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Triyono, Gandung
Universitas Budi Luhur
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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.
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.
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%..
APPLICATION OF ENSEMBLE METHOD FOR EMPLOYEE TURNOVER PREDICTIONS IN FINANCIAL SERVICES COMPANY Fadel, Muhamad; Kanasfi, Kanasfi; Arifin, Zainal; Triyono, Gandung
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.1871

Abstract

High employee turnover is a challenge for every company, considering that employees are a valuable asset for the company. A high employee turnover rate indicates the high frequency of employees leaving a company. This will harm the company in terms of time, costs, human resources, and reduce the company's reputation. Low employee turnover is an objective for every company in its efforts to achieve its vision and mission, the employee turnover rate is high at 78.97% at PT. HCI operating in the financial services sector can have a negative impact on the company's reputation. Therefore, there is a need to analyze and predict employee turnover so that company management can take preventive and persuasive actions so as to reduce employee turnover rates. Therefore, a tool is needed to predict whether an employee will leave the company. This paper aims to predict the possibility of employees out of the company using the ensemble method, which is a method that uses a combination of several algorithms consisting of base learners and individual learners, algorithms with the ensemble method used are stacking, random forest, and adaboost, then comparing the result to get the best accuracy. The test results prove that the Stacking algorithm technique is the best model with the highest score in terms of accuracy with a value of 86.84%, while the Random Forest and AdaBoost algorithm techniques have a value of 81.04% and 80.30%. With this high accuracy value, the Stacking model is proven to have better individual performance in analyzing employee turnover predictions in human resource applications in companies.
PEMBERDAYAAN MASYARAKAT MELALUI PELATIHAN E-COMMERCE UNTUK MENUMBUHKAN JIWA ENTERPRENEUR PADA KOMUNITAS PENCINTA IKAN HIAS Hamdani, Agus Umar; Suryadi, Lis; Indra, Indra; Triyono, Gandung
Jurnal Pintar Abdimas Vol 1 No 1 (2021): VOLUME 1 NOMOR 1 NOVEMBER 2021
Publisher : Lembaga Pengabdian Masyarakat Universitas Swadaya Gunung Jati

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

Abstract

Most of the residents in the RT run the Micro, Small and Medium Business Units (UMKM). Although some business actors have used information technology tools to support their business, they are only limited to posting products via Facebook, Twitter, Instagram and WhatsApp. Residents do not understand how to sell and market products using information technology tools. In addition, product sales turnover tends to decline during the Covid-19 pandemic and large-scale social restrictions (PSBB), due to the lack of buyers. E-Commerce is an information system technology device that can be an alternative solution in an electronic-based sales system. With the use of E-Commerce technology, business actors can market their products online anywhere and anytime. Based on the above conditions, we conducted training to build a business using Electronic Commerce (E-Commerce) technology for residents in the RT 03 RW 02 Pondok Jati Jurangmangu Barat environment in order to foster an entrepreneurial spirit based on information technology (Technopreneur). The end result of this community service activity is that residents of RT 03 RW 02 Pondok Jati Jurangmangu Barat gain knowledge and experience regarding the use of E-Commerce technology, and get assistance in building E-Commerce websites.
Analisis Sentimen pada Ulasan Aplikasi Wondr di Play Store dengan Metode Naïve Bayes Nurhikmah, Suci; Ramadani, Romi; Triyono, Gandung
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2507

Abstract

The advancement of digital technology continues to drive innovation in the banking sector, particularly in the development of mobile banking services that are more responsive to customer needs. Bank Negara Indonesia (BNI) has responded to this demand by launching the Wondr application as a replacement for its previous BNI Mobile Banking platform, which has received a wide range of user feedback on the Google Play Store.This study was conducted to understand user opinions and perceptions regarding the Wondr application, with the aim of evaluating feedback that could serve as a strategic basis for enhancing BNI’s digital services. The approach employed sentiment analysis using the Naive Bayes Classifier, implemented in Python. The dataset consisted of 27,124 user reviews.The classification results revealed that 52.9% of the reviews were positive, 39.9% negative, and 7.2% neutral. The Naive Bayes model achieved an accuracy of 82%, although its performance in identifying neutral sentiment remained weak, as evaluated through precision, recall, and F1-Score metrics.These findings indicate that the Wondr application is generally well received by users, although certain aspects still require improvement. The study recommends further exploration of alternative classification algorithms such as Random Forest, Support Vector Machine (SVM), and Deep Learning methodologies, as well as the application of SMOTE techniques to address data imbalance, particularly in neutral sentiment classification.
Co-Authors - Sumardianto Abdul Hamid Abdurrahman, Faris Nur Achmad Ardiansyah Achmad Solichin Achmad Syarif Adhi, Ajar Parama Aditya Ikhbal Maulana Agus Umar Hamdani Aji Guntoro Ajinarasena Hermanu Al Ghozali, Isnen Hadi Al-akbari, Munawir Fikri Amirudin Amirudin Ananda Dian Nugraha Angga Prasetyo Anggita Pamukti Anggraini Ujianti Annisa Putri Gita Cahyani Anwarsyah, Anwarsyah Aris Subagyo, Wismoyo Asep Lukman Arip Hidayat Assegaf , Noval Azizi, Hibatul Azrul Azmani 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 Idmi, Idmi Iman Permana, Iman Indra Indra Jotri Firdani Maharaja Juhari Juhari, Juhari Jumaryadi, Yuwan Kanasfi, Kanasfi Kiki Ari Suwandi kosasih Kristiyantho, Yutdhi Lestari, Triardani Lis Suryadi Lis Suryadi, Lis Lutfan Lazuardi Luthfi Mawardi Mahendra, M. Azmi Malik Aziz Habibie Maruanaya, Greghar Juan Tjether 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 Muhamad Rizky Syawalludi Muhammad Dzakky Ikhwani Imaduddin Munandar, Muhamad Arief Muttaqin, Zaenul Naurah Huwaida Ningrum, Sekar Ayu Novandy, Axel Nurhikmah, Suci Oktiara, Dara Putri Ono Taryono Pebry, Fachry Ajiyanda Pirman, Arif Prasetia, Andika Rohman Prasetyo, Angger Totik Prasetyo, Sigit Ari Putri Hayati Rahmat Hidayat Ramadani, Romi Reza Ariftiarno Ridho Firmansyah Ridho Putra Kusmanda Riki Ramdani Saputra Rima Tamara Aldisa Rinto Prasetyo Adi Riski Amalia Rita Fransina Maruanaya Rizka Pitriyani Rizky Adhi Saputra Rizky Fernanda Aprianto Rizky Tahara Shita Rojakul, Rojakul Rudi Hartono Rudi Hidayat Ryan Prasetya Safrina Amini Samuel Samuel Septiadi, Septiadi Setyadin, Rahmat Dipo Siswahyudianto Sittah Ifadah Sri Hartati Sri Melati Subekti, Yogi Agung Sudiyatno Yudi Nugroho Sufyan Asaury, Akhmad Suriah Setiana Widiastuti SURYANI Syarif Hidayatulloh Tansya Ingmukti Tunggal Saputra, Tri Aji Tutik Lestari Umar Alfaruq 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