Article Per Year (5 Year)
p-Index From 2021 - 2026
2.837
P-Index
This Author published in this journals
All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Sistem Komputer Jurnal Simetris Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) JOIV : International Journal on Informatics Visualization JURNAL REKAYASA TEKNOLOGI INFORMASI IJISTECH (International Journal Of Information System & Technology) MIND (Multimedia Artificial Intelligent Networking Database) Journal Journal of Appropriate Technology for Community Services Jurnal Teknik Informatika (JUTIF) IJISTECH JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pengabdian Siliwangi International Journal of Applied Information Systems and Informatics KARISMAS - JURNAL PENGABDIAN KARYA INOVASI MASYARAKAT
Acep Irham Gufroni
Jurusan Sistem Informasi, Fakultas Teknik, Universitas Siliwangi
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
Ektraksi Fitur menggunakan Regular Expression pada Naïve Bayes Classifier untuk Analisis Sentimen GUFRONI, ACEP IRHAM; YULIYANTI, SITI; DEWI, EUIS NUR FITRIANI
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 8, No 2 (2023): MIND Journal
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v8i2.230-241

Abstract

AbstrakRegular expression atau regex merupakan metode ekstraksi fitur yang menemukan substring pada sebuah teks yang cocok dengan harapan dapat meningkatkan kompleksitas waktu atau akurasi dengan melakukan preprocessing teks. Permasalahan praproses teks salah satunya kurang memperhatikan ektraksi fitur untuk proses klasifikasi sentiment, sehingga akurasi yang diperoleh kurang optiomal. Inovasi utama dari pendekatan penelitian ini yaitu mengembangkan pengklasifikasi teks berbasis ekspresi reguler sehingga menghasilkan performance kinerja algoritma yang baik. Tahapan penelitian ini, yaitu pengumpulan dataset lalu mengklasifikasikan sentiment dengan Naïve Bayes dan dalam praproses teks dilakukan ektraksi fiitur regular expression. Hasil rata-rata akurasi yang dihasilkan dengan ekstraksi ciri sebesar 88,05% dan yang tidak menggunakan 79,26% sehingga dapat disimpulkan bahwa penggunaan ekstraksi fitur pada praproses dapat meningkatkan akurasi sebesar 8,08% dari 1000 data latih dan 400 data uji. Kata kunci: ekstraksi fitur, regex, regular expression, substringAbstractRegular expression or regex is a feature extraction method that finds matching substrings in a text in hopes of increasing time complexity or accuracy by preprocessing the text. One of the problems with text preprocessing is the lack of attention to feature extraction for the sentiment classification process, so the accuracy obtained is not optimal. This research stage begins with collecting a dataset and then classifying sentiment using Naïve Bayes, which pre-processes the text by extracting features with regular expressions. The main innovation of this research approach is to develop a text classifier based on regular expressions so as to produce good algorithm performance. The average accuracy produced by feature extraction is 88.05% and 79.26% is not used, so it can be concluded that the use of feature extraction in pre-processing can increase accuracy by 8.08% from 1000 training data and 400 test data.Keywords:  extraction feature, regex, regular expression, substring
Pengembangan Sistem Pengukur pH Air Untuk Menentukan Derajat Asam Basa Media Kolam Ikan Berbasis Internet of Things (IoT) Ramdani, Cecep Muhamad Sidik; Gufroni, Acep Irham; Rachman, Andi Nur; Shofa, Rahmi Nur
CESS (Journal of Computer Engineering, System and Science) Vol 9, No 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.50799

Abstract

Bidang fisika dapat mempengaruhi keberlangsungan segala sesuatu yang hidup di lingkungan alam secara langsung atau tidak langsung, salah satunya berpengaruh pada kegiatan budidaya ikan. Kualitas air sangat berpengaruh pada kondisi ikan sehingga apabila kualitas air nya tidak memenuhi standar air untuk budidaya ikan, maka akan membuat ikan rawan terserang penyakit bahkan bisa menyebabkan kematian. Ada beberapa parameter yang dapat mempengaruhi kualitas air, diantaranya Ph air. Alat yang digunakan untuk mengukur Ph air yaitu Ph meter. Alat tersebut harus secara langsung di gunakan di lokasi media kolam ikan untuk dapat mengetahui nilai suhu dan Ph air. Dengan kondisi tersebut membuat kegiatan monitoring kolam ikan menjadi kurang efektif dan efisien. Untuk mengatasi hal tersebut maka dibuat suatu sistem monitoring Ph air berbasis Internet of Thing (IoT) yang dapat melakukan pemantauan dan monitoring kolam ikan secara real time. Pada monitoring Ph air ini menggunakan sensor PH-4502C. mikrokontroler yang digunakan yaitu NodeMCU ESP8266 dan Arduino Uno yang di lengkapi dengan Wi-Fi module ESP8266. Hasil pengujian yang di lakukan di tiga titik pada satu kolam ikan dalam rentang waktu 1 jam mempunyai nilai rata-rata 7,56 yang berarti nilai Ph air yang ada pada kolam tersebut masih sedikit di atas batas normal yaitu 7.  
Implementation of Ensemble Machine Learning Classifier and Synthetic Minority Oversampling Technique for Sentiment Analysis of Sustainable Development Goals in Indonesia Gufroni, Acep Irham; Hoeronis, Irani; Fajar, Nur; Rachman, Andi Nur; Sidik Ramdani, Cecep Muhamad; Sulastri, Heni
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.1949

Abstract

As part of the Sustainable Development Goals (SDGs), governments worldwide have committed to improving people's lives to improve the quality of life for all, including the 17 such goals that were agreed upon in 2015 to benefit the human race as a whole. It would be interesting to see how society responds to the SDGs after approximately half of them have been achieved. This public response was analyzed in terms of sentiment. Within the total number of internet users in Indonesia, there are 18.45 million Twitter users. The platform enables anyone to write about anything they are experiencing in their lives, such as what is happening in their environment, what is happening in their education system, what is happening in the food industry, how people feel, and many more. The platform enables anyone to write about anything they are experiencing in their lives, such as what is happening in their environment, what is happening in their education system, what is happening in the food industry, how people feel, and many more. To model the data collected, the researchers used Ensemble Machine Learning Classifiers (EMLC) to model the data by using a machine learning classifier that uses machine learning techniques. The best model in this study is EMLC-Stacking with a data splitting of 80:20 and using SMOTE, which obtains an accuracy of 91%. This accuracy results from a 5% increase compared to when not using SMOTE. From 15,698 tweets, this research found that 47% were positive sentiments, 28% were negative sentiments, and 25% were neutral sentiments. The results that we measured offer hope that there will be a positive trend in the journey of the SDGs until 2030 if these findings are true.
Academic Performance Prediction Using Supervised Learning Algorithms in University Admission Gufroni, Acep Irham; Purwanto, Purwanto; Farikhin, Farikhin
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2974

Abstract

Each educational institution has designed an academic system with the aim of providing as perfect learning as possible to students. The quality of good students is influenced by various factors, one of which is the available academic system. Previous research has shown that the quality of a student, which can be called academic achievement, can be determined through historical data on the student admission process. This research aims to process one of the admission processes previously implemented in Indonesian state universities using the National Selection for State University Entrance (SNMPTN) data, combined with Cumulative Achievement Index (GPA) data, so that it can be processed using a machine learning model. The algorithm used to create the model is a Supervised Learning Classification algorithm, which includes a Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB). The research was carried out in three schemes based on the percentages of training data and test data. The results obtained show that DT produces the highest accuracy and precision values, with an accuracy value of 0.79 and a precision value of 0.56, respectively. The XGB produces the highest recall and f1-score values, with a recall value of 0.35 and an f1-score value of 0.36. The model with the highest f1-score can be selected as the best model, namely, the model with the XGB algorithm on a 70%-30% train-test data scheme. The resulting model achieved a success rate of 77%.
Rancang Bangun Game Edukasi "Dinosawr" Berbasis Android Menggunakan Unity 3D Aemy, Nandhitta; Dewi, Euis Nur Fitriani; Gufroni, Acep Irham
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 13, No 1 (2025)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v13i1.78990

Abstract

Dalam era teknologi yang terus berkembang, perangkat mobile menjadi pendorong utama perubahan, khususnya dalam konteks penggunaan oleh anak-anak untuk bermain game. Melihat tren ini, dilakukan upaya untuk menggabungkan aspek hiburan dan pembelajaran melalui game edukatif Android dalam proyek "Dinosawr" yang menggunakan platform Unity 3D. Tujuan dari pengembangan game ini adalah untuk memberikan alternatif bermain yang tidak hanya menghibur tetapi juga memberikan nilai edukatif yang signifikan. Proyek ini melibatkan desain antarmuka pengguna yang responsif, pengembangan konten edukatif tentang dinosaurus, pengujian menyeluruh, dan evaluasi kinerja game. Melalui pengujian blackbox, permainan ini terbukti efektif dalam menghadirkan pengalaman edukatif yang menarik dan menyenangkan bagi anak-anak. Dengan menggunakan metode Game Development Life Cycle (GDLC), upaya dilakukan untuk menciptakan pengalaman bermain yang interaktif dan mendidik, menghasilkan solusi inovatif bagi pembelajaran berbasis game di era digital. Secara keseluruhan, penelitian ini memberikan kontribusi pada pengembangan game edukasi, dengan rekomendasi untuk perbaikan dalam aspek konten, antarmuka, serta perluasan platform untuk menjangkau audiens yang lebih luas.
PENERAPAN METODE ASSOCIATION RULE MINING PADA DATA TRANSAKSI PENJUALAN PRODUK KARTU PERDANA KUOTA INTERNET MENGGUNAKAN ALGORITMA APRIORI Baetulloh, Uci; Gufroni, Acep Irham; -, Rianto
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 1 (2019): JURNAL SIMETRIS VOLUME 10 NO 1 TAHUN 2019
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (845.283 KB) | DOI: 10.24176/simet.v10i1.2890

Abstract

Data transaksi penjualan produk kartu perdana kuota internet dapat dijadikan sebagai bahan acuan untuk mengetahui seberapa besar tingkat penjualan produk yang telah dipasarkan oleh beberapa operator telekomunikasi seluler. Data tersebut tidak hanya dijadikan sebagai data arsip penyimpanan laporan penjualan perusahaan saja, tetapi dapat dianalisa dan dimanfaatkan menjadi sebuah informasi untuk membantu dalam melakukan pengembangan strategi pemasaran produk. Tujuan dari penelitian ini yaitu untuk menemukan aturan asosiasi kombinasi antar item produk operator telekomunikasi seluler mana saja yang paling laku terjual di wilayah penjualan Priangan Timur meliputi cluster Ciamis, Garut dan Tasikmalaya. Perhitungan Algoritma Apriori pada aturan asosiasi ini dihitung melalui tiga tahap iterasi pembentukan kandidat k-itemset. Hasil analisa aturan asosiasi yang terbentuk dari perhitungan algoritma apriori dengan menentukan nilai minimum support 35% dan nilai minimum confidence 80%, menghasilkan 9 aturan asosiasi final terbaik pada cluster Ciamis, 21 aturan asosiasi final untuk cluster Tasikmalaya dan 7 aturan asosiasi final untuk cluster Garut. Ketiga wilayah penjualan tersebut produk yang paling sering laku terjual dipasaran outlet adalah produk dari operator kartu kuota internet XL dengan Telkomsel dan produk Indosat dengan Telkomsel. Dengan demikian hasil yang diperoleh dapat digunakan untuk membantu pengambil keputusan dalam meningkatkan penjualan produk yang lebih baik
Sistem Informasi Pengolahan Data Nilai Raport Terintegrasi di PAUD Rachman, Andi Nur; Gufroni, Acep Irham; Sulastri , Heni; Dewi , Euis Nur Fitriani
Journal of Appropriate Technology for Community Services Vol. 6 No. 1 (2025)
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/jattec.vol6.iss1.art10

Abstract

Developments in technology and science have had a big effect on life, including in the field of education. Many schools from high school, middle school, elementary school, even kindergarten or PAUD are developing themselves to provide quality learning or educational services by implementing computer-based information systems. The current problem is that the recording of report card scores as a child's development is done manually or written in a report card, this makes it difficult to find out the child's development graph. So there is a need for a system that helps facilitate the assessment of report cards and progress charts preschool children's education. The method used in this service is a descriptive research design method. Service activities in the system development process that will be proposed are the waterfall method. An integrated report card data processing information system to make things easier for PAUD schools. The information system makes things easier for students or parents in checking report scores via the website..
Pengembangan Sistem Pengukur pH Air Untuk Menentukan Derajat Asam Basa Media Kolam Ikan Berbasis Internet of Things (IoT) Ramdani, Cecep Muhamad Sidik; Gufroni, Acep Irham; Rachman, Andi Nur; Shofa, Rahmi Nur
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.50799

Abstract

Bidang fisika dapat mempengaruhi keberlangsungan segala sesuatu yang hidup di lingkungan alam secara langsung atau tidak langsung, salah satunya berpengaruh pada kegiatan budidaya ikan. Kualitas air sangat berpengaruh pada kondisi ikan sehingga apabila kualitas air nya tidak memenuhi standar air untuk budidaya ikan, maka akan membuat ikan rawan terserang penyakit bahkan bisa menyebabkan kematian. Ada beberapa parameter yang dapat mempengaruhi kualitas air, diantaranya Ph air. Alat yang digunakan untuk mengukur Ph air yaitu Ph meter. Alat tersebut harus secara langsung di gunakan di lokasi media kolam ikan untuk dapat mengetahui nilai suhu dan Ph air. Dengan kondisi tersebut membuat kegiatan monitoring kolam ikan menjadi kurang efektif dan efisien. Untuk mengatasi hal tersebut maka dibuat suatu sistem monitoring Ph air berbasis Internet of Thing (IoT) yang dapat melakukan pemantauan dan monitoring kolam ikan secara real time. Pada monitoring Ph air ini menggunakan sensor PH-4502C. mikrokontroler yang digunakan yaitu NodeMCU ESP8266 dan Arduino Uno yang di lengkapi dengan Wi-Fi module ESP8266. Hasil pengujian yang di lakukan di tiga titik pada satu kolam ikan dalam rentang waktu 1 jam mempunyai nilai rata-rata 7,56 yang berarti nilai Ph air yang ada pada kolam tersebut masih sedikit di atas batas normal yaitu 7.  
Implementation of the Naive Bayes Classifier for Sentiment Analysis of Shopee E-Commerce Application Review Data on the Google Play Store Rizkya, Adilia Tri; Rianto, Rianto; Gufroni, Acep Irham
Journal of Applied Information System and Informatic (JAISI) Vol 1, No 1 (2023): November 2023
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v1i1.8993

Abstract

E-commerce in Indonesia is growing very quickly every year. The Ministry of Communication and Information (KEMKOMINFO) stated that Indonesia is the 10th largest e-commerce growth country with score 78%. One of the effects from increasing number of internet users in Indonesia is the mushrooming of shopping activities through internet media. This causes internet users want everything that instant and easy. Knowing this, most business people use it to market their products, especially in the field of goods and services. As it grows, e-commerce becomes easier to use and download. One example of an e-commerce application that is in great demand is Shopee and can be downloaded via the Google Play Store. Google Play Store has a review feature which contains user comments about the downloaded apps. Sentiment analysis is carried out to extract information related to Shopee E-commerce. The Naïve Bayes Classifier algorithm is suitable for use in sentiment analysis because this algorithm is purposeful as a classification method into positive and negative categories. The data was used from November 2022 to January 2023. From a total of 4902 review data obtained, after going through preprocessing, translation and then classification, the total data is obtained that is 4849 review data. From the data obtained it is classified 2348 positive reviews, 1259 neutral reviews, and 1242 negative reviews. Based on the results of the naive Bayes classifier method and testing with the confusion matrix, an accuracy value of 79% has been obtainednprecision 77%, recall 86%, and f1-score 81% on positive sentiment with support 2127. For neutral sentiment with an accuracy value of 83%, precision 87%, and recall 85% with support 1209, while for negative sentiment is with an accuracy value of 78%, precision 64%, and recall 70% with support 1513. From this data it is obtained micro AVG values for precision 80%, recall 79%, f1-score 79%, and support 4849, then for weighted average for precision 79%, recall 79%, f1- score 79%, and support 4849.
Analysis of Information Technology Governance in the SaData-Ku Application at the Kuningan Regency Regional Development Planning, Research and Development Agency (BAPPEDA) Using the COBIT 2019 Framework Pratama, Eneng Kurnia Dewi; Gufroni, Acep Irham
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 1 (2024): Mei 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i1.11008

Abstract

Currently, the success and continuity of a company or organization is very much based on IT, in terms of speed and results that can help increase the effectiveness and efficiency of business processes to achieve goals. In its implementation, the Regional Development Planning, Research and Development Agency (BAPPEDA) of Kuningan Regency encountered problems with the SaData-Ku application, errors occurred when inputting data (system failure to operate), there was a risk that when collecting data there was a delay from the predetermined schedule, the operation of the application was limited in time. for data input, resulting in bugs in the application. This problem has a negative impact on the continuity of the development planning process and can reduce the quality performance of information technology. To overcome this, application users need learning and growth to become more proficient in the field of information technology, thereby reducing difficulties in dealing with sudden changes or disruptions to applications. These problems can be identified thoroughly with governance using the COBIT 2019 framework. The form and content of the COBIT 2019 model are updated from the previous COBIT method and many new functions are added, including enabling improvements to the IT governance system. By conducting analysis, you can provide recommendations to improve the organization's capabilities to meet the agency's expectations and goals regarding IT governance in supporting its performance. The COBIT 2019 domains used are APO and DSS with details of the APO07, APO12, APO14 and DSS01 processes. The results of measuring the capability level of the APO07 domain at the Kuningan Regency Regional Development Planning, Research and Development Agency (BAPPEDA) got a capability level 4 value, the APO12, APO14 and DSS01 domains got a capability level 5 value.
Co-Authors -, Rianto Aemy, Nandhitta Andi Nur Rachman Andi Nur Rachman Andi Nur Rachman Andi Nur Rachman Anshary, Muhammad Adi Khairul Aradea Baetulloh, Uci Baetulloh, Uci Busaeri, Nundang Cecep Muhamad Sidik Ramdani Cecep Muhamad SR Dewi , Euis Nur Fitriani Dewi, Euis Nur Fitriani Euis Nur Fitriani Dewi Fazamin Bin Wan Hamzah, Wan Mohd Amir Fransiska, Susanti Genta Nazwar Tarempa Gina Rahmayati Glaudira, Nadya Heni Sukmawati Heni Sulastri Heni Sulastri Irani Hoeronis Juwanda, Farikhin Miftahul Habib Fachrurozi Millah, Haikal Nanda Adi Pamungkas Nur Fajar Nurul Hiron Nurul Hiron Nurul Hiron, Nurul Pratama, Eneng Kurnia Dewi Purwanto Purwanto R. Reza El Akbar Rachman, Andi Nur Rahmi Nur Shofa Rahmi Nur Shofa Rahmi Nur Shofa Ramdani, Cecep Muhamad Sidik Rianto Rianto Rianto, Rianto Riza Lukmanulhakim Rizkya, Adilia Tri Ruswati, Ruswati Ruswati, Ruswati Shofa, Rahmi Nur Sidik Ramdani, Cecep Muhamad Siti Yuliyanti, Siti Sukmawati, Heni Sulastri , Heni Sulastri, Heni Wisandani, Iwan Yahya, Aria Priawan Yaya Abdul Malik