Safriandi, Safriandi Safwandi Safwandi, Safwandi Sahputra, Ilham Said Fadlan Anshari Salsabila, Thifal Sayed Fachrurrazi Sinambela, Ilmi Suciani Siti Fatimatun Zahro Siti Wahyuni Sudirman Sudirman T Irfan Fajri Taskia, Narita Teuku Zulkarnaen Tsania Asha Fadilah Daulay Utari, Sylva Putri Veri Ilhadi Wahdana, Aldi Wahyu Isnanda Nasution Wibowo, Patmono Yafis, Balqis Yanti, Riski Yesy Afrillia Yopy Anfelia Zara Yunizar Zulfadl, Zulfadl Zulfia , Anni