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All Journal JUITA : Jurnal Informatika E-Dimas: Jurnal Pengabdian kepada Masyarakat JOURNAL OF APPLIED INFORMATICS AND COMPUTING Indonesian Journal of Community Services Walisongo Journal of Information Technology Journal of Dinda : Data Science, Information Technology, and Data Analytics
Nugroho Dwi Saputro
Universitas PGRI Semarang
Humanities Computer Science & IT Engineering Social Sciences

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Analisis dan Penerapan Algoritma Support Vector Machine (SVM) dalam Data Mining untuk Menunjang Strategi Promosi Agung Handayanto; Khoirya Latifa; Nugroho Dwi Saputro; Rahmat Robi Waliansyah
JUITA : Jurnal Informatika JUITA VoL. 7 Nomor 2, November 2019
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (877.135 KB) | DOI: 10.30595/juita.v7i2.4378

Abstract

Universitas PGRI Semarang (UPGRIS) setiap tahun melakukan penerimaan mahasiswa baru. Banyaknya jumlah calon mahasiswa yang tidak melakukan registrasi ulang setiap tahunnya menjadi permasalahan dalam penerimaan mahasiswa baru Program Studi (prodi) Informatika. Hal tersebut menimbulkan masalah yang harus segera diselesaikan oleh pihak kampus, sehingga kuota mahasiswa baru untuk masing-masing prodi belum tercapai. Oleh karena itu diperlukan strategi promosi yang lebih efisien dan efektif. Untuk mengetahui pola dari data-data tersebut dibutuhkan pengolahan data yang baik sehingga dari data-data tersebut bisa diambil informasi yang tersembunyi. Metode SVM dipilih untuk analisis data mining pada riset ini. Parameter yang digunakan ada 6 yaitu jenis kelamin, agama, asal sekolah, jurusan, asal kota/kabupaten dan daftar ulang. Riset ini menggunakan data rekapitulasi penerimaan mahasiswa baru prodi Informatika UPGRIS dari tahun 2014 sampai 2018 dengan total 6371 baris. Berdasarkan hasil analisis diperoleh tingkat akurasi sebesar 73,6%.
Sistem Pakar Pembagian Harta Waris Menurut Hukum Islam Nur Aksin; Rahmat Robi Waliyansyah; Nugroho Dwi Saputro
Walisongo Journal of Information Technology Vol 2, No 2 (2020): Walisongo Journal of Information Technology
Publisher : Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjit.2020.2.2.5984

Abstract

In general, Muslims regarding the distribution of inheritance and calculation procedures lack understanding and the difficulty of also getting experts in the field of inheritance distribution according to Islamic law (faraidh), this is an issue for the Muslim community, especially for heirs who want to divide inheritance according to law Islam. The author uses backward chaining methods in designing expert systems. The result of this research is the design of an expert system for dividing inheritance that can be used by the general public to help Islam solve the problem of calculation inheritance.
Customer Relationship Management Berbasis Digital pada UMKM di Desa Tengguli, Bangsri, Kabupaten Jepara Khoirya Latifah; Rahmat Robi Waliyansyah; Nugroho Dwi Saputro; Mega Novita
Indonesian Journal of Community Services Vol 4, No 2 (2022): November 2022
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/ijocs.4.2.185-192

Abstract

UMKM adalah tulang punggung perekonomian di Indonesia. Saat ini pemerentah melalui visi Presiden Jokowi sedang mencanangkan program UMKM GO Digital. Rata-rata UMKM di Desa Trengguli Bangsri Jepara saat ini masih menggunakan cara-cara yang tradisonal dalam melakukan pemasaran, penjualan dan promosi sehingga hasil yang diperoleh kurang optimal. Untuk mengatasi masalah tersebut maka Tim Pengabdi memberikan pelatihan CRM E-Commerce untuk melatih softskill dan hardskill UMKM dalam mengembangkan inovasi digitalisasi UMKM sehingga mampu menguatkan pemasaran, penjualan dan promosi. Melalui pelatihan Customer Relationship Management (CRM) UMKM diharapkan mempunyai strategi bisnis dan pemasaran serta mampu menciptakan dan memelihara hubungan yang baik dengan pelanggan dan mengurangi kemungkinan pelanggan pindah ke kompetitor lain serta meningkatkan pelayanan kepada pelanggan. Hasil dari pelatihan ini berupa peningkatan hardskill dan softskill UMKM dalam membuat fitur CRM untuk UMKM antara lain adalah mengelola data pelangan, promosi produk-produk data penjualan dan pengelolaan layanan pelanggan yang digunakan untuk menyimpan pertanyaan customer dan mengelola review produk dari pelanggan untuk menciptakan hubungan yang baik dengan customer. Dengan beberapa fitur CRM tersebut maka diharapkan akan terjadi peningkatan dan penguatan pemasaran UMKM di Desa Bangsi Jepara. Peningkatan nilai rata-rata kemampuan dan skill peserta dalam pelatihan ini mencapai 0.58 yang artinya adalah peningkatan yang bagus. Setiap peserta pelatihan mengalami peningkatan yang signifikan pengetahuan dan skill mereka dalam melakukan penjualan online.MSMEs are the backbone of the economy in Indonesia. Currently, the government, through President Jokowi's vision, is launching the MSMEs GO Digital program. The average, MSMEs in Trengguli Bangsri Jepara Village are currently still using traditional methods of marketing, selling and promotion so that the results not optimal. One of the innovations is through marketing technology using E-Commerce CRM model. Customer Relationship Management (CRM) is a marketing strategy to create and maintain good relationships with customers and reduce the possibility of customers moving to other competitors. MSMEs must implement a business strategy to improve service to customers in order to add new customers by providing different services to pamper their customers. The features of this CRM for MSMEs include managing customer data, promoting product sales data and managing customer service which is used to store customer inquiries and manage product reviews from customers to create good relationships with customers. The increase in the average value of the abilities and sklills of participant in this training reached 0.58 which means a good increase. With some of these CRM features, it is hoped that there will be an increase and strengthening of MSMEs marketing in Bangsi Village, Jepara. 
Pendampingan Pengelolaan Kampung Pancasila Berbasis IT Nur Cholifah; Suwarno Widodo; Titik Haryati; Nugroho Dwi Saputro
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 14, No 2 (2023): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v14i2.15381

Abstract

Kampung pancasila adalah kelurahan yang dijadikan contoh penerapan nilai-nilai pancasila. Pengamalan nilai-nilai pancasila sangat penting dalam segala aspek kehidupan. Pengabdian ini dilakukan di Kampung Pancasila Kota Semarang. Terbentuknya Kampung pancasila, pengamalan pancasila dihargai dalam masyarakat setempat sesuai dengan pancasila masyarakat desa yang majemuk. Mewujudkan kepribadian dan memiliki jati diri berdasarkan nilai-nilai Pancasila yang mengagungkan Bhinneka Tunggal Ika. Tujuan pengabdian adalah pengembangan Kampung pancasila berbasis IT. Setelah pendampingan manajemen dan pelatihan yang didukung IT, pengelolaan Kampung Pancasila mampu dapat merencanakan kegiatan Kampung Pancasila yang didukung IT.
Comparison of Fisher-Yates Shuffle and Linear Congruent Algorithms for Question Randomization Nugroho Dwi Saputro
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 4 No 2 (2024): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v4i2.1584

Abstract

This research aims to compare Fisher-Yates algorithm and Linear Congruent algorithm in generating random numbers or permutations. The test is conducted using the Chi-Square method to evaluate the quality of randomness generated by both algorithms. The Chi-Square value of the shuffling results is calculated and compared with the critical value of Chi-Square at a significance level of 0.05 with a degree of freedom (df) of 4, which is 9.488. The results show that the Chi-Square value for the Fisher-Yates algorithm is 3.8 and for the Linear Congruent algorithm is 4.3, both of which are below the critical value. This indicates that there is not enough evidence to reject the Null Hypothesis (H₀), implying that the difference in randomness quality between the two algorithms is not statistically significant. Therefore, both algorithms are considered to have equivalent performance. The decision to choose one of the algorithms can be based on other considerations such as complexity and efficiency. Further research is recommended to explore the performance of the algorithms under different conditions.
Comparative Analysis Of Automatic Labeling With Cohen's Kappa Validation For Cyberbullying On Tiktok Using Pre-Trained Transformers David Rian Prabowo; Khoiriya Latifah; Nugroho Dwi Saputro
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13108

Abstract

The rapid growth of TikTok users in Indonesia increases the risk of cyberbullying, making manual content moderation inefficient. This study compares two automatic labeling methods, InSet Lexicon and Zero-Shot Classification, to address the problem of limited labeled data in cyberbullying detection. A total of 5,864 comment data were collected through scraping techniques and processed through comprehensive text preprocessing stages, including slang normalization. To evaluate labeling reliability, a validation test using Cohen's Kappa Score metric was conducted against a human annotated Gold Standard of 1,141 comments. The results show that Zero-Shot Classification achieves high reliability with a Kappa score of 0.9132 (almost perfect agreement), outperforming InSet Lexicon which drops to 0.2585 (fair agreement) due to lexical rigidity and high false positives on casual slang. The automatically labeled datasets were balanced using Random Oversampling (for the Zero-Shot Classification labeling scenario) and split via a stratified 80:10:10 ratio to fine-tune IndoBERT and RoBERTa. On independent test data, IndoBERT trained on Zero-Shot labels delivers the best performance, reaching an Accuracy and F1-Score of 91.10%, outperforming RoBERTa under the same scenario (85.83%). Conversely, training on InSet Lexicon labels reduces performance, limiting IndoBERT to an 86.94% F1-Score and RoBERTa to 80.21%. This study concludes that using Zero-Shot Classification and fine-tuning IndoBERT is more optimal for application to informal social media comment moderation systems.
Co-Authors Agung Handayanto David Rian Prabowo Khoiriya Latifah, Khoiriya Khoirya Latifa Khoirya Latifah Mega Novita Nur Aksin Nur Cholifah Rahmat Robi Waliansyah Suwarno Widodo Titik Haryati Waliyansyah, Rahmat Robi