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All Journal Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi JURTEKSI Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Media Informatika International Journal of Public Health Excellence (IJPHE) Internet of Things and Artificial Intelligence Journal International Journal of Community Service (IJCS) Jurnal Manajemen Informatika dan Bisnis Digital COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi International Journal of Health, Engineering and Technology Journal of Innovative and Creativity Sevaka: Hasil Kegiatan Layanan Masyarakat Jurnal Pengabdian Pada Masyarakat IPTEKS
Riszki Fadillah
Institut Teknologi Dan Kesehatan Ika Bina
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Penerapan Metode Simple Multi-Attribute Rating Technique untuk Pemilihan Lokasi Kos Terbaik di Kawasan UIN Suska Riau Riszki Fadillah; Putri Anglenia; Astia Weni Syaputri; Mustakim Mustakim
Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Vol 5, No 1 (2019): Februari
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/rmsi.v5i1.7377

Abstract

Information needs against boarding houses and the current location are important, to find the location of the boarding houses that fit the desires and confused to its decision because of the many boarding houses that are available. This research will be conducted on the application of the method of a decision support system to select the location of the area's finest boarding houses UIN Suska Riau using a few street names as alternative and criteria that have been tailored to their needs. To help someone chose the location of the boarding houses, then built the expected decision support systems can help a person to choose the location of the boarding houses. The methods used in decision support system is a method of Simple Multi-Attribute Rating Technique (SMART) to select or specify the location of the boarding houses the best there is in the region of UIN Suska Riau. From the results of the completion of a method using SMART obtained the rank of 20 alternatives with rank one in the street Mustamindo with a value of utilities 0.64, in the alley of Iman value utilities is 0.63, and so on until the 20th rank. After the implemented decision support system, further Testing is performed by using the user Acceptance Testing results obtained then the average response i.e. 97%, in accordance with the reality of the expected response. Kata kunci: Boarding House, Decision Support System, Simple Multi-Attribute Rating Technique, SMART.
COUNSELING MODEL BASED ON BACKWARD CHAINING OF STUDENT BEHAVIOR AT SMK 10 MUHAMMADIYAH KISARAN Muhammad Amin; Boby Supriyanto; Muhammad Abyanda Tamaza; Ilham Asy’ari; Riszki Fadillah
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 1 (2023): Desember 2023
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2811

Abstract

Student development includes conduct as a key component. Student behavior becomes crucial in deciding how successful students will be in different spheres of life. The variety of student behavior can hinder the learning process and personal development of students. Through the development of an expert system-based counseling model based on backward chaining, this study seeks to discover trends in student behavior. The research process starts with problem analysis, goal setting, literature study, data collection, system design and implementation, and results analysis. It then moves on to counseling model development and implementation in the school setting. To determine the reasons for the unruly behavior of the kids, data were analyzed using a backward chaining methodology. UML Usecase diagrams are used in system design to define the roles of actors and users. The established counseling model, which consists of 14 behaviors, 67 phenomena/symptoms, and 14 rules, focuses on goals and methods to modify student behavior. Three students underwent system testing based on previously achieved goals from therapy. The findings revealed "Smoking," "Emotional Problems," and "Fighting" among the student behaviors. When the Backward Chaining-based counseling model is used, it is simpler for homeroom teachers to gather information about students' conduct from them and to offer remedies based on the transfer of professional knowledge without having to wait for the counselor guidance procedure
Implementasi Data Mining untuk Pemetaan Persebaran Infeksi Human Imunodeficiency Virus di Provinsi Riau Fadillah, Riszki; Sarjon Defit; Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): 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.v5i1.6712

Abstract

Based on data released by the Riau Provincial Health Service until October 2022, there were 8034 people living with HIV/AIDS (PLWHA), of which 3,711 were in the AIDS stage. Human Immunodeficiency Virus is a virus that attacks the body's immune system, while Acquired ImmunoDeficiency Syndrome (AIDS) is a collection of diseases caused by the HIV virus due to damage to the immune system in humans, resulting in the body being susceptible to potential diseases. This research aims to map the spread of HIV/AIDS in Riau Province to prevent and control the spread of the HIV/AIDS virus by the relevant agencies. The method used in this research is Fuzzy C-Means to carry out clustering in districts/cities which will then be visualized using a map or with a Geography Informatics System (GIS). The Fuzzy C-Means method is a data grouping technique that uses the existence of each data point in A cluster as determined by the degree of membership. The output from Fuzzy C-Means is a series of cluster centers and several degrees of membership for each data point. The data used in this research is HIV/AIDS data in Riau Province from 1997 to 2023. Based on the results of the tests that have been carried out, the results obtained are 3 clusters, namely the safe zone has 5 districts/cities, the alert zone has 5 districts/cities, and There are 2 districts/cities in the dangerous zone. There needs to be treatment through the Health Service, the AIDS Control Commission, and related Non-Governmental Organizations (NGOs) to prevent and control HIV/AIDS in Riau Province for areas that have a high potential for the spread of HIV/AIDS. The tests that have been carried out obtain a minimum error value of 0.008251 in the 8th iteration with the performance of Fuzzy C-Means being 13.271 in the distance between clusters.
Selection of Head of Study Program using Weighted Aggregated Sum Product Assessment (WASPAS) method Ramadani, Ramadani; Fadillah, Riszki; Fitriyani, Intan Nur
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i3.803

Abstract

Selecting a Head of Study Program is a crucial strategic decision in education, particularly in Vocational High Schools. At the Software Engineering Study Program Vocational School Sitibanun Sigambal, Labuhanbatu, Rantau Prapat, this process becomes highly complex due to the involvement of various criteria, such as Psychotest Scores, IQ Tests, Communication Skills, Cognitive Tests, and Teaching Experience. The Weighted Aggregated Sum Product Assessment (WASPAS) method, which combines the Weighted Sum Model (WSM) and Weighted Product Model (WPM), is utilized to enhance the accuracy and efficiency of decision-making. This method enables a more objective and structured selection process by leveraging information technology. Based on implementing the Decision Support System (DSS) using the WASPAS method, it can be concluded that it is highly effective in determining the best Head of Study Program rankings, considering the complex criteria and the need for accurate decisions. This DSS facilitates the selection process with results that are more objective, transparent, and aligned with the School's needs and priorities, thus aiding in achieving the School's mission of providing high-quality education.
Addict Coffee Barista Recruitment Decision Support System Using the ARAS Method Mesran, Mesran; Fadillah, Riszki; Wahyu, Riski Ferita
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6249

Abstract

Barista is a person who works in a coffee shop as a delicious coffee maker. So it is necessary to recruit baristas who can work in coffee shops and have responsibilities that not only mix coffee but also have skills in processing coffee beans. The problem in the barista recruitment process is the process of determining barista candidates who are only selected individually so that it is less accurate to get barista candidates who have the expected skills so that it can have an impact on opinions on the coffee shop. So the solution is provided through a decision support system, a highly interactive computer-based system that assists in making a decision to utilise data and models in solving unstructured and semi-structured problems. The method used in making these decisions is the Additive Ratio Assessment Method (ARAS). A total of 11 people who will become data samples and five criteria are used as rules for assessing (selecting). The ARAS method is able to provide maximum results to obtain superior barista recruitment with a result of 5,342, namely A1 as the selected alternative in barista recruitment after going through the method application stage.
Edukasi Tentang Pemanfaatan Internet dan Teknologi Internet Of Things (IoT) di Kelurahan Padang Matinggi, Kecamatan Rantau Utara Riszki Fadillah; Intan Nur Fitriyani
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 1 (2025): Februari : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i1.311

Abstract

The utilization of internet technology and the Internet of Things (IoT) has become an integral part of various aspects of modern life, including the development of Community Social Worker (PSM) cadres' capacity. This study aims to provide education on the use of the internet and IoT to PSM cadres in Padang Matinggi Village, Rantau Utara Subdistrict, so they can optimize these technologies in supporting their social work activities. This community service activity is carried out through counseling and training that covers the basics of internet usage, the introduction of IoT concepts, and their application in social data management and community activities. The results of this activity showed a significant improvement in the participants' understanding of the technology provided, measured through pre-test and post-test evaluations. With a better understanding of technology, it is expected that PSM cadres can be more effective in performing their duties and contribute to improving the welfare of the community in Padang Matinggi Village.
Penerapan Metode K-Means Clustering untuk Klasifikasi Efek Samping Penggunaan Obat ARV pada Pasien HIV di Puskesmas Fadillah, Riszki; Fitriyani, Intan Nur
Jurnal Media Informatika Vol. 6 No. 1 (2024): Jurnal Media Informatika Edisi September - Desember
Publisher : Lembaga Dongan Dosen

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

Abstract

Pola efek samping yang dialami pasien HIV yang menjalani terapi antiretroviral (ARV) menggunakan metode K-Means Clustering. Data yang digunakan berasal dari rekam medis pasien di puskesmas, yang mencakup informasi tentang usia pasien, jenis efek samping, durasi terapi ARV, dan pola penggunaan obat ARV. Metode Elbow dan Silhouette Score digunakan untuk menentukan jumlah cluster optimal, yang menghasilkan tiga cluster dengan tingkat pemisahan yang baik. Cluster pertama mencakup pasien dengan efek samping ringan dan durasi terapi pendek (kurang dari 6 bulan), cluster kedua berisi pasien dengan efek samping sedang dan durasi terapi menengah (6-12 bulan), sementara cluster ketiga meliputi pasien dengan efek samping berat dan durasi terapi lebih panjang (>12 bulan). Hasil clustering ini memberikan wawasan penting untuk perencanaan intervensi medis yang lebih tepat sasaran, seperti pemantauan rutin untuk cluster 1, pendekatan khusus untuk cluster 2, dan perhatian medis intensif untuk cluster 3. Visualisasi data dengan scatter plot mengilustrasikan hubungan antara keparahan efek samping dan durasi terapi, memudahkan pemahaman tentang pola distribusi pasien yang mengalami efek samping ARV. Temuan ini diharapkan dapat meningkatkan kualitas perawatan dan kepatuhan pasien terhadap terapi ARV.
Penerapan Naive Bayes untuk Identifikasi Keterlambatan Perkembangan Anak Berdasarkan Data Kesehatan pada Program Studi Kebidanan Sirait, Fahruzi; Sakti Tanjung, Rani Darma; Tusakdiyah Harahap, Halimah; Fadillah, Riszki
Jurnal Media Informatika Vol. 6 No. 1 (2024): Jurnal Media Informatika Edisi September - Desember
Publisher : Lembaga Dongan Dosen

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

Abstract

Penelitian ini berfokus pada pemantauan perkembangan anak, yang merupakan aspek penting dalam kesehatan anak, terutama pada masa emas (golden period) perkembangan. Keterlambatan perkembangan anak sering kali tidak terdeteksi secara dini, yang dapat berdampak negatif pada kualitas hidup mereka di masa depan. Penelitian ini bertujuan untuk mengeksplorasi penerapan metode Naive Bayes dalam mengidentifikasi keterlambatan perkembangan anak berdasarkan data kesehatan yang tersedia. Dengan menggunakan pendekatan kuantitatif dan eksperimen, penelitian ini menganalisis data dari rekam medis, hasil pemeriksaan kebidanan, serta informasi tambahan dari orang tua. Metode Naive Bayes dipilih karena kemampuannya dalam mengolah data besar dan memberikan klasifikasi yang akurat dengan cepat. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes dapat digunakan untuk mengklasifikasikan status perkembangan anak ke dalam kategori normal atau terlambat dengan tingkat akurasi yang tinggi. Dengan memanfaatkan sistem informasi kesehatan, tenaga medis dapat lebih mudah mengakses dan menganalisis data kesehatan anak, sehingga memungkinkan deteksi dini terhadap keterlambatan perkembangan. Penelitian ini diharapkan dapat memberikan kontribusi signifikan dalam meningkatkan efektivitas pemantauan kesehatan anak dan mendukung intervensi yang tepat waktu. Selain itu, temuan ini juga membuka peluang untuk pengembangan lebih lanjut dalam penerapan teknologi informasi di bidang kebidanan dan kesehatan anak, dengan fokus pada peningkatan kualitas layanan kesehatan secara keseluruhan
Sentiment Analysis on Twitter Social Media towards Najwa Shihab Using Naïve Bayes Algorithm and Support Vector Machine (SVM) Fahruzi Sirait; Desi Irpan; Riszki Fadillah; Rizalina Rizalina; Riswan Syahputra Damanik
International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i1.280

Abstract

With the rapid growth of digital technology, social media has become a key platform for sharing information and opinions. Twitter, one of the most popular platforms in Indonesia, enables users to interact directly with public figures such as Najwa Shihab. This study aims to analyze public sentiment toward Najwa Shihab on Twitter using sentiment analysis, specifically employing the Naïve Bayes and Support Vector Machine (SVM) algorithms. Sentiment analysis is essential to understanding public opinion, as it classifies text into categories like positive, negative, or neutral, providing valuable insights into societal perspectives on public figures. In this study, 10,000 tweets related to Najwa Shihab were collected from January 1, 2023, to January 31, 2023. Data preprocessing steps such as data cleaning, tokenization, stopwords removal, and filtering were conducted to ensure high-quality data for analysis. The Naïve Bayes and SVM algorithms were applied using RapidMiner to classify the sentiment of the tweets. The performance of both algorithms was evaluated based on accuracy, precision, recall, and F1-score.The results revealed that SVM outperformed Naïve Bayes in all metrics, demonstrating its superior ability to classify sentiments correctly. The sentiment distribution indicated a majority of positive opinions toward Najwa Shihab, with fluctuations in negative sentiment during specific events. This study provides insights into public sentiment analysis and contributes to understanding social media opinions on public figures.
Analysis of Factors Causing Students' Failure to Complete Their Thesis on Time Using the Random Forest Algorithm Riszki Fadillah; Intan Nur Fitriyani; Nur Indah Nasution; Rahadatul 'Aisy Riadi; Dinda Salsabila Ritonga
International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i1.281

Abstract

This research aims to analyze the factors that influence students' delays in completing final assignments using the Random Forest algorithm. The data used includes variables such as GPA, number of credits, employment status, frequency of guidance, organizational activities, and personal motivation. These variables were analyzed to determine their effect on students' ability to complete their final assignments on time. The Random Forest model is applied to predict whether students complete their final assignments on time or not. The model results show an accuracy of 63.33%, with the frequency of guidance and personal motivation being the most influential factors in completing the final assignment on time. Followed by the number of credits and GPA, which also have a significant but smaller influence. Organizational activity factors and employment status have a lower contribution to tardiness, but are still relevant in the context of student time management. Based on these results, research suggests the importance of academic guidance support and motivation management to help students overcome obstacles in completing their final assignments on time. This research, which uses the case of ITKES Ika Bina students, is expected to provide recommendations for universities in improving the academic mentoring process to support student graduation.
Co-Authors Adawiyah, Quratih Al Ghazali, Baginda Restu Astia Weni Syaputri Asy’ari, Ilham Atika Sadariah Nasution Baginda Restu Al Ghazali Boby Supriyanto Chairul Huda D, Novica Jolyarni Desi Irfan Desi Irpan Dinda Salsabila Ritonga Fahruzi Sirait Hazlita Ilham Asy’ari Intan Nur Fitriyani Mardivta, Hafizhah Mesran, Mesran Muhammad Abyanda Tamaza Muhammad Amin Muhammad Amin Mustakim Mustakim Nabila Keysa Erianti Nur Indah Nasution Purwanto, Juni Putri Anglenia Putri Ramadani Rahadatul 'Aisy Riadi Ramadani, Ramadani Rani Darma Sakti Tanjung RINA ANGGRAINI Riswan Syahputra Damanik Riyan Agus Faisal Rizalina Rizalina Sarjon Defit Sentosa Pohan Sirait, Fahruzi Suerni Suerni, Suerni Sumijan Supriyanto, Boby Tamaza, Muhammad Abyanda Tanjung, Rani Darma Sakti Tusakdiyah Harahap, Halimah Tusakdiyah, Halimah Wahyu, Riski Ferita Yusril Iza Mahendra Hasibuan