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All Journal Jurnal Algoritma Jurnal Wawasan Ilmiah Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) Jurnal Ilmu Sosial dan Ilmu Politik JOIN (Jurnal Online Informatika) Edu Komputika Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Teknologi Informasi Komunikasi dan Industri JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Elektronika dan Telekomunikasi Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMATICS Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Sistem Cerdas Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Teknika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal PkM MIFTEK Jurnal Algoritma Engineering Science Letter IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Integrated : Journal Of Information Technology and Vocational Education JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of Intelligent Systems Technology and Informatics International Journal of Applied Information Systems and Informatics
Dede Kurniadi
Institut Teknologi Garut
Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Social Sciences Other

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Perancangan Sistem Informasi Manajemen Ijazah dan Transkrip Nilai Baru di Institut Teknologi Garut Nuraeni, Fitri; Kurniadi, Dede; Hadi Wijaya, Tryana
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1395

Abstract

Submission of diplomas and grade transcripts is an important process in the management of education in tertiary institutions. However, at the Garut Institute of Technology (ITG), the process of submitting diplomas and grade transcripts is still conventional, resulting in obstacles such as long queues and difficulty accessing students who are outside the campus. To overcome these problems, this study aims to design and develop an efficient and integrated management information system for filing new diplomas and grade transcripts. The method used in this study is the Extreme Programming (XP) method. Software development is carried out by utilizing web technology and features such as validation, submission monitoring, email notifications, and submission logs. Students can apply for diplomas and transcripts online through the platform provided, fill out the online submission form, and upload the required documents. Related units, such as BAAK, Libraries, BAK, CDC, LP3B, and Study Programs, can carry out validation and verification processes online. Students can also monitor the progress of their submissions through the monitoring feature and receive notifications via email.
Perancangan Aplikasi Pengelolaan Data Penjualan dan Pemesanan di SKMart Berbasis Web Rahayu, Sri; Kurniadi, Dede; W, Faksi Ahmad
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1405

Abstract

A sales and ordering data management application is very necessary in improving performance in a company. SKMart still applies conventional methods or uses manual methods in ledgers, which is in accordance with the results of interviews with the owner that using manual methods causes the process of managing sales and ordering data, searching for data and calculating transaction data to take quite a long time, even when data loss. The aim of this research is to design a web-based sales and ordering data management application that can make it easier for shop owners to manage data, record item data and recap each transaction. With a web-based sales and ordering data management application, it is able to make it easier for users (admins) to obtain the data needed so that the process of managing sales and ordering data that occurs at SKMart stores becomes efficient. Regarding improving this application, this research uses a methodology called RUP, the stages of which are inception, elaboration, contraction and transition. Then use Unified Modeling Language modeling. The result of this research is a web-based sales and ordering data management application, which is able to facilitate the management of information data needed by users (admins) to manage goods sales data, goods ordering data, transaction data.
Aplikasi Sistem Prediksi Mahasiswa Penerima Beasiswa Berbasis Web dengan Menerapkan Model Klasifikasi K-Nearest Neighbors Kurniadi, Dede; Nuraeni, Fitri; Hazar, Aura Fitria
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1424

Abstract

The Indonesian Smart College Card Scholarship or KIP-K is one of the many scholarships provided by the government to continue their education to a higher level for students who excel but are constrained by costs. One of the universities in Garut that provides new student admissions through this scholarship route is the Garut Institute of Technology. Every year, the Garut Institute of Technology always experiences an increase in the number of KIP-K scholarship applicants, however this is not commensurate with the number of quotas obtained so a selection process must be carried out so that the scholarship can be right on target. The selection process itself is carried out manually without the help of a special system that can help select more precisely and efficiently. The aim of this research is to build a web-based prediction system application by applying the K-Nearest Neighbors classification model to help select prospective KIP-K scholarship recipients at the Garut Institute of Technology based on test scores, economic conditions, academic and non-academic achievements of each participant. The classification model is applied in the system as a process of classifying the eligibility of prospective recipients so that the selection process is more focused on participants who are categorized as eligible. The system was built using the waterfall approach method so that system development is more structured. This research produces an application in the form of a web-based prediction system that can help classify eligibility and select prospective KIP-K scholarship recipients at the Garut Institute of Technology with a system accuracy level in predicting participant eligibility of 91.86%.
Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

Abstract

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.
Bacteria Recognition Application Model Using Marker-Based Augmented Reality for Android Mobile Devices Mulyani, Asri; Kurniadi, Dede; Fadillah, Hadi Bagus
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3278

Abstract

This article aims to develop a multimedia application model for bacterial recognition using Marker-Based Augmented Reality (Marker-Based AR) technology for Android mobile devices. Marker-based tracking creates mobile augmented reality markers to increase user interaction in Marker-Based Augmented Reality systems. The software development method uses the Multimedia Development Life Cycle, which consists of 6 phases: concept, design, material collecting, assembly, testing, and distribution. The results of this study are a model of a multimedia application for bacterial recognition using Marker-Based AR, which has a marker-based tracking feature and displays bacterial objects in 3 dimensions along with their explanations and exercise questions. Based on user tests, it shows that the application model developed helps and makes it easier to learn about bacteria independently using Android mobile devices more easily and interestingly. This is proven based on beta testing towards users who got a score of 73.68% is obtained which agrees.
Improvement of Data Mining Models using Forward Selection and Backward Elimination with Cryptocurrency Datasets Julianto, Indri Tri; Kurniadi, Dede; Fauziah, Fathia Alisha; Rohmanto, Ricky
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7568

Abstract

Cryptocurrency is a digital currency not managed by a state or central bank, and transactions are peer-to-peer. Cryptocurrency is still considered a speculative asset and its price volatility is relatively high, but it is also expected to become an efficient and secure transaction tool in the future. The purpose of this study is to compare and improve the performance of the Data Mining Algorithm model using the Feature Selection-Wrapper with the Binance Coin (BNB) cryptocurrency dataset. The Feature Selection-Wrapper approach used is Forward Selection and Backward Elimination. The algorithms used are Neural Networks, Deep Learning, Support Vector Machines, and Linear Regression. The methodology used is Knowledge Discovery in Databases. The results showed that from a comparison using K-Fold Cross Validation with a value of K=10, the Neural Network Algorithm has the best Root Mean Square Error value of 10,734 +/- 10,124 (micro average: 14,580 +/- 0,000). Then after improving performance using Forward Selection and Backward Elimination in the Neural Network Algorithm, the best performance improvement results are shown by using Backward Elimination with RMSE 5,302 +/- 2,647 (micro average: 5,805 +/- 0,000). 
Enhancing Urban Waste Management: An IoT-based Automated Trash Volume Monitoring System Latifah, Ayu; Kurniadi, Dede; Sanusi, Muhammad
Jurnal Elektronika dan Telekomunikasi Vol 24, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.560

Abstract

Industrial development nowadays affects the increase in types of packaging waste which causes the accumulation of waste that has the potential to damage the environment. This research uses an Internet of Things for Automatic Waste Volume Monitoring System, so that waste management in an area can be improved. The purpose of this research is to make it easier for trashman to monitor the volume of the garbage collector on the notification feature. The research method used is the Rapid Application Development methodology with the Requirement Planning stage to analyze and identify the purpose of the system, then design the tools and system and create tools and system. Testing is used to evaluate the results of the tools and system. The result of the research is a prototype of an Internet of Things-based for Automatic Waste Volume Monitoring System tool equipped with a website-based monitoring system and for each user. Apart from that, the system which is equipped with a sensor that can detect the volume of the garbage collector is also equipped with an automatic opening and closing sensor to maintain the health of its users to provide answers to the problem of waste, especially in urban areas. Keywords: Internet of Things, Monitoring System, Waste, Waste Volume.
Algoritma K-Nearest Neighbor pada Kasus Dataset Imbalanced untuk Klasifikasi Kinerja Karyawan Perusahaan Nuraeni, Fitri; Kurniadi, Dede; Diazki, Moch Haiqal
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 3: Juni 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.938144

Abstract

Perusahaan perlu menilai kinerja karyawan mereka untuk berbagai tujuan, termasuk promosi jabatan. Namun, data karyawan yang semakin rumit dapat membuat proses penilaian ini menjadi sulit. Penelitian ini bertujuan untuk membuat model machine learning yang dapat memprediksi apakah karyawan berpotensi untuk dipromosikan atau tidak. Penelitian ini menggunakan metode Machine Learning LifeCycle (MLLC) dan algoritma K-Nearest Neighbor. Untuk mengatasi masalah ketidakseimbangan label kelas dalam dataset, teknik SMOTE (Synthetic Minority Over-sampling Technique) digunakan. Hasil dari penelitian ini, model dibangun dengan melakukan pemisahan data menggunakan cross validation dan menggunakan nilai k=2 dalam implementasi algoritma K-Nearest Neighbor. Hasil evaluasi model menunjukkan kinerja yang sangat baik dengan nilai akurasi 94%, nilai presisi 90,8%, dan nilai recall 97,4%. Selain itu, evaluasi confusion matrix menunjukkan bahwa hanya 562 dari 9377 data testing yang tidak sesuai dengan hasil klasifikasi. Model ini juga memiliki kurva ROC yang baik yang hampir menyentuh sudut kiri atas dan nilai AUC sebesar 94,1% atau 0,94 yang termasuk ke dalam kategori excellent.
Perencanaan Sistem Informasi Manufaktur Berbasis Engginering To Order dan Make To Order Mauluddin, Yusuf; Kurniadi, Dede; Abdulah, Farhan Naufal
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1393

Abstract

In fulfilling demand at PT. Garut Makmur Perkasa, the production process often experiences errors in recording and reporting, including in exchanging information between departments. This is caused by a lack of control in the recording process which still relies on manual methods and the absence of special procedures that regulate this process. Frequent errors in recording and reporting cause communication between departments to be hampered. Therefore, companies need Standard Operating Procedures (SOP) which regulate work procedures in the production process. To support this, an integrated information system is needed that can replace manual methods with digital methods. The method used in this research uses the waterfall method and SOP design uses the Cross Functional Flowchart method combined with narrative. This research only reaches the prototype stage of the manufacturing information system which was created using Canva web design simulation. This research produced a draft Standard Operating Procedure (SOP) for the production department, wetblue leather warehouse department, and finished goods warehouse department to help the company maintain employee consistency and performance. And a manufacturing information system to make it easier for employees to manage the recording process and exchange information between departments.
Aplikasi Sistem Prediksi Mahasiswa Penerima Beasiswa Berbasis Web dengan Menerapkan Model Klasifikasi K-Nearest Neighbors Kurniadi, Dede; Nuraeni, Fitri; Hazar, Aura Fitria
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1424

Abstract

The Indonesian Smart College Card Scholarship or KIP-K is one of the many scholarships provided by the government to continue their education to a higher level for students who excel but are constrained by costs. One of the universities in Garut that provides new student admissions through this scholarship route is the Garut Institute of Technology. Every year, the Garut Institute of Technology always experiences an increase in the number of KIP-K scholarship applicants, however this is not commensurate with the number of quotas obtained so a selection process must be carried out so that the scholarship can be right on target. The selection process itself is carried out manually without the help of a special system that can help select more precisely and efficiently. The aim of this research is to build a web-based prediction system application by applying the K-Nearest Neighbors classification model to help select prospective KIP-K scholarship recipients at the Garut Institute of Technology based on test scores, economic conditions, academic and non-academic achievements of each participant. The classification model is applied in the system as a process of classifying the eligibility of prospective recipients so that the selection process is more focused on participants who are categorized as eligible. The system was built using the waterfall approach method so that system development is more structured. This research produces an application in the form of a web-based prediction system that can help classify eligibility and select prospective KIP-K scholarship recipients at the Garut Institute of Technology with a system accuracy level in predicting participant eligibility of 91.86%.
Co-Authors Abania, Nia Abdulah, Farhan Naufal Abdurrahman, Fauzan Abdussalam, Iqbal Abdussalam Abdusy Syakur Amin Ade Sutedi Ade Sutedi Ade Sutedi, Ade Adiwangsa, Alfian Akmal Agus Hermawan Agus Nugraha Agustiansyah, Yoga Ahmad Habib Lutfi Aisyah Fitri Islami Ajif, Arvin Muhammad Ajiz, Rafi Nurkholiq Akbar, Gugun Geusan Alamsyah, Renaldy Aldy Rialdy Atmadja Ali Djamhuri Alisha Fauzia, Fathia Alkamal, Chaerulsyah Alvin Zainal Musthafa Alwan Nul Hakim Amrulloh, Muhammad Fawaz Andri Saepuloh Aneu Suci Nurjanah Asri Indah Pertiwi Asri Mulyani Asri Rahayu Ningsih Ayu Suryani B. Balilo Jr , Benedicto B. Balilo Jr, Benedicto Balilo Jr, Benedicto B. Barlinti Maryam Budik Burhanuddin, Ridwan Cahya Mutiara Dede Sopiah Della Adelia Anugrah Detila Rostilawati Dewi Tresnawati Dhea Arynie Noor Annisa Diar Nur Rizky Diaz Radhian Salam Diazki, Moch Haiqal Diki Jaelani Dini Destiani Siti Fatimah Diva Nuratnika Rahayu Dudy Mohammad Arifin Dyka Afan Afthori Dzikri Nursyaban Efi Sofiah Elsen, Rickard Eri Satria Erick Fernando B311087192 Erwan Yani Erwan Yani, Erwan Erwin Gunadhi Rahayu, Raden Erwin Widianto Fadillah, Hadi Bagus Faisal, Ridwan Nur Fajar Rahman Faturrohman, Nadhif Fauziah, Fathia Alisha Fauziyah, Asyifa Fikri Zakaria Rahman Firmansyah, Marshal Fitri Nuraeni Fitriani, Ranti Fitriyani Gelar Panca Ginanjar Ghilman Hasbi Basith Gisna Fauzian Dermawan H. Bunyamin Hadi Wijaya, Tryana Haekal, Mohamad Fikri Hamzah Nurrifqi Fakhri Fikrillah Hari Ilham Nur Akbar Hasfi Syahrul Ramadhan Hazar, Aura Fitria Helmalia P, Nabilla Febriani Hendri Aji Pangestu Heri Johari Heri Suhendar Heri Suhendar Hilmi Aulawi Ida Farida Ikbal Lukmanul Hakim Ikhrom, Taufik Darul Ikmal Muhammad Fadhil Ilham Muhamad Ramdan Imas Dewi Ariyanti Inda Muliana Indra Trisna Raharja Indri Tri Julianto Indri Tri Julianto Intan Sri Fatmalasari Irawan, Muhammad Randy Irfan Qusaeri Irfanov, Muhammad Irsyad Ahmad Iskandar, Joko Jajang Jaenudin Jajang Romansyah Jembar, Tegar Hanafi Khaerunisa, Nisrina Khoerunisa, Sarah Kusmayadi, Kusmayadi Latif, A. Abdul Latifah, Ayu Leni Fitriani Leni Fitriani, Leni Lia Amelia Lindayani, Lindayani M. Mesa Fauzi Mahendra Akbar Musadad Maulana , Muhammad Arief Maulana, Ahmad Rakha Maulana, Ilham Ahmad Maulana, Yusep Maulina, Wina Senja Meta Regita Mochamad Deni Ramdani Muhamad Solihin Muhammad Abdul Yusup Hanifah Muhammad Affan Al Sidqi Muhammad Rikza Nashrulloh Muhammad Saleh Muhammad Sanusi Muhammad Wildan Muliana, Inda Muttaqin, Moch Riefky Chaerul Nita Nurliawati Nugraha, M Aldi Nugraha, Nikolas Pranata Nurfadillah, Rifa Sri Nurhaliza, Nabila Putri Nurlisina, Elisa Nurpatmah, Lisna Nursa'diah, Rifania Sapta Nursyaban, Dzikri Nurul Fauziah Nurul Khumaida Nurzaman, Muhammad Zein Omar Komarudin Pratama, Reifalga Gais Prayoga, Moch. Gumelar Putri, Mita Hidayani Raharja, Indra Trisna Rahayu, Diva Nuratnika Rahayu, Raden Erwin Gunadhi Rahmat, Agil Rahmi, Murni Lestari Rajab, Ilham Syahidatul Ramdhan, Dekha Ramdhani Hidayat Randy Wardan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rifky Muhammad Shidiq Rinda Cahyana Rinda Cahyana Risfiyanisa Fasha Rizki Fauziah Roeri Fajri Firdaus Rohman, Fauza Rohmanto, Ricky Rostina Sundayana Rubi Setiawan Rudi Sutrio Safei P, M Iqbal Ismail Sarah Khoerunisa Sermana, Elsa Maharani Sheny Puspita Indriyani Siti Rima Fauziyah Sofwan Hamdan Fikri Sopiah, Dede Sri Intan Multajam Sri Mulyani Lestari SRI RAHAYU Sri Rahayu Sri Rahayu Syahrul Sidiq Syaiffani, Moch Assami Tina Maryana Undang Indrajaya W, Faksi Ahmad Wahidah, Tania Agusviani Wiwit Septiani Yanti Sofiyanti Yayat Supriatna Yoga Handoko Agustin Yosep Septiana Yosep Septiana Yuni Yuliani Yusfar Ilhaqul Choer Yusuf Mauluddin Zaqiah, Neng Nufus Zulkarnaen, Ade Iskandar