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Fake News Detection using the Random Forest Algorithm Setyadin, Rahmat Dipo; Winasis, Reza Handaru; Triyono, Gandung
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): 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.v14i3.4995

Abstract

Detecting fake news has become increasingly important in the digital era, where false information can spread rapidly and significantly influence public opinion. The dissemination of fake news can lead to public distrust in the media, economic losses, and even social conflict. This study aims to develop an effective fake news detection system using the Random Forest algorithm approach. The dataset used in this research was collected from the official Kominfo website and includes attributes such as title, description, author, date, category, page, news URL, and image URL. The text preprocessing process involves tokenization, stop word removal, text normalization, and feature extraction using Term Frequency and Inverse Document Frequency (TF-IDF) to generate numerical representations of the textual data. The Random Forest model was evaluated using accuracy, precision, recall, and F1-score metrics to assess its effectiveness in detecting fake news. The results show that the model performed exceptionally well, with k-fold cross-validation (k=5) yielding high average accuracy—Random Forest achieved an accuracy of 0.9890.
Design and Construction of Employee Recruitment System Application using Profile Matching Method Mahendra, M. Azmi; Firmansyah, Maulana; Triyono, Gandung
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/xvzgjq78

Abstract

The employee recruitment process is one of the important aspects of human resource management, which ensures a match between company needs and available candidates. This research aims to design an E-Recruitment system based on Profile Matching to improve efficiency and accuracy in the employee selection process at PT XYZ. The research methods used include literature study, observation, and interviews with the HRD team. System development follows the SDLC waterfall model, which includes planning, analysis, design, implementation, and testing stages. In this case study, we use data samples from 5 applicants. For the criteria used, there are 3 criteria, namely administration, interview results, and skills/expertise. The results showed that the developed system was able to automate the selection process, reduce administrative burden, and increase objectivity in candidate selection. In conclusion, the implementation of Profile Matching-based E-Recruitment can optimise the recruitment process, but still needs to be combined with other selection methods to get a more comprehensive picture of candidates.
Peningkatan Literasi Digital dan Keamanan Data Pribadi pada Siswa SMK Triguna 1956 Pebry, Fachry Ajiyanda; Sakti, Dolly Virgian Shaka Yudha; Santika, Reva Ragam; Permana, Iman; Triyono, Gandung
Jurnal Pengabdian kepada Masyarakat TEKNO (JAM-TEKNO) Vol 5 No 1 (2024): Juni 2024
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/jamtekno.v5i1.5892

Abstract

Penggunaan layanan keuangan berbasis teknologi seperti PayLater semakin populer di kalangan masyarakat Indonesia, terutama di kalangan generasi muda. Meskipun menawarkan kemudahan dalam berbelanja, layanan ini membawa resiko terkait privasi dan keamanan data pribadi. Di era digital, literasi digital dan kesadaran akan pentingnya menjaga data pribadi menjadi sangat penting untuk menghindari penyalahgunaan data dan potensi kejahatan finansial. Untuk mengatasi masalah ini, seminar "Dampak PayLater Sebagai Gaya Hidup Instan: Nggak Bahaya Tah?" diadakan di SMK Triguna 1956 dengan tujuan meningkatkan literasi digital dan kesadaran akan privasi dan keamanan data pribadi di kalangan siswa-siswi. Seminar ini dihadiri oleh 20 peserta dari kelas XII dan beberapa guru, serta dihadiri oleh kepala sekolah yang memberikan sambutan. Metode pengabdian masyarakat yang digunakan mencakup analisa kondisi objek mitra, persiapan konsep dan administrasi kerjasama, survey kebutuhan materi pelatihan, pembuatan proposal PKM, pembuatan materi seminar, pelaksanaan kegiatan, evaluasi kegiatan, serta penyusunan laporan dan publikasi kegiatan. Hasil dari seminar menunjukkan bahwa 86% peserta pernah menggunakan layanan PayLater, dan 85% dari mereka menyatakan bahwa materi yang dibahas merupakan pengetahuan baru. Penilaian terhadap kualitas penyampaian materi oleh narasumber juga menunjukkan hasil yang positif, dengan rata-rata skor di atas 4 dari skala 5. Sebagian besar peserta merasa bahwa seminar ini bermanfaat dan ingin diadakan seminar serupa dengan topik yang berbeda di masa mendatang. Kritik dan saran yang diterima akan menjadi masukan berharga untuk perbaikan kegiatan berikutnya.
Selection of Recipients of Excellent Scholarship Educational Assistance using Simple Addictive Weighting Method Rudi Hidayat; Ryan Prasetya; Gandung Triyono
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 2 (2025): MEY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i2.2360

Abstract

The selection of educational assistance recipients is an important process that determines the effectiveness of aid distribution. However, inconsistencies in assessment criteria and less systematic data management often become obstacles in determining the right recipient candidates. This problem results in subjectivity and lack of transparency in the selection process. This study proposes a solution in the form of implementing the Simple Additive Weighting (SAW) method as a multi-criteria-based decision support system. This method is used to process data on prospective recipients with criteria including economic conditions, number of family dependents, written test results, and interviews. The approach used is quantitative descriptive with stages of data collection, criteria weighting, SAW score calculation, and evaluation of results. The results of the study show that the SAW method is able to provide objective and consistent rankings of prospective recipients. Evaluation of real data on scholarship recipients shows an accuracy level of 84.62%, indicating the effectiveness of this method in the selection process. These results indicate that the SAW method can be an effective solution to increase transparency, consistency, and fairness in the educational assistance selection process.
Pemanfaatan LMS Moodle Sebagai Media Pembelajaran Daring Bagi Santri Pondok Pesantren Tahfidzul Qur’an Wahidin Halim Syarif, Achmad; Suryadi, Lis; Triyono, Gandung
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 6 : Juli (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

Abstract

The use of information technology in the world of education is an important need, especially in the context of online learning. The Tahfidzul Qur'an Wahidin Halim Islamic Boarding School faces challenges in organizing effective and structured online learning. This community service activity aims to introduce and implement the Learning Management System (LMS) Moodle as an online learning medium for students. The partner for this activity is the Tahfidzul Qur'an Wahidin Halim Islamic Boarding School with a total of 45 students and 5 teachers involved. The implementation method includes training, technical assistance, and evaluation through questionnaires. The results of the activity showed that 87% of participants stated that the LMS Moodle was very helpful in the online learning process, and 76% of teachers were able to independently upload materials and create discussion forums. This activity shows that the use of the LMS Moodle can increase the effectiveness and interactivity of online learning in the Islamic boarding school environment
Application of Data Mining on Player Statistics for Scouting in Football Triyono, Gandung; Wisanto, Aditya Agus; Fachrurozy, Achmad
CCIT (Creative Communication and Innovative Technology) Journal Vol 19 No 1 (2026): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v19i1.3886

Abstract

The sophistication of today's technology makes the use of data increasingly massive. All digital aspects must have data that is ready to be processed, including in the football industry. The use of data in the football industry is one of them used to record all activities carried out by players to see their performance in the match. Dewa United has a scouting division that is tasked with finding talented players according to the wishes of the head coach. In its search, the scouting division observes the players on the field and also uses raw statistical data to see the player's performance. However, the implementation of these activities still has obstacles as evidenced by the difference between the results of observations and the performance of players when joining the team. To solve this problem, the use of data mining can provide scouting recommendations according to player statistics, making the scouting process effective and efficient. The purpose of this study is to make it easier for the team to search for players according to what is desired, which is obtained is a web-based application that has a scouting recommendation feature based on attributes or players according to choice and detailed descriptions of the selected players..
INTEGRATED AHP-TOPSIS DECISION SYSTEM FOR FAIR STUDENT PERFORMANCE EVALUATION Hafiz, Rahmad; Triyono, Gandung; Assegaf , Noval; Yasmin , Nadia; Effendi , Muhtar
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 4 (2025): September 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i4.4064

Abstract

Giving awards is essential to motivate students; however, selecting outstanding students at the junior high school level is often conducted manually and subjectively, which can lead to unfairness and prolonged processing time. This study develops a Decision Support System (DSS) that integrates the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to support objective and transparent student selection. A quantitative descriptive approach was employed, with data collected through questionnaires, interviews, and documentation at two state junior high schools in Banjarmasin City. Seven assessment criteria were applied: attendance, behavior, uniform neatness, extracurricular participation, academic grades, competition achievements, and disciplinary records. AHP was used to determine the weight of each criterion, while TOPSIS ranked students based on these weights. The web-based system was developed using PHP and MySQL and evaluated using the Technology Acceptance Model (TAM). Results show that academic grades had the highest weight (28.5%), followed by attendance (22.3%) and competition performance (15.2%). The TAM evaluation yielded average scores of 4.32 for Perceived Ease of Use, 4.40 for Perceived Usefulness, 4.15 for Attitudes Towards Use, and 4.28 for Behavioral Intention to Use. The DSS produces accurate rankings, is well-received by users, and offers an efficient, fair, and replicable solution for data-driven educational governance in the digital era.
Diagnosis Dini Demam Berdarah Berdasarkan Data Hematologi Menggunakan Algoritma Machine Learning Nita, Yulia; Sister, Maya Gian; Triyono, Gandung
Jurnal Nasional Teknologi dan Sistem Informasi Vol 11 No 2 (2025): Agustus 2025
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v11i2.2025.185-191

Abstract

Infeksi virus dengue yang dikenal sebagai DBD masih menjadi tantangan serius dalam layanan kesehatan di Indonesia karena sifatnya yang menular dan terus menimbulkan masalah hingga saat ini. Penyebaran DBD yang cepat dan peningkatan angka kejadian memerlukan strategi deteksi dini yang lebih efektif untuk mencegah komplikasi serius. Sayangnya, metode konvensional seperti pemeriksaan NS1, IgM/IgG, dan PCR masih menghadapi keterbatasan dalam ketersediaan serta biaya. Penelitian ini difokuskan pada pengembangan Sistem Pendukung Keputusan (SPK) yang berbasis algoritma Naïve Bayes dengan memanfaatkan data hematologi rutin untuk mengklasifikasikan tingkat risiko infeksi DBD. Dataset yang digunakan berasal dari platform Kaggle dengan 924 data pasien yang telah melalui tahap pembersihan dan normalisasi. Data yang digunakan terdiri dari variabel-variabel seperti usia, gender, tekanan darah, gula darah, suhu tubuh, denyut jantung, dan level risiko. Algoritma Naïve Bayes dipilih untuk membangun model Atas dasar kapasitasnya dalam mengolah data secara optimal dengan asumsi bahwa setiap atribut bersifat independen. Dataset Pembagian data dilakukan ke dalam dua subset, di mana sebagian besar (80%) ditujukan untuk training, dan sisanya (20%) untuk testing. Kinerja model dievaluasi menggunakan metrik seperti akurasi, presisi, recall, serta F1-score. Dari hasil pengujian, model mampu memperoleh tingkat akurasi sebesar 98,03%, dengan performa sangat baik di seluruh kelas risiko, terutama recall sempurna pada kelas risiko tinggi. Hal ini menunjukkan kemampuan model dalam mengidentifikasi kasus-kasus berisiko tinggi tanpa terlewat. Dengan demikian, penelitian ini membuktikan bahwa data hematologi yang sederhana dapat dimanfaatkan secara optimal untuk deteksi dini DBD. Sistem yang dikembangkan berpotensi menjadi alat bantu diagnosis yang cepat, hemat biaya, dan dapat diimplementasikan secara luas untuk mendukung pelayanan kesehatan primer.
Sistem Pendukung Keputusan Dalam Penilaian Kinerja Karyawan Rumah Sakit Menggunakan Metode Multi Factor Evaluation Process Anwarsyah, Anwarsyah; Triyono, Gandung
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4778

Abstract

Employees are a resource that is a supporting factor for a company or organization. Having employees who meet qualification standards can develop the company and increase company productivity. Employee performance assessments are carried out looking at the company's success in organizing employees and determining the level of employee loyalty and professional performance towards the company. Petukangan Hospital has a large number of employees ranging from health workers to management employees and others. Currently there is no system used to evaluate employee performance, so the assessment process takes a long time and is not timely and there is an element of subjectivity in the assessment. Therefore, we need a system that can help assess employee performance with the aim of the research as an alternative in systematically and objectively assessing employee performance according to the weights and criteria obtained by each employee. In this research, the method used is the Multi Factor Evaluation Process of a Decision Support System, where this method carries out an assessment by calculating weights and criteria. The aim of this research is to provide the best solution and tools for Petukangan Hospital in assessing employee performance, and this research is expected to have benefits that can become effective and efficient problem solving. This research has results obtained from testing in the form of a ranking system where employees with the highest total evaluation score is the employee with the best performance score. The calculation results show that the employee with the best performance and rank 1 is Employee 26 with a value of 0.8375.
COMPARISON OF SAW AND TOPSIS METHODS TO DETERMINE THE BEST SERVICE DESK AGENT Suryani; Prasetyo, Angger Totik; Triyono, Gandung
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.1675

Abstract

Pusintek's Service Desk, as a single point of contact, has quite high work demands with many tasks and requests handled. In order to improve the performance of Service Desk agents, the organization can give awards to the best Service Desk agents. However, there are obstacles in selecting the best Service Desk agent because there is still a subjective element in the assessment of Service Desk agents. So that a decision support system is needed that is in accordance with the weight of the organization's assessment criteria. This research proposes an approach in selecting the best Service Desk agent using the Simple Additive Weighting (SAW) method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in processing and ranking agent value data. This research focuses on assessing agents based on key parameters, namely ticket processing time (service response time), agent attendance data, assignment weight and assessment from other coworkers. The number of agents assessed was seventeen. The results of this study obtained the highest value using the SAW method of 2.22 for A1, while the calculation using the TOPSIS method, the highest value on A1 is 0.74 and the accuracy rate using the SAW method is 82.35% while the TOPSIS accuracy is 41.18%..
Co-Authors - Sumardianto Abdurrahman, Faris Nur Achmad Ardiansyah Achmad Solichin Achmad Syarif Adhi, Ajar Parama Aditya Ikhbal Maulana Agus Umar Hamdani Aji Guntoro Al Ghozali, Isnen Hadi Ananda Dian Nugraha Angga Prasetyo Anggita Pamukti Anggraini Ujianti Anwarsyah, Anwarsyah Aris Subagyo, Wismoyo Asep Lukman Arip Hidayat Assegaf , Noval Azizi, Hibatul Chaerul, Muh Coudry Bernadeth Dana Indra Sensuse Daniel Iskandar Dede Wahyu Saputra Dermawan Ginting Devy Fatmawati Dini Astuti Dini Handayani, Dini Djafar, Muhammad Agung A. Djati Kusdiarto Dolly Virgian Shaka Yudha Sakti Dwi Kristanto Dyah Puji Utami Effendi , Muhtar Eliyani, Eliyani Ery Rinaldi Fachrurozy, Achmad Fadel, Muhamad Fahlevi, Noval Fajriah, Riri Febri Maulana Febrianti, Rizkia Saski Feby Lukito Wibowo Firmansyah, Maulana Gilang Ramadhan Hadi rahadian Hafiz, Rahmad Hakim, Sulaiman Hanifa, Annisa Hardjianto, Mardi Helmi Zulqan Hendra Adi Saputra Henny Idam Risnaputra Iman Permana, Iman Indra Indra Jotri Firdani Maharaja Juhari Juhari, Juhari Jumaryadi, Yuwan Kanasfi, Kanasfi Kiki Ari Suwandi kosasih Lestari, Triardani Lis Suryadi Lis Suryadi, Lis Lutfan Lazuardi Luthfi Mawardi Mahendra, M. Azmi Malik Aziz Habibie Maruanaya, Greghar Juan Tjether Maruanaya, Rita Fransina Maskur A, Moch Riyadi Masnuryatie, Masnuryatie Maya Asmita Megananda Hervita P. Melyana, Melyana Mepa Kurniasih MHD. Reza M.I. Pulungan Moch. Rezaf Ivanka Haris Mohammad Aldinugroho Abdullah Muhamad Dikhi Rohman Muttaqin, Zaenul Ningrum, Sekar Ayu Nita, Yulia Nurhikmah, Suci Oktiara, Dara Putri Pebry, Fachry Ajiyanda Pirman, Arif Prasetia, Andika Rohman Prasetyo, Angger Totik Rahmat Hidayat Ramadani, Romi Reza Ariftiarno Ridho Firmansyah Ridho Putra Kusmanda Riki Ramdani Saputra Rima Tamara Aldisa Rinto Prasetyo Adi Rizka Pitriyani Rizky Adhi Saputra Rizky Fernanda Aprianto Rizky Tahara Shita Rojakul, Rojakul Rudi Hartono Rudi Hidayat Ryan Prasetya Safrina Amini Septiadi, Septiadi Setyadin, Rahmat Dipo Sister, Maya Gian Sittah Ifadah Sri Hartati Sri Melati Subekti, Yogi Agung Sudiyatno Yudi Nugroho Sufyan Asaury, Akhmad Suriah Setiana Widiastuti SURYANI Syamsiar, Syamsiar Syarif Hidayatulloh Tansya Ingmukti Taryono, Ono Tunggal Saputra, Tri Aji Umar Alfaruq Umuri, Khairil Utomo Budiyanto Vasthu Imaniar Ivanoti Wahyu Adi Setyo Wibowo Wahyu Cesar, Wahyu Wahyuningram, Nugroho Warih Dwi Cahyo Wawan Gunawan Widyanto, Tetrian Wilsen Grivin Mokodaser Winasis, Reza Handaru Wisanto, Aditya Agus Wisnu Cahyadi Wulan Trisnawati Yasmin , Nadia Yeros Fathullah Achmad Zainal Arifin