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All Journal Jurnal Informatika JURNAL SISTEM INFORMASI BISNIS TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Sarjana Teknik Informatika JUITA : Jurnal Informatika Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Teknologi dan Sistem Komputer JIEET (Journal of Information Engineering and Educational Technology) Indonesian Journal of Information System BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) JMM (Jurnal Masyarakat Mandiri) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal KOMPUTA : Jurnal Ilmiah Komputer dan Informatika GERVASI: Jurnal Pengabdian kepada Masyarakat INSIST (International Series on Interdisciplinary Research) Jurnal Informatika Global Jurnal Teknologi Terpadu bit-Tech Jurnal Abdimas Mandiri Indonesian Journal of Electrical Engineering and Computer Science Reswara: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Idealis : Indonesia Journal Information System Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Indonesian Community Journal Jurnal Teknologi Sistem Informasi Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal INFOTEL SISFOTENIKA Jurnal Teknik Informatika dan Teknologi Informasi
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Pendampingan Implementasi E-Arsip Untuk Proyek Infrastruktur Tol Gustriansyah, Rendra; Suhandi, Nazori; Puspasari, Shinta; Sanmorino, Ahmad; Wiyanto, Ari
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol 8, No 2 (2025): April 2025
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v8i2.3605

Abstract

The conventional management of archives using physical files at the Jambi-Betung II Toll Road Land Procurement Commitment Making Officer (PPK-PPTJT) agency results in slow document retrieval, a higher risk of data loss, and limited accessibility to important information. This community service initiative aims to enhance the technological skills of human resources at PPK-PPTJT Jambi-Betung II, particularly in electronic archive management. The methods employed involve socialization and technical training on using e-archive applications for four PPK-PPTJT employees. Evaluation was conducted through questionnaires and interviews to assess the participants' improvement in understanding and skills. The results demonstrated a significant increase in participants' capabilities: 25% reported a better understanding of the benefits of e-archives, 75% enhanced their operational application skills, and 25% felt more confident in managing electronic archives. The implementation of e-archives has successfully reduced reliance on physical documents and expedited the toll road land procurement administration process, ultimately increasing the operational efficiency of PPK-PPTJT Jambi-Betung II.Keywords: e-archive; mentoring; land procurement; archive management  Abstrak: Pengelolaan arsip secara konvensional dengan menggunakan berkas fisik di instansi Pejabat Pembuat Komitmen Pelaksana Pengadaan Tanah Jalan Tol (PPK-PPTJT) Jambi-Betung II menyebabkan lambatnya pencarian dokumen, rentan kehilangan data, dan terbatasnya aksesibilitas terhadap informasi penting. Tujuan pengabdian ini adalah untuk meningkatkan kapasitas sumber daya manusia di PPK-PPTJT Jambi-Betung II dalam hal digitalisasi dan pengelolaan arsip elektronik. Metode yang digunakan meliputi sosialisasi, pelatihan teknis penggunaan aplikasi e-arsip bagi empat pegawai PPK-PPTJT. Evaluasi dilakukan dengan angket dan wawancara untuk mengukur peningkatan pemahaman dan keterampilan empat peserta. Hasil evaluasi menunjukkan peningkatan signifikan: 19% peserta lebih memahami manfaat e-arsip, 31% peningkatan kemampuan operasional aplikasi, dan 25% peningkatan kepercayaan diri dalam pengelolaan arsip elektronik. Penerapan e-arsip berhasil mengurangi ketergantungan pada arsip fisik, mempercepat proses administrasi pengadaan tanah jalan tol, efisiensi ruang penyimpan, dan kemudahan monitoring dan evaluasi proses operasional PPK-PPTJT Jambi-Betung II.Kata kunci: e-arsip; pendampingan; pengadaan tanah; pengelolaan arsip
MEASURING PERCEIVED USABILITY OF ARTIFICIAL INTELLIGENCE-BASED QUIZZES IN A VIRTUAL MUSEUM Shinta Puspasari; Rendra Gustriansyah; Dwi Asa Verano; Ahmad Sanmorino; Hartini Hartini; Ermatita Ermatita
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 4 (2025): JITK Issue May 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i4.5611

Abstract

The transformation of modern museums through digital technology offers added value to visitors, especially in the context of education. Virtual museums, in particular, complement physical museums by providing accessibility and enhancing the learning experience. The SMBII virtual museum includes an AI-based quizzes feature designed to assess the knowledge level of visitors regarding the museum's history and collections as an educational feature. In addition to physical museums, virtual museums offer convenience and enrich the learning process for visitors. The quizzes adapts its questions based on the visitor's profile, leveraging AI to tailor content and maximize learning outcomes. This study aims to compare the effectiveness of two widely used usability metrics—System Usability Scale (SUS) and Usability Metric for User Experience (UMUX)—in evaluating the usability of the AI-driven quiz feature within the SMBII virtual museum. The study specifically seeks to determine whether there are significant differences between SUS and UMUX in measuring user perceptions of the quiz’s usability. The primary respondents of this study were students, who represent the museum's target audience for educational purposes. Hypothesis testing results show no significant difference between the SUS and UMUX scores (P > 0.05), indicating that both metrics offer similar evaluations of usability. Based on these findings, the study recommends the use of UMUX over SUS for future usability assessments in virtual museum systems, as UMUX is more time-efficient without compromising accuracy. This research contributes to advancing the understanding of usability testing methods for AI-based educational features in virtual museum environments
PENINGKATAN PENGETAHUAN MASYARAKAT LEWAT PEMANFAATAN APLIKASI VIRTUAL TOUR 360 MUSEUM SMBII DI MASA PANDEMI Puspasari, Shinta; Dhamayanti, Dhamayanti; Gustriansyah, Rendra; Verano, Dwi Asa; Sanmorino, Ahmad
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 4, No 1 (2023)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v4i1.2493

Abstract

Museum SMBII memiliki fungsi menyimpan, memelihara, memamerkan koleksi benda bersejarah dan budaya Palembang untuk tujuan rekreasi maupun edukasi yang dimanfaatkan seluas-luasnya bagi masyarakat khususnya kota Palembang. Namun, saat pandemi COVID-19 melanda dunia, kebijakan pemerintah daerah Palembang menetapkan museum SMBII untuk menerapkan kebijakan yang disesuaikan dengan situasi pandemi. Museum terpaksa tutup dan membatasi akses bagi aktivitas fisik di museum.  Pengelola museum SMBII telah menyediakan aplikasi untuk memudahkan masyarakat mengakses museum secara virtual. Untuk lebih memperkenalkan aplikasi tersebut, kegiatan pengenalan pemanfaatan aplikasi virtual tour 360 museum SMBII dilaksanakan dengan peserta pelajar atau mahasiswa yang merupakan kategori pengunjung dominan dari museum SMBII Palembang sebelum pandemi. Peserta dikenalkan fungsionalitas dan cara pemanfaatan tiap fitur aplikasi. Peserta diminta menggunakan aplikasi dan mengisi kuesioner evaluasi tingkat penerimaan peserta terhadap aplikasi. Hasil kuesioner menunjukkan bahwa pengetahuan peserta rata-rata meningkat dan aplikasi virtual tour 360 mudah digunakan serta meningkatkan minat peserta untuk jelajah wisata budaya Palembang
Single Exponential Smoothing Method to Predict Sales Multiple Products Gustriansyah, Rendra
International Series on Interdisciplinary Science and Technology Vol. 3 No. 2 (2018)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/ins.v3i2.176

Abstract

—Activity to predict sales multiple products intended for control of the number of existing stock, so the lack or excess stock can be minimized. When the number of sales can be accurately predicted, then the fulfilment of consumer demand can be cultivated in a timely and cooperation with suppliers maintained properly so that company can avoid losing sales and customers. This study aims to predict sales multiple products (6,877 products) using Single Exponential Smoothing (SES) approach, which is expected to improve the efficiency of the inventory system. Measurement accuracy of prediction in this study using a standard measurement Mean Absolute Percentage Error (MAPE), which is the most important criteria in analyzing the accuracy of the prediction. The results showed that the average of percentage prediction error of products using SES is high, because MAPE value obtained is 1.056% with a smoothing parameter α = 0.9
Marketing Strategy Using Frequent Pattern Growth Suhandi, Nazori; Gustriansyah, Rendra
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1039

Abstract

The biggest problem faced by printing companies during the Covid-19 pandemic was that the number of orders was unstable and tends to decrease, which had the potential to harm the company. Therefore, various appropriate marketing strategies were needed so that the number of product orders was relatively stable and even increases. The impact was that the company could survive and continued to grow. This study aimed to assist company managers in developing appropriate marketing strategies based on association rules generated from one of the data mining methods, namely the Frequent Pattern Growth (FP-Growth) method. The case study of this research was a printing company where there was no similar research that used a printing company's dataset. This study produced nine association rules that meet a minimum of 25% support and a minimum of 60% confidence, but only two association rules that had a high positive correlation, namely for a custom paper bag and banner products. Therefore, several marketing strategies were suggested that could be used as guidelines for companies in managing sales packages and giving special discounts on a product. The results of this study are expected to trigger an increase in the number of product orders because this study tried to find the right product for consumers and did not try to find the right consumers for a product.
Sosialisasi Augmented Reality Koleksi Kain Tradisional Museum Songket Palembang Puspasari, Shinta; Gustriansyah, Rendra; Sanmorino, Ahmad; Purbasari, Nadira Putri; Farhan, Muhammad
Jurnal Abdimas Mandiri Vol. 9 No. 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v9i2.5804

Abstract

Museum Songket di Palembang merupakan institusi budaya yang memiliki peran penting dalam pelestarian kain tradisional khas Sumatera Selatan, khususnya kain Songket yang kaya nilai sejarah dan estetika. Namun, metode penyampaian informasi koleksi yang masih bersifat konvensional sering kali kurang menarik bagi pengunjung, terutama generasi muda. Kegiatan Pengabdian kepada Masyarakat ini bertujuan untuk mensosialisasikan pemanfaatan teknologi Augmented Reality (AR) sebagai media interaktif dalam memperkenalkan motif-motif Songket koleksi Museum Songket Zainal dan Museum Sultan Mahmud Badaruddin II Palembang. Aplikasi AR yang dikembangkan menampilkan visualisasi motif kain berbasis marker, dilengkapi dengan deskripsi dan fitur kuis untuk mengukur pemahaman pengguna. Sosialisasi dilakukan secara langsung kepada pengunjung museum dan secara daring kepada masyarakat umum. Hasil evaluasi menggunakan instrumen System Usability Scale (SUS) menunjukkan skor rata-rata sebesar 71 dari 30 responden, yang mengindikasikan tingkat usabilitas aplikasi yang baik. Penggunaan teknologi AR terbukti mampu meningkatkan pemahaman dan minat pengunjung terhadap warisan budaya kain tradisional khusunya songket, sekaligus menjadi solusi pelestarian koleksi yang sudah rapuh tanpa kontak fisik langsung. Kegiatan ini mendorong pengelola museum untuk mempertimbangkan adopsi teknologi digital sebagai bagian dari strategi edukasi dan pelestarian budaya yang lebih adaptif di era digital. 
Klasifikasi Kelayakan Keringanan UKT Menggunakan SMOTE dan Regresi Logistik Ario Pratama, Surya; Aries Fadilla, Muhammad Bagas; Gustriansyah , Rendra
Jurnal Sarjana Teknik Informatika Vol. 13 No. 2``` (2025): Juni
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v13i2```.31084

Abstract

Keringanan Uang Kuliah Tunggal (UKT) merupakan bantuan finansial bagi mahasiswa dari keluarga berpenghasilan rendah. Namun, proses seleksi penerima sering kali menghadapi tantangan subjektivitas dan ketidakseimbangan data, yang dapat berdampak pada ketepatan keputusan. Penelitian ini bertujuan membangun model klasifikasi untuk memprediksi kelayakan mahasiswa secara objektif menggunakan algoritma Regresi Logistik dan metode penyeimbangan data Synthetic Minority Over-sampling Technique (SMOTE). Penelitian ini menggunakan pendekatan kuantitatif dengan metode supervised learning. Dataset terdiri dari 100 data, yakni 80 data latih dan 20 data uji, dengan distribusi kelas yang tidak seimbang. Evaluasi model dilakukan menggunakan confusion matrix, akurasi, presisi, recall, dan F1-score. Hasil menunjukkan bahwa model tanpa SMOTE memiliki akurasi 91,2%, presisi 95,9%, recall 90,4% dan f1-score berada 93,1%. Setelah penerapan SMOTE, model menunjukkan akurasi meningkat menjadi 92,3% dengan presisi 94,0%, recall tetap stabil di nilai yang sama dengan model latih tanpa smote, dan F1-score mencapai 92,2%. Pada data uji, model mempertahankan kinerja tinggi dengan seluruh metrik evaluasi di atas 90%, menunjukkan kemampuan generalisasi yang baik dan minim overfitting. Penerapan SMOTE terbukti efektif dalam mengatasi ketidakseimbangan kelas dan meningkatkan sensitivitas model terhadap kelas minoritas.
Analisis Perbandingan PCA-KNN dan SVM untuk Prediksi Risiko Diabetes Desfourtheen, Rinda; Damayanti, Nadia; Gustriansyah, Rendra
Jurnal Sarjana Teknik Informatika Vol. 13 No. 3 (2025): Oktober
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v13i3.31232

Abstract

Diabetes merupakan penyakit kronis yang sering terlambat terdiagnosis akibat gejala awal yang tidak spesifik, sehingga deteksi dini penting untuk mencegah komplikasi serius. Penelitian ini bertujuan menganalisis dan membandingkan performa kombinasi Principal Component Analysis dengan K-Nearest Neighbor (PCA-KNN) dan Support Vector Machine (SVM) dalam prediksi risiko diabetes. Dataset yang digunakan berasal dari Kaggle dengan 768 entri dan delapan atribut medis. Tahap praproses mencakup imputasi median untuk nilai nol, normalisasi Z-score, serta reduksi dimensi menggunakan PCA pada model KNN yang menghasilkan lima komponen utama dengan varian kumulatif >80%. Nilai k optimal ditentukan melalui 10-Fold Cross Validation dengan hasil terbaik pada k=16. Hasil evaluasi menunjukkan PCA-KNN mencapai akurasi 76,47%, sensitivitas 90,00%, dan spesifisitas 50,94%, lebih baik dibanding KNN standar. Sementara itu, SVM memperoleh akurasi 72,73% dengan spesifisitas tinggi (84,00%) namun sensitivitas rendah (51,85%). Temuan ini mengindikasikan bahwa PCA-KNN lebih sesuai untuk skrining awal karena sensitivitas tinggi, sedangkan SVM dapat digunakan pada tahap konfirmasi berkat spesifisitas yang lebih baik.
Prediksi Kualitas Susu Menggunakan Metode K-Nearest Neighbors Suhandi, Nazori; Gustriansyah, Rendra; Destria, Abel; Amalia, Marshanda; Kris, Via
SISFOTENIKA Vol. 14 No. 2 (2024): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v14i2.430

Abstract

Milk is a nutrient-rich source abundant in calcium and lactose, playing a crucial role in addressing nutritional deficiencies. Milk quality is determined by pH levels and pasteurization processes. This research aims to predict milk quality using the K-Nearest Neighbors (K-NN) Method. The analysis is conducted through a series of steps, including data preprocessing involving categorical data encoding, handling missing values, and data cleansing. Subsequently, the optimal K value is selected using the elbow method, with a value of K=3. The data is then divided into training and testing sets to avoid overfitting and validate model performance, and the testing results of using K-NN to predict milk quality are evaluated using three different data splitting schemes: 80-20, 70-30, and 60-40. By utilizing Confusion Matrix to calculate precision, recall, and accuracy, we can assess the proportion of correctly classified positive cases, accurately identified. The best accuracy result is obtained from scheme one at 0,94, with a recall of 0.8, and precision reaching 1. This research provides a significant contribution to understanding, predicting, and monitoring milk quality, encompassing a profound understanding of factors influencing milk quality and the development of advanced predictive models. Overall, this study strengthens the scientific foundation for the dairy industry comprehensively.
The Housing Recommendation System Uses Multi-Criteria Decision-Making Methods Suhandi, Nazori; Gustriansyah, Rendra
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2497

Abstract

Economic and population growth, increasing urbanization, changing habits, new welfare requirements, and lower interest rates have led to increased demand for housing in cities. However, housing conditions in many cities are slightly alarming, while housing is a primary need for the community. Selecting housing for low-income people (LIP) that meets the criteria required by LIP is not an easy task. Because most of the decisions people made did not utilize detailed information. Therefore, a recommendation system for LIP is required. This study aims to develop the housing selection recommendation system for LIP that best suits their wishes. This study integrated two multi-criteria decision-making (MCDM) methods: the Best Worst (BW) method, which has fewer pairwise comparisons compared to other MCDM methods for selecting criteria and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for determining housing recommendations for LIP according to their wishes. Based on the analysis results, ten criteria dominate the housing selection for LIP sequentially: Location, Land Size, Down Payment, Public Facilities, Price, Booking Fee, Home Design, House Specifications, House Quality, and Home Ownership Credit. Furthermore, the sensitivity analysis results showed that the robustness score of this approach was high. The model could recommend housing for LIP that best suits their wishes.