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All Journal SAMUDERA Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) INFORMAL: Informatics Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JISKa (Jurnal Informatika Sunan Kalijaga) JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Jurnal Informasi dan Teknologi JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Multica Science and Technology jeti TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi International Journal of Information System & Innovative Technology Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Scientific Journal of Informatics International Journal of Information System and Innovative Technology Smatika Jurnal : STIKI Informatika Jurnal Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Rozzi Kesuma Dinata
Program Studi Teknik Informatika, Unversitas Malikussaleh, Aceh Utara 24351, Indonesia
Religion Agriculture, Biological Sciences & Forestry 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 Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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Public Facility Recommendation System in Subulussalam City Using Fuzzy C-Means Algorithm Berutu, Indah Fachlira; Dinata, Rozzi Kesuma; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.873

Abstract

Subulussalam City, as one of the autonomous regions in Aceh Province, Indonesia, has excellent potential to develop public facilities to improve the quality of life for its residents. Recommendation systems have become an effective solution in helping users find relevant information based on the preferences and needs of the community. This research focuses on developing a recommendation system using the Fuzzy C-Means algorithm. This algorithm is one of the clustering methods capable of handling uncertainty and ambiguity in data. This study aims to develop and analyze a public facility recommendation system in Subulussalam City using the Fuzzy C-Means algorithm. The dataset in this study was obtained from the Youth, Sports, and Tourism Office of Subulussalam City and the results of a research questionnaire. Regarding the names of each public facility, it provides information about the location and various forms of visitor assessments, including evaluations related to accessibility, facilities, costs, environment, and visitor experiences, using a rating scale of 1-5. Based on the testing results, the Fuzzy C-Means clustering algorithm can group facilities based on characteristics and user preferences, resulting in more personalized and relevant recommendations. The data to be clustered is divided into two categories: recommended and not recommended. The study's results using the Fuzzy C-Means algorithm show the final grouping based on the degree of membership from the last iteration of each public facility, with cluster 1 containing 31 locations and cluster 2 containing 31 locations.
Comparison of the Results of the Weighted Moving Average Method and the Least Absolute Shrinkage and Selection Operator Method for Predicting Total Palm Oil Production at PT. Mora Niaga Jaya Ardiansyah, Sakha; Dinata, Rozzi Kesuma; Ar Razi, Ar Razi
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.862

Abstract

This study compares two prediction methods, Weighted Moving Average (WMA) and Least Absolute Shrinkage and Selection Operator (LASSO), in forecasting the total palm oil production at PT. Mora Niaga Jaya. Accurate forecasting is essential in the palm oil industry to support decision-making, optimize production planning, and manage supply chains efficiently. The WMA method produced more realistic prediction results, with a Mean Absolute Error (MAE) of 114,854 tons and a Mean Absolute Percentage Error (MAPE) of 220.45%, despite still having a considerable margin of error. These values suggest that while WMA is not perfectly accurate, it performs moderately well, given the complexity and variability inherent in agricultural production data. On the other hand, the LASSO method yielded significantly worse results, with an extremely high and unrealistic MAE and a MAPE of 291,456.000%, indicating that this approach is unsuitable for palm oil production forecasting in this specific case. The underperformance of the LASSO method may be due to the nature of the data used, which may not meet the assumptions required for LASSO to function optimally, such as linear relationships and minimal noise. This highlights the importance of aligning forecasting methods with the dataset's characteristics. Based on the comparison, it can be concluded that the WMA method is more appropriate for predicting palm oil production than LASSO. However, further steps such as parameter optimization, data normalization, and outlier removal should be undertaken to achieve better predictive accuracy. This research provides valuable insights into the importance of selecting the correct predictive method and ensuring data quality in forecasting. Ultimately, careful model selection and data preprocessing support effective operational and strategic decisions in the palm oil industry.
Classification Of Outpatient Visit Status Walking at Dr. Zubir Mahmud Hospital Using Algoritma C4.5 Fikria, Putri; Dinata, Rozzi Kesuma; afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.865

Abstract

This study aims to classify the status of outpatient visits at RSUD Dr. Zubir Mahmud into three main categories, namely "Very Urgent", "Urgent", and "Not Urgent”, using the C4.5 algorithm. The web-based system uses the PHP programming language and MySQL database to ensure ease of implementation and efficient data management. The classification process is done by setting threshold parameters, calculating entropy, and the gain ratio to form an accurate and reliable decision tree. The results show that the C4.5 algorithm can classify patient visit data with a reasonably high accuracy rate, which is 93.75% for 2022 data and reaches 100% for 2023 data. In 2022 the “Very Urgent" category had 9 True Positives (TP); in 2023, the number remained consistent. However, in both years, there were also False Negatives in the same category, with 4 cases in 2022 and 5 cases in 2023. The "Urgent" and "Not Urgent" categories show suboptimal classification performance due to uneven data distribution, which causes the precision and recall values in these categories low. Model evaluation was conducted using evaluation metrics such as precision, recall, and F1 score. The evaluation results show that the model works very well in identifying high-priority categories, but further development is needed to improve classification in other categories. This system is expected to be a reliable tool in decision-making in health services, especially in determining the priority of patient services appropriately and efficiently. With further development, this system has the potential to be widely applied in various other hospitals.
Comparison of Linear Regression and Polynomial Regression for Predicting Rice Prices in Lhokseumawe City Muhammad Iqbal; Rozzi Kesuma Dinata; Rizki Suwanda
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 3 (2025): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i3.2396

Abstract

Rice is a strategic food commodity in Indonesia, and its price fluctuations significantly impact inflation, economic stability, and poverty levels. Accurate price prediction is, therefore, essential for effective policymaking. The objective of this research is to develop a system for predicting the price of rice in Lhokseumawe City, employing a comparison of the accuracy of linear and polynomial regression models. To this end, daily price data from the Strategic Food Price Information Center (PIHPS) from 2020 to 2024 were utilized, with both models being implemented in Python. The findings indicate that 4th-order polynomial regression exhibited optimal performance, attaining a mean absolute percentage error (MAPE) of 1.85%, a mean absolute error (MAE) of 205.23, and a root mean squared error (RMSE) of 284.88. Conversely, the implementation of linear regression resulted in substantially elevated error metrics, with a mean absolute percentage error (MAPE) of 5.16%, a mean absolute error (MAE) of 553.91, and a root mean square error (RMSE) of 614.14. The findings indicate that 4th-order polynomial regression is a substantially more effective model for predicting rice prices in Lhokseumawe. The latter's superiority suggests that local rice price dynamics are characterized by significant non-linear patterns, rendering it a more robust tool for capturing data volatility and supporting data-driven policy.
Implementation of The Logistic Regression Algorithm to Analyze Poverty Factors in Aceh Province Mursyidah, Mursyidah; Kesuma Dinata, Rozzi; Yunizar, Zara
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9715

Abstract

Aceh Province continues to face a high poverty rate despite its abundant natural resources. This study aims to analyze the factors influencing poverty status in Aceh Province by applying a binary logistic regression algorithm. The research specifically focuses on an inferential analytical approach to reveal significant relationships among socioeconomic variables. Secondary data were obtained from the Aceh Provincial Statistics Agency (Badan Pusat Statistik/BPS) for the period 2019–2023. Inferential analysis was conducted using the entire dataset through the statsmodels library to identify variables that are statistically significant to poverty status. In addition, a classification approach was implemented using scikit-learn, with a data split between training data (2019–2022) and testing data (2023), yielding an accuracy of 0.70, precision of 0.81, recall of 0.70, F1-score of 0.66, and AUC of 0.69. These findings provide empirical evidence that improving access to education and equitable infrastructure development in densely populated areas can serve as effective policy focuses in efforts to alleviate poverty in Aceh Province.
Clustering Coastal Areas Based on Aquaculture Productivity in North Aceh Regency Using K-Means Algorithm Ulfa, Septia Mulya; Dinata, Rozzi Kesuma; Risawandi, Risawandi
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10094

Abstract

This study aims to cluster coastal subdistricts in North Aceh Regency based on the productivity of seven key aquaculture commodities milkfish, vannamei shrimp, tiger shrimp, tilapia, mojarra, grouper, and crab using the K-Means algorithm. The dataset, sourced from 15 coastal subdistricts, was normalized using the Z-Score method. The optimal number of clusters was determined using the Elbow Method, and clustering performance was evaluated with the Silhouette Score, yielding a value of 0.5293, indicating a moderately well-defined structure. The resulting clusters reflect distinct productivity levels: Cluster 0 (low), Cluster 1 (moderate), and Cluster 2 (high). A two-dimensional PCA plot was used to visualize the clusters, showing clear separations among them. These findings offer valuable insights for regional planners and policymakers in developing targeted aquaculture strategies and optimizing resource allocation, particularly for underperforming areas.
Clustering of Aquaculture Productivity Villages in East Aceh Using the K-Means Algorithm Arif, M. Arif Saputra; Dinata, Rozzi Kesuma; Afrillia, Yesy
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10102

Abstract

This study aims to classify villages based on the level of pond utilization and to develop a web-based application for categorizing aquaculture areas in East Aceh Regency. In contrast to traditional definitions based on harvest volume, this research defines productivity functionally—whether the pond area is actively managed or abandoned. The dataset consists of 146 villages and includes five primary variables: number of fish farmers, total pond area, number of pond plots, productive pond area, and abandoned pond area. Clustering was conducted using the K-Means algorithm, resulting in two main groups: productive and non-productive villages. Validation through the Silhouette Score revealed that using k = 2 yielded the highest score of 0.7576, indicating the most optimal clustering structure. The analysis showed that 92% of villages were categorized as productive, while 8% fell into the non-productive cluster. These two clusters differ significantly in terms of land utilization ratios and the number of active aquaculture workers. The findings not only offer a more refined spatial insight but also serve as a basis for the Department of Marine Affairs and Fisheries in formulating aquaculture zoning, revitalization programs, and more targeted resource allocation.
Sosialiasi Manajemen Sistem Notifikasi Keberangkatan Jamaah Haji dan Umrah Secara Online di Kantor Kemenag Lhokseumawe Kesuma Dinata, Rozzi; Sujacka Retno; Novia Hasdyna; T Irfan Fajri; Mutasar
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 4 No. 4 (2023): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN)
Publisher : Lembaga Dongan Dosen

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

Abstract

Currently, at the Ministry of Religious Affairs (Kemenag) office in Lhokseumawe, there is no online notification system available for the departure of Hajj and Umrah pilgrims. In the age of rapid advancements in information technology, the importance of an online notification system is increasing, as it can facilitate the departure process for Hajj and Umrah pilgrims. The objective of this community engagement activity is to provide socialization to the staff in the Hajj and Umrah department at the Ministry of Religious Affairs (Kemenag) in Lhokseumawe. The primary focus is on enhancing their understanding of the online notification system, as part of an ongoing effort to improve the efficiency and transparency in the online departure process for Hajj and Umrah pilgrims at the Kemenag office in Lhokseumawe.
Sosialisasi Peningkatan Pengelolaan dan Efisiensi Sistem Informasi Perpustakaan Kitab di Dayah Darul Ulum Desa Alue Awe Kota Lhokseumawe Hasdyna, Novia; Kesuma Dinata, Rozzi; Retno, Sujacka; Fajri, T Irfan; Mutasar, Mutasar
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 5 No. 2 (2024): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN)
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v5i2.3156

Abstract

Dalam era globalisasi saat ini, teknologi informasi dan komunikasi telah mengalami perkembangan yang pesat. Perpustakaan sebagai lembaga penting dalam menyediakan akses ke pengetahuan dan informasi perlu memanfaatkan teknologi ini dengan tepat guna meningkatkan peranannya dalam masyarakat. Di Dayah Darul Ulum, Desa Alue Awe, Kota Lhokseumawe, Perpustakaan Kitab masih belum terkomputerisasi, sehingga diperlukan sosialisasi tentang pentingnya sistem perpustakaan dan pemanfaatannya secara efektif. Tujuan kegiatan ini adalah untuk meningkatkan layanan kepada pembaca dengan optimal. Melalui pengabdian kepada masyarakat, diharapkan dapat memperoleh masukan yang berguna dalam meningkatkan kualitas layanan, termasuk sumber daya manusia, fasilitas, teknologi, dan manajemen. Perpustakaan saat ini berperan sebagai pusat informasi, pengetahuan, dan layanan jasa lainnya, namun masih terdapat ruang untuk perbaikan yang signifikan. Hasil dari kegiatan pengabdian ini diharapkan dapat memberikan kontribusi yang berarti bagi Dayah Darul Ulum dalam meningkatkan kualitas layanan dengan memanfaatkan sistem informasi perpustakaan kitab.
Pelatihan Dasar Jaringan Komputer bagi Pemula: Membangun Keterampilan Teknologi dari Teori ke Praktik di Kota Langsa Mutasar, Mutasar; Hasdyna, Novia; Yustizar, Yustizar; Muttaqin, Muttaqin; Kesuma Dinata, Rozzi
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 5 No. 4 (2024): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN) Edisi September - Desembe
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v5i4.4293

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan pelatihan dasar jaringan komputer bagi pemula di Kota Langsa, yang difokuskan pada pengaplikasian teori jaringan komputer ke dalam praktik nyata. Pelatihan ini diinisiasi oleh dosen dari beberapa universitas bekerja sama dengan Dinas Pendidikan dan Kebudayaan (Disdikbud) Kota Langsa, dan dilaksanakan pada tanggal 24 Agustus 2024. Metode yang digunakan adalah pendekatan ceramah dan praktik langsung, di mana peserta yang terdiri dari pelajar dan tenaga pendidik, diberikan pemahaman tentang jaringan komputer dasar, perangkat keras dan lunak jaringan, serta diajarkan konfigurasi dan instalasi jaringan sederhana. Evaluasi dilakukan melalui pre-test dan post-test untuk mengukur peningkatan pemahaman peserta. Hasil evaluasi menunjukkan peningkatan signifikan, dengan 85% peserta memahami teori dasar jaringan komputer dan 90% berhasil melakukan instalasi jaringan sederhana secara mandiri. Simpulan dari kegiatan ini menekankan pentingnya kolaborasi antara akademisi dan instansi pemerintah dalam meningkatkan literasi teknologi dan keterampilan digital masyarakat, terutama dalam menghadapi tantangan transformasi digital yang pesat.
Co-Authors ., Yustizar Ahmad Fauzi Abdillah Aidilof, Hafizh Al Kautsar Akbar, Hafizal Akram, Rizalul Alvanof, Mulia Andik Bintoro Annisa Afrilia Zahra Annisa Anya Regina Putri Ar Razi Ar Razi Ar Razi, Ar Razi Ardiansyah, Sakha Arif, M. Arif Saputra Arnawan Hasibuan Asrianda Asrianda Azrai Putra Barumun Daulay Badriana, Badriana Baringin Sianipar Berutu, Indah Fachlira Bustami Bustami Bustami Bustami Bustami Chaeroen Niesa Cut Fadhilah Deffiyani Eva Darnila Fadlisyah Fadlisyah Fadlisyah Fajri, T Irfan Fajriana, Fajriana Fiasari, Fiasari Fikria, Putri Fuadi, Wahyu Gadis Ayu Sofiana Hafizal Akbar Haried Novriando Hasan Tahir Hasmar, Muhammad Al Hafiz Irwanda Syahputra Iswari, Syahyana Jasmin, Nadya Khairul Muttaqin Khairunnisa Khairunnisa Khairunnisa Khairunnisa Lubis, Aulia Azzahra Ma'aruf Maryana Maryana Maryana Melita Saldila Muhammad Al Hafiz Hasmar Muhammad Alif Muhammad Arasyi Muhammad Arrayyan Muhammad Fikry Muhammad Iqbal Muhammad Nurfahmi Muhammad Rivai Muhammad Rizal MUHAMMAD RIZAL Munirul Ula Mursyidah Mursyidah Mutammimul Ula Mutasar Muttaqin Muttaqin Narita Taskia Novia Hasdyna Novianda Novianda Nur Azizah Nurwijayanti Rahmat Hidayat Rahmat Hidayat Rahmatin Nisak Risawandi, Risawandi Rizki Suwanda Rizky Fasya Ramdhani Safwandi Safwandi Safwandi Safwandi Sahputra, Ilham Said Fadlan Anshari Selly Alfika Suci Ramadani Sujacka Retno Sujacka Retno Syatriani Jauhari T Irfan Fajri Tahir, Hasan Ulfa, Septia Mulya Yafis, Balqis Yessy Afrillia Yesy Afrillia Zahratul Fitri Zahratul Fitri Zara Yunizar Zuboili, Zuboili Zulfa Zulfa