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All Journal Jurnal Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) INFORMAL: Informatics Journal Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 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 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) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS)
Sujacka Retno
Universitas Malikussaleh
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Evaluasi model data chatbot dalam natural language processing menggunakan k-nearest neighbor Sujacka Retno; Rozzi Kesuma Dinata; Novia Hasdyna
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4690

Abstract

Chatbot merupakan sebuah aplikasi yang terdapat pada rumpun ilmu Natural Language Processing (NLP) berbasis Artificial Intelligence (AI) atau juga dikenal dengan Kecerdasan Buatan yang dapat mensimulasikan sebuah percakapan antar pengguna layaknya melalui aplikasi SMS, situs website, private chatroom, ataupun melalui aplikasi seluler. Penelitian ini dilakukan di Kota Lhokseumawe dengan membuat sebuah aplikasi chatbot dengan pemodelan data yang diperoleh dari Pemerintah Kota Lhokseumawe. Penelitian ini bertujuan untuk memudahkan para wisatawan ataupun penduduk setempat dalam mencari informasi terkait dengan Kota Lhokseumawe. Pemodelan data yang dibangun dievaluasi dengan menggunakan algoritma K-Nearest Neighbor. Pemodelan data di dalam penelitian ini adalah sebanyak 600 model data yang dievaluasi sebanyak 400 kali pengujian untuk menemukan model terbaik dalam pengunaan model data dari chatbot yang dibangun. Hasil penelitian menunjukkan tingkat akurasi pada pengujian ke 400 adalah sebesar 100% dengan loss rate sebesar 0,0352
Penerapan Metode Nine-Step Kimball Dalam Pengolahan Data History Menggunakan Data Warehouse dan Business Intelligence Said Fadlan Anshari; Sujacka Retno
Jurnal Ilmu Komputer Vol 16 No 1 (2023): JIK Edisi April 2023
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2023.v16.i01.p07

Abstract

Data warehouse dan business intelligence merupakan perpaduan teknologi informasi yang dapat dimanfaatkan oleh banyak perusahaan yang memiliki data histori dan data transaksi yang cukup besar untuk bisa selanjutnya diolah, seperti yang dimiliki oleh beberapa perusahaan waralaba. Dengan menggunakan metode nine-step Kimball sebagai metode pengembangan data warehouse-nya, seta aplikasi Tableau sebagai media visuailsasi dari hasil business intelligence-nya, perusahaan dapat melihat hasil pengolahan data histori dan data transaksi yang telah dihasilkan, yang berkaitan dengan fungsi bisnis penjualan atau transaksi. Hasil pengolahan data ini dapat dimanfaatkan oleh lintas tim dan seluruh stakeholder perusahaan untuk bisa melihat gambaran bisnis yang telah dijalankan, serta membantu untuk mendukung keputusan dalam pengembangan bisnis di waktu yang akan datang. Selain daripada itu, hasil pengolahan data dalam data warehouse ini dapat dimanfaatkan oleh perusahaan untuk diolah lebih lanjut, salah satunya menggunakan metode data mining, yang dapat dimanfaatkan untuk kebutuhan prediksi di masa depan. Kata kunci: data warehouse, business intelligence, nine-step Kimball, Tableau, data mining
Clustering Analysis and Mapping of ISPA Disease Spread Patterns in Bireuen District Mutammimul Ula; Tsania Asha Fadilah Daulay; Richki Hardi; Sujacka Retno; Angga Pratama; Ilham Sahputra
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 3 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i3.4936

Abstract

ISPA disease can be detected by analyzing the regional distribution map of the disease. Early detection of ARI is very important for effective prevention. The study conducted in Bireuen Regency used data from 2019 to 2021, sourced from dr. Fauziah Bireuen Hospital, revealed that there was an increase in ARI cases from an average of 13.18 to 59.24 per year. The aims of the study were to identify ARI clusters, analyze disease patterns using Spatial Pattern Analysis and Flexible Shaped Spatial Scanning Statistics. The methodology involves collecting patient data for each ARI case and processing it using DBSCAN to obtain cluster points on the map. Spatial Pattern Analysis is used to analyze these clusters and identify hotspot points on the map. The analysis resulted in four clusters: Cluster 1 (6 subdistrict), Cluster 2 (4 subdistrict), Cluster 3 (1 subdistrict), and Cluster 4 (6 subdistrict). The study identified 6 hotspots in 2019, 5 hotspots in 2020, and 6 hotspots in 2021. Each ARI disease clustering map shows the distribution of ARI cases and identifies areas prone to the disease. These findings provide valuable insights for targeted interventions and preventive actions in identified high-risk areas of ISPA.
Sistem Pengajuan Cuti Pegawai Berbasis Website Pada Bagian Sekretariat Daerah Kabupaten Bireun Cut Agusniar; Sujacka Retno; Nisa Ul Fadila
Jurnal Minfo Polgan Vol. 12 No. 1 (2023): Artikel Penelitian Juni 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v12i1.12610

Abstract

Cuti merupakan salah satu hak karyawan dan kewajiban yang diberikan instansi unt,uk setiap karyawan memiliki hak mengambil cuti yang dimiliki pada instansi masing-masing tempat mereka bekerja. Sekarang masih banyak instansi yang menangani cutin karyawan bersifat manual. Dalam pengolahan data karyawan selama ini, di Bagian Organisasi SETDAKAB Bireuen menggunakan sistem yang terkomputerisasi secara sederhana yaitu menggunakan Microsoft Oficce Excel, sehingga pada pengolahan data banyak mengalami hambatan seperti terjadinya proses kesalahan yaitu sulitnya dalam mengolah data cuti karena data yang masih manual. Untuk mengatasi masalah tersebut, maka dirancang suatu sistem informasi pengajuan cuti pegawai di Bagian Organisasi SETDAKAB Bireuen menggunakan Bahasa Pemograman PHP dan database MySQL. Menggunakan database dapat mengurangi ruang penyimpanan dan mengurangi terjadinya kehilangan data, sehingga mempercepat proses pembuatan laporan dan rekapan data. Perancangan pada website ini, terdiri dari beberapa tahapan yang meliputi wawancara, pengumpulan data, observasi analisi data kemudian dilanjutkan dengan perancangan website kepegawaian cuti karyawan dengan cara menganalisis dan merancang setiap komponen menggunakan UML. Dengan adanya Sistem Informasi Pengajuan Cuti Pegawai Berbasis Website Pada Bagian Organisasi SETDAKAB Bireuen menjadi suatu sarana media informasi yang dengan mudah untuk mengetahui segala informasi terkait pengajuan cuti dan hak cuti yang dimiliki oleh setiap karyawan. Kata Kunci: Sistem Pengajuan Cuti, Pegawai, Website, UML dan PHP
Z-Score and Floyd Warshall Algorithms for Determining Alternative Routes of Mugging-Prone Areas in Medan City, Indonesia Dinata, Rozzi Kesuma; Bustami, Bustami; Fiasari, Fiasari; Retno, Sujacka
ILKOM Jurnal Ilmiah Vol 15, No 3 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i3.1608.436-444

Abstract

This study analyzes and implements the Floyd Warshall algorithm using Z-Score to track alternative routes to areas in Medan City, Indonesia that are prone to mugging. The data was obtained from Porlestabes (Police station) Medan-Indonesia. This study employed the Z-Score rank method to rank specific values and determine the levels of crime-prone areas. The highest and lowest levels of crime-proneness were identified using the Z-Score method, and the Floyd Warshall Algorithm is used to identify alternative routes to avoid such areas. The language used in this study adheres to objective and formal writing principles, with value-neutral and clear terminology employed throughout.  The results of this analysis showed that out of 99 roads across 18 districts, 4.04% of them were classified as very high prone, 9.09% as high prone, 11.11% as prone, and 75.76% as low prone. The search results from conducting alternative route analysis with the Floyd Warshall algorithm on Perintis Kemerdekaan street indicate the identification of the safest routes.
CLASSIFICATION OF COLOR BLIND STUDENTS AT SMA NEGERI 1 LHOKSEUMAWE USING NAÏVE BAYES ALGORITHM Rozzi Kesuma Dinata; Maryana; Sujacka Retno; Gadis Ayu Sofiana
Multica Science and Technology Vol 3 No 1 (2023): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v3i1.425

Abstract

This research aims to classify students and determine eye conditions with normal and partial color blindness by using Naïve Bayes algorithm. The research dataset was obtained from students at SMA Negeri 1 Lhokseumawe. The variables used in this research were 24 Plate Ishihara Tests with data collection techniques by using interviews, literature studies and questionnaires. Total data in this research are 140 data and divided into 110 training data and 30 testing data. The results showed that from 110 data trained, there were 69 students included in the normal group and 41 students included in the partial group. Then, the 30 testing data were tested into the classification system for color blind students using Naïve Bayes Algorithm. The accuracy level of the test results was 86.67% and 13.33% error.
Analysis of the Topsis in the Recommendation System of PPA Scholarship Recipients at Universitas Islam Kebangsaan Indonesia Hasdyna, Novia; Dinata, Rozzi Kesuma; Retno, Sujacka
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.7051

Abstract

This research implements the TOPSIS method on a recommendation system for Peningkatan Prestasi Akademik (PPA) scholarship recipients. The research data was obtained from the computer and multimedia faculty, UNIKI. The results showed that the TOPSIS method can provide the best alternative based on the highest rank. In this research, the highest rank was obtained from the results for predetermined criteria, namely GPA, achievements, parental dependents and parental income. The highest value obtained is 0.7489. The system built based on a website with the PHP programming language.
Implementation of K-NN Algorithm to classify the Scholarship Recipients of Aceh Carong at Universitas Malikussaleh Yanti, Riski; Retno, Sujacka; Yafis, Balqis
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 1 (2024): Journal of Advanced Computer Knowledge and Algorithms - January 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i1.14534

Abstract

In an effort to increase the efficiency of the scholarship selection process, this research aims to implement the K-Nearest Neighbors (K-NN) algorithm in the classification of scholarship recipients. The research method involves collecting data on scholarship receipts from several previous years based on predetermined criteria such as father's job, mother's job, parent's income, number of parents working, father's last education, and mother's last education. Next, the K-NN algorithm is applied to classify prospective scholarship recipients based on the similarity of their profiles to students who have received previous scholarships. The results of this research indicate that the implementation of the K-NN algorithm in the classification of scholarship admissions at Malikussaleh Aceh Carong University can increase selection accuracy. The experimental results of the accuracy values obtained show that using the K-Nearest Neighbors algorithm with the Euclidean Distance approach and a value of K = 3 produces an algorithm accuracy level of 87.55%. Thus, the K-NN algorithm can be a useful method for scholarship selectors to support more precise and objective decision making.
K-NN with Purity Algorithm to Enhance the Classification of the Air Quality Dataset Retno, Sujacka; Hasdyna, Novia; Yafis, Balqis
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.15890

Abstract

The large number of attributes in a large dataset can cause a decrease in the level of classification accuracy. Attribute reduction can be a solution to improve classification performance, especially in the K-NN algorithm. This research discusses the classification results of K-NN with attribute reduction using Purity. Based on the results of testing carried out on the Air Quality Dataset, the level of accuracy obtained after attribute reduction was 70.71%, while the level of accuracy obtained before attribute reduction was 56.44%, the increase in accuracy obtained from testing this dataset was equal to 14.27%. The proposed Purity method for attribute reduction can increase the accuracy level of the K-NN classification process.
Comparison of Chen's Fuzzy Time Series and Triple Exponential Smoothing in Forecasting Medicine Stocks at the Blang Cut Kuala Community Health Center Devi, Salma; Yunizar, Zara; Retno, Sujacka
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16870

Abstract

Forecasting is estimating future conditions by examining conditions in the past. In social life, everything is uncertain and difficult to predict precisely, so forecasting is needed. Efforts are always made to make forecasts in order to minimize the influence of this uncertainty on a problem. In other words, forecasting aims to obtain forecasts that can minimize forecast errors, which are usually measured by the mean absolute percentage error. This method is usually used for time series-based forecasting and uses data or information from the past as a reference when predicting current data. This research will compare the application of the Fuzzy Time Series Chen method and the Triple Exponential Smoothing method in forecasting drug stock determination at the Kuala Community Health Center, Blang Mangat District, Lhokseumawe City Regency, Aceh. The research results showed that the Triple Exponential Smoothing method was better in forecasting drug stock inventories compared to Chen's Fuzzy Time Series method. Chen's Fuzzy Time Series method produces a MAPE value of 17.67%, which means it has an accuracy of 82.33%, while the Triple Exponential Smoothing method produces a MAPE value of 9.842%, which means it has an accuracy of 90.158%
Co-Authors Abdul Azis Andra Munandar 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 Hayatun Nisa Hidayatsyah Hidayatsyah ilham - sahputra Ilham Sahputra Ilmi Suciani Sinambela 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 Novia Hasdyna Nur Faliza Nurdin Nurdin Panjaitan, Cherlina Helena Purnamasari 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, Safwandi Sahputra, Ilham Said Fadlan Anshari Salsabila, Thifal Sayed Fachrurrazi Selly Alfika Sinambela, Ilmi Suciani Siti Fatimatun Zahro Siti Wahyuni Sudirman Sudirman T Irfan Fajri Taskia, Narita Teuku Zulkarnaen Tsania Asha Fadilah Daulay Utari, Sylva Putri Uzia Ulfa Veri Ilhadi Wahdana, Aldi Wahyu Isnanda Nasution Wibowo, Patmono Yafis, Balqis Yanti, Riski Yesy Afrillia Yopy Anfelia Zara Yunizar Zulfadl, Zulfadl Zulfia , Anni