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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar Journal of Information Systems and Informatics Neo Teknika: Jurnal Ilmiah Teknologi Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Teknologi Informasi Cyberku Jurnal Algoritma Majalah Ilmiah Inspiratif Indonesian Journal of Community Empowerment (IJCE) "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika INOVTEK Polbeng - Seri Informatika Jurnal Ilmu Komputer
Abdul Rohman
Universitas Ngudi Waluyo
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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Sistem Prediksi Penjualan Menggunakan Metode Single Exponential Smoothing Berbasis Web (Studi Kasus : PT Ungaran Sari Garments) Husnul Khotimah; Abdul Rohman
Multimatrix Vol. 7 No. 1 (2025): Juli 2025
Publisher : Universitas Ngudi Waluyo

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Abstract

Selama ini PT Ungaran Sari Garments hanya memprediksi penjualannya mengandalkan insting atau perkiraan dari manajer gudang untuk mengambil keputusan dalam pembelian persediaan barang. Belum adanya perhitungan yang menggunakan suatu sistem untuk membantu memprediksi penjualan periode kedepannya. Ada beberapa metode terkait prediksi salah satunya yaitu Single Exponential Smoothing, metode ini tidak memerlukan banyak data penjualan dari periode-periode sebelumnya untuk menghasilkan suatu peramalan. Data yang diambil adalah data penjualan dari bulan juni 2021 sampai Mei 2022 yaitu berjumlah 190.771. Hasil pengujian metode Single Exponential Smoothing untuk mengetahui tingkat nilai keakuratan memperoleh hasil peramalan terbaik terdapat pada alpha 0.1 dengan MAPE 8,28%, dan peramalan penjualan periode bulan juli 2022 yaitu 15758. Metode ini dinyatakan sangat akurat karena memiliki nilai MAPE terendah. Sistem ini hanya dapat meramalkan satu periode tertentu saja tidak dapat digunakan untuk melakukan peramalan beberapa periode kedepan dalam satu peralaman. Kata kunci: Sistem Prediksi Penjualan, Single Exponential Smoothing, PT Ungaran, Sari Garments Until now, PT Ungaran Sari Garments has relied solely on instinct or estimates from warehouse managers to predict its sales when making inventory purchasing decisions. There has been no systematic calculation to help predict future sales. Several forecasting methods exist, one of which is Single Exponential Smoothing. This method does not require extensive sales data from previous periods to generate a forecast. The data used was sales data from June 2021 to May 2022, totaling 190,771. Testing the Single Exponential Smoothing method to determine the accuracy of the forecast showed the best result at an alpha of 0.1 with a MAPE of 8.28%, and a sales forecast for July 2022 of 15,758. This method was deemed highly accurate due to its lowest MAPE value. This system can only forecast a specific period and cannot be used to forecast multiple future periods in a single run. Keywords: Sales Prediction System, Single Exponential Smoothing, PT Ungaran, Sari Garments
Sistem Pendukung Keputusan Untuk Penentu Kategori Anak Terajin Pada Pelayanan Sekolah Minggu di GSJA Bukit Horeb Salatiga Dengan Metode Analytical Hierarchy Process Siska Nadeak; Iwan Setiawan Wibisono; Abdul Rohman
Multimatrix Vol. 7 No. 1 (2025): Juli 2025
Publisher : Universitas Ngudi Waluyo

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Sistem pendukung keputusan penentuan kategori anak terajin pada pelayanan anak sekolah minggu GSJA Bukit Horeb Salatiga masih dijumpai sistem keputusan manual merupakan hambatan dalam proses pelayananan karena seringkali terjadi kesulitan dalam menyeleksi. Hal tersebut dapat mengakibatkan tidak tepat sasarannya pengahargaan yang diberikan serta memerlukan banyak waktu dalam proses yang manual. Untuk itu diperlukan suatu aplikasi pendukung keputusan untuk memilih anak dalam kategori terajin. Sistem pendukung keputusan (SPK) memungkinkan pengguna untuk melakukan keputusan dengan lebih cepat dan tepat. Metode yang digunakan adalah metode Analytic Hierarchy Process (AHP). Penelitian dilakukan berdasarkan prosedur AHP. Kriterianya adalah Kehadiran, tugas, keaktifan dan disiplin. Untuk mempermudah pengujian digunakan lima alternatif anak sekolah minggu yaitu: Alvino ghani putra, Bunga kanya A, Melody Novelita Purw, Ruben shalom natanael, Susistiani febrian. Hasil penelitian menunjukkan bahwa peringkat pertama didapat oleh Ruben shalom natanael (0,295769), kedua Susistiani febrian (0,193573), ketiga Alvino ghani putra (0,188745), kempat Melody Novelita Purw (0,163848) kelima Bunga kanya A(0,158063). Jadi dapat disimpulkan bahwa aplikasi dapat mendukung sistem pengambilan keputusan penentuan kategori anak terajin. Kata kunci : SPK, kategori anak terajin, AHP(Analytic Hierarchy Process) The decision support system for determining the category of "most diligent" children in the Sunday school service at GSJA Bukit Horeb Salatiga still encounters a manual decision-making system, which is a barrier to the service process because it often causes difficulties in selection. This can result in inaccurate awards and requires a lot of time in the manual process. Therefore, a decision support application is needed to select children in the most diligent category. A Decision Support System (DSS) allows users to make decisions more quickly and accurately. The method used is the Analytic Hierarchy Process (AHP) method. The research was conducted based on the AHP procedure. The criteria were attendance, assignments, activeness, and discipline. To facilitate testing, five alternative Sunday school children were used: Alvino Ghani Putra, Bunga Kanya A, Melody Novelita Purw, Ruben Shalom Nathanael, and Susistiani Febrian. The results showed that Ruben Shalom Nathanael ranked first (0.295769), followed by Susistiani Febrian (0.193573), Alvino Ghani Putra (0.188745), Melody Novelita Purw (0.163848), and Bunga Kanya A (0.158063) in third place. Therefore, it can be concluded that the application can support the decision-making system for determining the category of skilled children.
Pelatihan Membuat Website Sekolah Sekolah dengan Menggunakan Blooger di Komunitastas e-guru.id Abdul Rohman; Yoannes Romando Sipayung; Basuki Sulistio
Multimatrix Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Ngudi Waluyo

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Abstract

Website sekolah merupakan instrumen vital dalam era transformasi digital untuk mendukung transparansi informasi, promosi, dan komunikasi antara sekolah dengan masyarakat. Namun, keterbatasan kompetensi teknis guru dan kendala biaya seringkali menjadi hambatan utama bagi sekolah dalam memiliki website resmi. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk meningkatkan literasi digital guru serta memberikan keterampilan praktis dalam pembuatan dan pengelolaan website sekolah berbasis platform Blogger. Kegiatan ini melibatkan 79 guru dari berbagai wilayah di Indonesia yang tergabung dalam komunitas e-Guru.id. Metode pelaksanaan dilakukan secara daring selama enam bulan pada tahun 2024 dengan pendekatan partisipatif dan learning by doing, yang mencakup tahap persiapan, pelatihan inti, pendampingan, serta evaluasi. Hasil kegiatan menunjukkan bahwa seluruh peserta berhasil membuat website sekolah secara mandiri yang dilengkapi dengan fitur profil sekolah, berita, dan layanan interaktif tanpa memerlukan keahlian pemrograman (coding). Selain itu, terdapat peningkatan signifikan pada kepercayaan diri dan kompetensi guru dalam pengelolaan konten digital. Penggunaan Blogger terbukti menjadi solusi praktis, efisien, dan berkelanjutan untuk mengatasi kesenjangan digital di lingkungan pendidikan. Kata Kunci: Blogger, Kompetensi Guru, Literasi Digital, Transformasi Digital, Website Sekolah. School websites are vital instruments in the era of digital transformation, supporting information transparency, promotion, and communication between schools and the community. However, limited teacher technical competency and financial constraints are often major barriers for schools in establishing official websites. This Community Service (PkM) activity aims to improve teachers' digital literacy and provide practical skills in creating and managing school websites based on the Blogger platform. This activity involved 79 teachers from various regions in Indonesia who are members of the e-Guru.id community. The implementation method was conducted online for six months in 2024, using a participatory and learning-by-doing approach, encompassing preparation, core training, mentoring, and evaluation. The results showed that all participants successfully created their own school websites, complete with school profile features, news, and interactive services without requiring programming skills (coding). Furthermore, there was a significant increase in teachers' confidence and competency in digital content management. The use of Blogger has proven to be a practical, efficient, and sustainable solution to address the digital divide in educational settings. Keywords: Blogger, Teacher Competence, Digital Literacy, Digital Transformation, School Website.
Prediksi Minat Mahasiswa Terhadap Kegiatan Sinematografi Menggunakan Algoritma C4.5 di Universitas Ngudi Waluyo Ray Taufiqy Sagala; Abdul Rohman
Multimatrix Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Ngudi Waluyo

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Abstract

Minat merupakan salah satu hal yang paling mendasar bagi mahasiswa untuk menemukan bakatnya. Dan bakat mahasiswa sangatlah penting untuk diketahui oleh universitas sebagai kegiatan kemahasiswaan untuk mengembangkan potensi mahasiswa. Maka dari itu perlu adanya prediksi minat mahasiswa agar pihak universitas bisa mengetahui minat dan bakat mahasiswa. Oleh karena itu diperlukan system prediksi minat mahasiswa menggunakan Algoritma C4.5. Penelitian ini dirancang dan dikembangkan menggunakan aplikasi Microsoft Excel, yang kemudian di evaluasi akurasinya menggunakan aplikasi Rapid Miner. Dan hasil dari pengujian Confusion Matrix memperlihatkan bahwa system ini dapat berjalan sesuai dengan fungsinya yaitu melakukan prediksi minat mahasiswa terhadap kegiatan sinematografi. Serta pada pengujian akurasi, system ini menghasilkan nilai akurasi sangat baik sebesar 94,24%. Kata Kunci : Algoritma C4.5, Minat, Mahasiswa, Sinematografi Interest is one of the most basic things for students to discover their talents. And student talent is very important to be known by the university as a student activity to develop student potential. Therefore it is necessary to predict student interest so that the university can find out student interests and talents. Therefore we need a prediction system for student interest using the C4.5 Algorithm. This research was designed and developed using the Microsoft Excel application, which was then evaluated for accuracy using the Rapid Miner application. And the results of the Confusion Matrix test show that this system can run according to its function, namely predicting student interest in cinematography activities. As well as in testing accuracy, this system produces a very good accuracy value of 94.24%. Keywords : C4.5 Algorithm, Interest, Student, Cinematography
Cyberbullying Detection in Indonesian TikTok Comments Using IndoBERT with Fairness Evaluation Hanik Dewi Jayanti; Abdul Rohman
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1448

Abstract

This study investigates automated cyberbullying detection on TikTok within the Indonesian digital context, where high social media usage among children and adolescents demands scalable and consistent content moderation. We propose an IndoBERT-based framework for detecting and classifying cyberbullying in Indonesian-language TikTok comments, incorporating algorithmic fairness considerations. A dataset of 2,122 TikTok comments was collected from a publicly available Kaggle repository and divided into training, validation, and testing sets using a 70:15:15 stratified sampling ratio. The IndoBERT-base-p1 model was fine-tuned with the PyTorch and HuggingFace frameworks, optimizing hyperparameters like the AdamW optimizer and learning rate scheduling. Experimental results show that the model achieved an accuracy of 70.66% and a ROC-AUC score of 0.7969, demonstrating solid discriminative power. With a macro F1-score of 0.7066 and a cyberbullying recall of 0.7170, the model shows balanced performance in identifying harmful content. A key contribution of this study is a fairness evaluation framework that reveals an accuracy gap of 2.08% and an equal opportunity gap of 0.0208, indicating overall fairness. However, demographic parity remains a concern. This system, supporting content triage combined with human review, enhances moderation workflows by filtering non-cyberbullying cases while flagging potentially harmful content for human oversight.
Co-Authors Afiatna, Puji Afif Faisal Yasin Afifah Nur Hawa Agung Wibowo Agung Wibowo Anief Rufiyanto Aqmal Putra R.R Basuki Sulistio Bayu Evendi Catur Supriyanto Choerul Fikri Hamdani Cicik Harini Dedy Alan Wirawan Desi Fitria Wulandika Deta verrensyah Dika Ade Royani Erika Ifalinda Fernanda Bagus Dwi Prastyo Fiki Wijayanti Hanik Dewi Jayanti hia, Meriani Husnul Khotimah Intan Febriyana Irene Trivena Montalili Ismail, Ahmad Hafizh Iwan Setiawan Wibisono Khilda Afriyani Khoirul Asrofi Mayasa Kurnia Muhammad Diva Livarizi Muhammad Rochcham Munasiroh Munasiroh Nopita Widayanti Noviyana Dwi Herlinda Ray Taufiqy Sagala Rochmawati, Nur Intan Sabilatul Hidayah Salman Alfarizi Siska Nadeak Sri Mujiyono Sugeng Deri Pratama Tara Indah Afelia Teguh Santoso Ucik Lujiyanti Rukmana Vincent Suhartono Wahyu Aji Kuswoyo Wildan Khoiri Priandana Yoannes Romando Sipayung Yusak Maryunianta