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All Journal Techno.Com: Jurnal Teknologi Informasi PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic 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 Telematika MKOM AMMA : Jurnal Pengabdian Masyarakat 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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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%.
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.
OPTIMASI PEMILIHAN QUALITY ASSURANCE CV FORTUNE CLEAN MENGGUNAKAN METODE TOPSIS Annisa Putri Gita Cahyani; Naurah Huwaida; Gandung Triyono
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 9 No. 1 (2026): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/dxeh2n20

Abstract

CV Fortune Clean, a company providing cleaning services and products, requires Quality Assurance (QA) professionals to ensure the optimal performance of technological and system updates in its internal applications, which are vital for business processes such as inventory management and service scheduling. The previous recruitment process, reliant on manual CV screening and subjective interviews, took up to four months to identify truly competent candidates, causing delays in application updates and potentially hindering operational efficiency. To address this issue, this study designs a Decision Support System (DSS) based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS was chosen for its ability to evaluate candidates based on their proximity to an ideal solution, considering technical criteria and non-technical criteria (e.g., problem-solving and communication skills). The DSS implementation reduced recruitment time from four months to one month, enhanced selection accuracy by minimizing subjective bias, and proved more consistent than manual methods in comparative simulations. The TOPSIS system also improved transparency and objectivity in the selection process, optimizing recruitment duration and enhancing the quality of QA personnel to support the reliability of internal applications critical to business operations.
Analysis of the Influence of System QuaAnalysis of the Influence of System Quality, Information Quality, and Service Quality on User Satisfaction of Payment Systems Using Virtual Accountslity, Information Quality, and Service Quality on User Satisfaction of Payment Systems Using Virtual Accounts Azrul Azmani; Tutik Lestari; Muhammad Dzakky Ikhwani Imaduddin; Ajinarasena Hermanu; Gandung Triyono
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16034

Abstract

This study aims to analyze the influence of system quality, information quality, and service quality on user satisfaction in virtual account payment systems implemented at Pesantren Darunnajah. The increasing adoption of digital payment solutions in educational institutions underscores the need for reliable systems that ensure convenience, security, and efficiency. Using the Technology Acceptance Model (TAM) as a theoretical framework, data were collected through a survey of 36 respondents, including guardians and staff, and analyzed using multiple linear regression. The findings reveal that system quality, information quality, and service quality all have a significant positive effect on user satisfaction, with service quality emerging as the most influential factor. These results highlight the importance of responsive support and accurate information in enhancing user experience. The study contributes to the literature on digital payment adoption in Islamic educational institutions and provides practical insights for improving service delivery. Future research should explore additional factors such as security, interface design, and user trust to broaden understanding of technology acceptance in similar contexts.
PENERAPAN K-MEDOIDS UNTUK MENGELOMPOKKAN HARGA JUAL IKLAN Kristiyantho, Yutdhi; Triyono, Gandung; Novandy, Axel
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7414

Abstract

Penjualan dan pemesanan produk berupa iklan menjadi hal yang sangat penting nilainya bagi perusahaan. Peningkatan penjualan iklan akan mempengaruhi keuntungan dan pemasukan perusahaan. Pada penelitian dalam pengelompokkan harga penjualan menggunakan metode k-medoids dengan tahapan analisis data sebanyak 500 data, pra-pemrosesan (preprocessing) data dengan tahapan data cleaning atau pembersihan dari data yang tidak valid, salah, atau kosong. Kemudian transformasi data dengan mengubah platform online menjadi 0 dan print menjadi 1. Tahapan selanjutnya adalah perhitungan manual dengan algoritma k-medoids dan implementasi pada aplikasi rapidminer. Pengelompokkan menghasilkan 2 cluster yaitu cluster 1 berjumlah 68 items dan cluster 2 berjumlah 432 items. Harga yang terdiri dari (before_discount, after_discount, tax, dan after tax) dari cluster 1 lebih tinggi dari cluster 2. Cluster 1 juga mempunyai jumlah kelompok data yang lebih sedikit dibandingkan dengan cluster 2. Hal ini menunjukkan bahwa harga mempengaruhi penjualan iklan, harga yang murah akan lebih banyak dipesan. Sedangkan platform dengan nilai 0 atau online  lebih banyak dipesan oleh cluster 2 dengan data pengelompokkan terbanyak. Hal ini juga menunjukkan bahwa online lebih banyak dipesan karena banyak terdapat pada cluster 2. Hasil tersebut dapat menjadi acuan bagi perusahaan untuk menentukan kebijakan dan strategi dalam penjualan atau pemesanan iklan agar lebih banyak mendapatkan keuntungan dan pemasukan.
IMPLEMENTASI HYBRID ARIMA-PROPHET UNTUK PREDIKSI HARGA BERAS NASIONAL Amirudin, Amirudin; Prasetyo, Sigit Ari; Triyono, Gandung
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.8689

Abstract

Fluktuasi harga beras sebagai komoditas pangan utama di Indonesia berpengaruh signifikan terhadap stabilitas ekonomi dan ketahanan pan-gan nasional. Penelitian ini bertujuan untuk mengembangkan model hybrid ARIMA-Prophet guna memprediksi harga beras nasional dengan tingkat akurasi yang lebih tinggi dibandingkan implementasi model tunggal. Data yang digunakan dalam penelitian ini bersumber dari da-taset Kaggle "Harga Pangan Indonesia" dengan rentang waktu 2021–2024. Metodologi penelitian meliputi preprocessing data, implementa-si model ARIMA, implementasi model Prophet, pengembangan model hybrid, dan evaluasi performa model menggunakan metrik MAE, RMSE, dan MAPE. Hasil penelitian menunjukkan bahwa model hybrid ARIMA-Prophet mampu menangkap pola tren jangka panjang dan fluktuasi musiman dengan lebih efektif, serta meningkatkan akurasi prediksi sebesar 18,5% dibandingkan model ARIMA dan 12,3% dibandingkan model Prophet. Implementasi model hybrid ini menghasilkan nilai MAPE sebesar 3,2%, yang menunjukkan tingkat akurasi yang sangat baik dalam konteks prediksi harga komoditas. Kesimpulan penelitian ini mengonfirmasi keunggulan pendekatan hybrid dalam memodelkan data time series yang kompleks seperti harga beras, yang dipengaruhi oleh berbagai faktor eksternal, musiman, dan tren pasar global.
ANALISIS PERBANDINGAN MODEL NAÏVE BAYES DAN C4.5 UNTUK PREDIKSI STROKE BERDASARKAN RIWAYAT DATA MEDIS DENGAN PENDEKATAN MATRIKS KORELASI Samuel, Samuel; Idmi, Idmi; Triyono, Gandung
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.8653

Abstract

Stroke merupakan satu diantara penyakit mematikan yang bisa terjadi secara mendadak dan bisa menyebabkan kematian/kecacatan. Prediksi dini risiko stroke sangat krusial guna mendukung tindakan an-tisipasi dan penanganan yang tepat. Penelitian ini membandingkan akurasi dua algoritma klasifikasi, yaitu Naive Bayes dan C4.5, dalam memprediksi risiko stroke berdasarkan data medis pasien. Metode pemilihan atribut menggunakan matriks korelasi diterapkan untuk memilih fitur yang paling relevan guna meningkatkan akurasi model. Data yang digunakan merupakan dataset stroke dari situs Kaggle. Hasil penelitian memperlihatkan penerapan matriks korelasi sebagai teknik seleksi atribut meningkatkan akurasi kedua algoritma. Algoritma C4.5 memberikan akurasi tertinggi men-capai 95%. Atribut yang berpengaruh signifikan dalam prediksi stroke antara lain tipe tempat tinggal, jenis kelamin, penyakit jantung, hipertensi, rata-rata kadar glukosa, dan status merokok. Dengan demikian, kombinasi seleksi fitur berbasis matriks korelasi dan algoritma C4.5 efektif untuk membangun model prediksi risiko stroke yang akurat dan dapat menjadi alat bantu diagnosis medis
Pelatihan Komputer Untuk Santri Pondok Pesantren Tahfidzul Qur’an Wahidin Halim Mardi Hardjianto; Lis Suryadi; Dolly Virgian Shaka Yudha Sakti; Gandung Triyono
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 1 : Februari (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

Abstract

This Community Service activity was carried out in collaboration with the Wahidin Halim Tahfidzul Qur'an Islamic Boarding School, an Islamic boarding school located on Jl. H. Gillan RT. 003/RW. 001, Pinang District. Pinang, Tangerang City, Banten 15145. Currently, our partners are struggling to overcome problems arising from the lack of computer training for students. To overcome this problem, we held face-to-face computer training sessions at the ICT Laboratory of Budi Luhur University. The survey evaluation showed that more than 85% of participants felt that the activity was useful, easy to understand, effective, and met their expectations. Therefore, it can be concluded that this activity provides the right solution to partner problems.
Pemanfaatan LMS Moodle Sebagai Media Pembelajaran Daring Bagi Santri Pondok Pesantren Tahfidzul Qur’an Wahidin Halim Achmad Syarif; Lis Suryadi; Gandung Triyono
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
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