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All Journal Techno.Com: Jurnal Teknologi Informasi PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnas Nasional Teknologi dan Sistem Informasi Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta CogITo Smart Journal JTERA (Jurnal Teknologi Rekayasa) Jurnal Sisfokom (Sistem Informasi dan Komputer) KACANEGARA Jurnal Pengabdian pada Masyarakat JSiI (Jurnal Sistem Informasi) JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal Jurnal Pendidikan dan Konseling Jurnal Sistem Informasi dan Informatika (SIMIKA) Jurnal Investasi Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) Madaniya Idealis : Indonesia Journal Information System SKANIKA: Sistem Komputer dan Teknik Informatika Sekretari & Administrasi (Serasi) Jurnal Teknik Informatika (JUTIF) Teknika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer Decode: Jurnal Pendidikan Teknologi Informasi Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Jurnal Sisfotek Global Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Malcom: Indonesian Journal of Machine Learning and Computer Science Telematika MKOM AMMA : Jurnal Pengabdian Masyarakat Jurnal Ticom: Technology of Information and Communication The Indonesian Journal of Computer Science Jurnal Pengabdian Masyarakat Tekno INOVTEK Polbeng - Seri Informatika Jurnal Pintar Pengabdian dan Pemberdayaan Masyarakat
Triyono, Gandung
Universitas Budi Luhur
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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.
Penerapan Sistem Informasi Administrasi Laundry Angga Prasetyo; Triyono, Gandung Triyono; Utomo Budiyanto
Jurnal Ticom: Technology of Information and Communication Vol 10 No 3 (2022): Jurnal Ticom-Mei 2022
Publisher : Asosiasi Pendidikan Tinggi Informatika dan Komputer Provinsi DKI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70309/ticom.v10i3.34

Abstract

Pada saat ini bisnis laundry atau jasa pencucian pakaian terus berkembang. Meningkatnya bisnis ini menjadikan tantangan baru bagi pelaku bisnis laundry, karena semakin banyaknya persaingan dalam bisnis ini. Banyaknya persaingan ini menyebabkan pendapatan semakin menurun. Oleh sebab itu diperlukanya statrategi yang tepat untuk menangani masalah tersebut, salah satunya meningkatkan pelayanan secara maksimal. Penelitian ini bertujuan untuk mengembangkan model sistem administrasi laundry guna meningkatkan pelayanan terhadap pelanggan. Pengembangan model menggunakan pendekatan berbasis obyek. Hasil dari penelitian ini mendapatkan model sistem informasi administrasi laundry yang memiliki fungsi lengkap. Mulai dari proses penerimaan cucian sampai dengan pembuatan laporan. Dari hasil pengujian yang dilakukan, model yang dikembangkan merupakan model yang fleksibel, yaitu dapat diterapkan untuk semua jenis bisnis laundry. Model yang dikembangkan telah dilakukan pengujian di tingkat user, yaitu User Acceptance Test (UAT). Hasil pengujian didapatkan bahwa model yang dikembangkan mendapatkan respon yang cukup baik dari user, yaitu diperoleh presentase sebesar 80%.
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.
Prediksi Harga Beras di Kalimantan Barat Menggunakan Metode Regresi Linier Sederhana Azizi, Hibatul; Aris Subagyo, Wismoyo; 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.22-2.2755

Abstract

Beras merupakan bahan makanan pokok utama masyarakat Indonesia, sehingga kestabilan harga beras menjadi hal yang sangat penting dalam menjaga stabilitas ekonomi, sosial, dan politik. Fluktuasi harga beras yang signifikan, termasuk di Provinsi Kalimantan Barat, sering kali dipengaruhi oleh berbagai faktor, seperti cuaca, produksi, dan distribusi, yang memerlukan pendekatan prediktif untuk mendukung pengambilan keputusan. Penelitian ini bertujuan untuk memprediksi harga beras menggunakan metode regresi linier sederhana, dengan fokus pada harga beras premium dan medium. Data yang digunakan meliputi harga historis beras serta beberapa parameter indeks relevan lainnya. Model regresi linier sederhana diterapkan untuk menganalisis hubungan antara faktor independen dengan harga beras sebagai variabel dependen. Hasil penelitian menunjukkan bahwa model regresi memiliki tingkat akurasi yang sangat baik, dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 2,76% untuk harga beras premium dan 3,28% untuk harga beras medium. Temuan ini menunjukkan bahwa regresi linier sederhana dapat menjadi alat yang andal untuk prediksi harga beras dan mendukung pengambilan keputusan strategis, baik oleh pemerintah maupun pemangku kepentingan lainnya. Model yang dibangun diharapkan dapat berkontribusi terhadap perencanaan kebijakan pangan yang lebih efektif, terutama di wilayah dengan fluktuasi harga tinggi seperti Kalimantan Barat.
Tinjauan Literatur Sistem Rekomendasi Film: Mengidentifikasi Pendekatan Terbaik Febrianti, Rizkia Saski; Ningrum, Sekar Ayu; 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.22-2.3011

Abstract

The recommendation system is a crucial element in various digital platforms, particularly within the entertainment industry. Its presence helps users discover films that align with their preferences. As the popularity of digital platforms continues to rise in the modern era, the main challenge lies in meeting users’ needs for relevant recommendations amid the diversity and ever-increasing volume of available content. This study focuses on a literature review to determine the most suitable methods to be applied in movie recommendation systems. The urgency of this research lies in the importance of a platform’s ability to provide recommendations that are not only relevant but also capable of enhancing user engagement and satisfaction. The proposed solution in this study involves applying methods that can analyze user preferences and behavior to improve the accuracy and level of personalization within the recommendation system. The research employs the Systematic Literature Review (SLR) method by collecting articles published between 2020 and 2024 from the Google Scholar database, all of which are relevant to the topic of movie recommendation systems. From the search results, 20 selected articles were used as the basis for analysis. Based on the analysis of these articles, it was found that up until the end of 2024, the most widely used method in movie recommendation systems is Collaborative Filtering, achieving the highest precision rate of 89% and a recall value of 96%.
Diagnosis Dini Demam Berdarah Berdasarkan Data Hematologi Menggunakan Algoritma Machine Learning Yulia Nita; Maya Gian Sister; Gandung Triyono
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.
Model Optimalisasi Seleksi Penerimaan Beasiswa Perguruan Tinggi Swasta Menggunakan K-Means dan TOPSIS Al-akbari, Munawir Fikri; Munandar, Muhamad Arief; 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.22-2.2531

Abstract

Ensuring a fair and well-targeted scholarship distribution process remains one of the major challenges faced by private universities. In many cases, scholarship recipient selection is carried out subjectively and lacks support from a systematic approach. This study proposes a hybrid method using K-Means Clustering and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to optimize the scholarship selection process. Student data covering academic aspects (GPA), socio-economic factors (parental income and occupation, family dependents), and non-academic components (achievements and organizational activity) were analyzed using the K-Means algorithm to group students with similar characteristics. Silhouette Score validation produced four optimal clusters with a score of 0.1683. Subsequently, the TOPSIS method was applied to rank the clusters based on predetermined criteria. The results show that Cluster 4 achieved the highest ranking with a score of 0.7853, followed by Cluster 3 (0.6359), Cluster 1 (0.6014), and Cluster 2 (0.5807). Attribute contribution analysis revealed that GPA is the dominant factor (48.61%–52.26%), followed by parental income (16.15%–19.59%) and family dependents (11.36%–12.09%). The developed model successfully provides an objective foundation for allocating scholarship quotas based on student group characteristics. This study contributes to the development of a more transparent and accountable scholarship selection system.
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 Angga Prasetyo Anggita Pamukti Anggraini Ujianti Annisa Hanifa Annisa Putri Gita Cahyani Anwarsyah, Anwarsyah Arif Pirman Aris Subagyo, Wismoyo Asep Lukman Arip Hidayat Assegaf , Noval Azizi, Hibatul Azrul Azmani Chaerul, Muh Coudry Bernadeth Dana Indra Sensuse Daniel Iskandar Dara Putri Oktiara Dede Wahyu Saputra Dermawan Ginting Devy Fatmawati Dini Astuti Dini Handayani Djafar, Muhammad Agung A. Djati Kusdiarto Dolly Virgian Shaka Yudha Sakti Dwi Kristanto Dyah Puji Utami Dzakiyyah, Syifa Ghina Effendi , Muhtar Eliyani, Eliyani Ery Rinaldi Eva Yulyanti 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 Hardjianto, Mardi Helmi Zulqan Henny Hikmah, Maulida 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 M. Azmi Mahendra Mahendra, M. Azmi Malik Aziz Habibie Marentek, Billy Maruanaya, Greghar Juan Tjether Maskur A, Moch Riyadi Masnuryatie, Masnuryatie Maulana Firmansyah Maya Asmita Maya Gian Sister Megananda Hervita P. Melyana, Melyana Mepa Kurniasih MHD. Reza M.I. Pulungan Moch. Rezaf Ivanka Haris Mohammad Aldinugroho Abdullah Mohammad Syafrullah Muhamad Dikhi Rohman Muhamad Rizky Syawalludi Muhammad Dzakky Ikhwani Imaduddin Munandar, Muhamad Arief Naurah Huwaida Ningrum, Sekar Ayu Novandy, Axel Nurhikmah, Suci Nurjanah, Septiana Ono Taryono Pebry, Fachry Ajiyanda Pipit Ari Mufidah Prasetia, Andika Rohman Prasetyo, Angger Totik Putri Hayati putri yani, putri 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 Hidayat Ryan Prasetya Safrina Amini Samuel Samuel Septiadi, Septiadi Setyadin, Rahmat Dipo Shindy Yuliyatini Sigit Ari Prasetyo 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 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 Yulia Nita Zaenul Muttaqin Zainal Arifin