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All Journal Jurnal Inovasi Teknologi Pendidikan Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Applied Engineering and Technological Science (JAETS) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Inspiration: Jurnal Teknologi Informasi dan Komunikasi SmartComp
Panggabean, Supriadi
Universitas Darunnajah
Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Neuroscience Social Sciences Transportation

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Implementasi Algoritma Dijkstra Untuk Menentukan Jalur Terpendek Wilayah Pasar Minggu Dan STMIK Nusamandiri Jakarta Supriadi Panggabean; Windu Gata; Arief Rama Syari; Siska Rahmadan; Tetra Widianto
Swabumi Vol 9, No 1 (2021): Volume 9 Nomor 1 Tahun 2021
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v9i1.9574

Abstract

Banyaknya urbanisasi penduduk membuat wilayah Jakarta menjadi sangat padat. Kepadatan tersebut sangat berpengaruh dengan kemacetan lalu lintas di Jakarta. Banyak cara yang sudah dilaksanakan oleh pemerintah DKI Jakarta untuk mengatasi masalah kemacetan. Akan tetapi, kemacetan tetap saja masih terjadi. Maka sebagai pengguna jalan harus mencari cara untuk mengatasi masalah tersebut. Salah satu cara yang efektif untuk digunakan adalah mencari rute alternatif terpendek yang dilalui dengan menggunakan Algoritma Dijkstra. Pemanfaatan Algoritma Dijkstra dapat digunakanan untuk menyelesaikan masalah ini karena Algoritma Dijkstra memberikan output berupa jalur terpendek dan tercepat dari dari titik awal menuju titik tujuan. Hasil pencarian rute terpendek antara kawasan Pasar Minggu dengan rute STMIK Nusa Mandiri Kramat Jakarta telah ditemukan yaitu rute ketiga dengan jarak tempuh 14,8 km.Kata Kunci: Algoritma Dijkstra, implementasi, Rute terpendek.
Analisa faktor penentu penerimaan dan penggunaan aktual mahasiswa terhadap sistem e-Learning Siska Rahmadani; Agus Salim; Supriadi Panggabean; Dwiza Riana
Jurnal Inovasi Teknologi Pendidikan Vol 8, No 2 (2021): Oktober
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (477.318 KB) | DOI: 10.21831/jitp.v8i2.38886

Abstract

Sistem pembelajaran online melalui media e-learning merupakan solusi agar kegiatan belajar mengajar tetap terjaga selama pandemi. Agar penerapan dalam penggunaan sistem e-learning berhasil, perlu diperhatikan faktor-faktor yang dapat mempengaruhi penerimaan sistem tersebut. Penelitian ini bertujuan untuk mencari faktor utama yang mempengaruhi penerimaan dan penggunaan aktual sistem e-learning pada mahasiswa. Metode yang digunakan diadopsi dari model Unified Theory of Acceptance and Use of Technology (UTAUT) ditambah variabel baru yaitu course design, course content support, course assessment, dan instructor characteristics. Analisa data menggunakan SmartPLS dengan model PLS-SEM. Dari hasil penelitian course content support, course assessment, dan behavioral intention to use mempunyai pengaruh signifikan terhadap actual use sistem e-learning. Course design, course content support, dan course assessment mempunyai pengaruh signifikan terhadap performance expectancy, dan yang mempunyai pengaruh signifikan terhadap behavioral intention to use dari sistem e-learning adalah performance expectancy dan social influence. Penelitian ini bisa digunakan sebagai bahan referensi bagi perguruan tinggi untuk meningkatkan penerimaan dan penggunaan sistem e-learning.Analysis of determinants of acceptance and actual use of students e-learning systemsAbstractThe online learning system through e-learning media is a solution to maintain teaching and learning activities during the pandemic. In order for the application in the use of e-learning systems to be successful, it is necessary to consider the factors that can affect the system's acceptance. This study aims to find the main factors that influence students' acceptance and actual use of e-learning systems. The method used was adapted from the Unified Theory of Acceptance and Use of Technology (UTAUT) model plus new variables, namely course design, course content support, course assessment, and instructor characteristics. Data analysis using SmartPLS with PLS-SEM model. From the research results, course content support, course assessment, and behavioral intention to use significantly influence the actual use of the e-learning system. Course design, course content support, and course assessment have a significant influence on performance expectancy, and those that have a significant influence on behavioral intention to use the e-learning system are performance expectancy and social influence. This research can be used as reference material for universities to increase the acceptance and use of e-learning systems.
Analysis of Twitter Sentiment Towards Madrasahs Using Classification Methods Supriadi Panggabean; Windu Gata; Tri Agus Setiawan
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v4i1.1088

Abstract

In today's digital era, the influence and use of the internet has become a necessity, especially in Indonesia itself, internet users in early 2021 reached 202.6 million people. The most widely used internet use by Indonesians is social media. Several incidents of sexual violence that occurred in the madrasa environment as reported in the media, the emergence of radical Islamic issues which he said were the fruit of thoughts from the madrasa environment, terrorism which was also said to come from misinterpreting knowledge from madrasahs, intolerance to different religions, changes in the character of madrasah students and so on will cause negative thoughts towards madrasah. To find out how the sentiment of social media users towards madrasahs, a study was conducted on analisis twitter sentiment towards madrasah using the classification method. The methods used are Naïve Bayes (NB), Decision Tree (DT) and K – Nearest Neighbor (K-NN). Toimprove the performance of the classification method is carried out using the Particle Swarm Optimization (PSO) selection feature. On the other hand, tools gataframework, execute Python script dan rapidminer diguna kan jug a dalam penelitian this to membantu preprocessi ng dan cleansing pa da datasethingga membantu menciptaka n corpus dan sentiment ana lysis. Acuration obtained from the Naïve Bayes algorithm accuracy: 76.86% +/- 5.24% (micro average: 76.86%), Decision Tree accuracy: 61.38% +/- 5.46% (micro average: 61.35%), K-NN accuracy: 74.70% +/- 4.83% (micro average: 74.67%), Naïve Bayes PSO accuracy: 80.80% +/- 4.86% (micro average: 80.79%, Decision Tree PSO accuracy: 65.27% +/- 5.26% (micro average: 65.28%), and K-NN PSO accuracy: 67.24% +/- 7.92% (micro average: 67.25%). The results showed that the Naïve Bayes PSO algorithm got the best and accurate results. This study succeeded in obtaining an effective and best algorithm in classifying positive comments and negative comments related to sentiment analysis towards madrasahs by classification method.
Perbandingan Prediksi Harga Saham Dengan Menggunakan LSTM GRU Dengan Transformer Idham Idham; Muhammad Ghudafa Taufik Akbar; Supriadi Panggabean; Mohamad Noor
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 11, No 1 (2022): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v11i1.3185

Abstract

Saham adalah sebuah bukti kepemilikan nilai sebuah perusahaan, artinya pemilik saham adalah pemilik perusahaan . Semakin besar saham yang dimiliki, maka semakin besar kekuasaannya di perusahaan tersebut. Faktor yang terjadi sekarang dalam sektor pasar saham yaitu adanya dampak dari virus corona terhadap indeks harga saham dan arus dana asing ke pasar saham. Maka sangat perlu untuk dilakukan prediksi sentiment analysis pandemi corona terhadap sektor pasar saham untuk melihat bagaimana perbandingan pergerakan IHSG di Indonesia sebelum terjadi pandemi dan pada saat terjadi pandemi Covid-19. Metode yang digunakan untuk prediksi analysis sentimen dengan index harga saham Indonesia ini menggunakan transformers dengan fitur bag of word , TF- IDF dan word embedding. Dari hasil prediksi sebelum menggunakan metode transformers pada LSTM,dan GRU didapatkan rata-rata pada LSTM Performance akurasi 0,394 dan GRU 0,216[1]. Algoritma yang yang digunakan dalam model ini adalah Long short-term memory (LSTM), dan Gated Recurrent Unit (GRU), sedangkan untuk mendapatkan hasil word embedding menggunakan Vector space model. Terdapat 1989 baris data dan 27 atribut, sedangkan untuk akurasi yang dihasilkan setelah melakukan iterasi beberapa kali mendapatkan hasil yang signifikan, performance yang dihasilkan adalah semakin mendekati akurasi yang cukup tinggi. Berdasarkan hasil eksprimen perbandingan performance akurasi antara LSTM dan GRU terhadap penggunaan Transformers, maka terlihat lebih baik performance akurasinya setelah menggunakan transformers pada ketiga model tersebut.Kata kunci: Transformer, GRU, LSTM, TF-IDF, word embedding, bag of word..
Evaluasi User Experience Situs Web Perguruan Tinggi Menggunakan User Experience Questionnaire: Studi Kasus Universitas Darunnajah Faishal Wafiq Zakiy; Supriadi Panggabean; Wahyu Joko Saputro
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 3 (2024): Juni 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i3.7629

Abstract

Abstrak - Penelitian ini bertujuan untuk mengevaluasi tingkat kepuasan pengguna terhadap situs web Universitas Darunnajah (UDN) dengan menggunakan metode User Experience Questionnaire (UEQ) yang meliputi enam dimensi pengalaman pengguna. Data dikumpulkan melalui kuesioner yang disebarkan kepada mahasiswa aktif Universitas Darunnajah serta melalui wawancara dengan staf akademik. Hasil evaluasi menunjukkan bahwa situs web UDN mendapatkan kategori di bawah rata-rata menurut kriteria UEQ. Oleh karena itu, penelitian ini memberikan landasan penting untuk pengembangan situs web yang lebih sesuai dengan kebutuhan pengguna, dengan harapan dapat meningkatkan pengalaman dan kepuasan pengguna dalam menggunakan situs web tersebut. Evaluasi rutin seperti ini sangat diperlukan agar situs web UDN dapat terus memenuhi ekspektasi pengguna dan berkembang sesuai dengan kebutuhan mereka.Kata kunci: User Experience, User Experience Questionnaire, Universitas Darunnajah, Situs web Abstract - This research aims to evaluate user satisfaction with the Universitas Darunnajah (UDN) website using the User Experience Questionnaire (UEQ) method, which encompasses six dimensions of user experience. Data were collected through questionnaires distributed to active students of Universitas Darunnajah and through interviews with academic staff. The evaluation results indicate that the UDN website falls below average according to the UEQ criteria. Therefore, this research provides a critical foundation for developing a website that better meets users' needs, with the hope of enhancing user experience and satisfaction with the website. Routine evaluations like this are essential for ensuring that the UDN website continues to meet user expectations and evolves according to their needs.Keywords: User Experience, User Experience Questionnaire, University of Darunnajah, Website
Sentimen Analisis dengan Long Short-Term Memory dan Synthetic Minority Over Sampling Technic Pada Aplikasi Digital Perbankan Ahmad, Ali; Gata, Windu; Panggabean, Supriadi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 4 (2024): OCTOBER-DECEMBER 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i4.2320

Abstract

In recent years, we have witnessed significant growth in digital banking transactions, supported by technological advancements. According to the latest data from the FinTech Association of Indonesia, digital banking transactions in Indonesia have increased by 35% from the previous year. In this context, the development of digital banking applications becomes increasingly important. However, to ensure the quality and success of these applications, feedback from users is crucial. One technique used by banks is sentiment analysis to gather feedback on their digital applications. This research aims to analyze user sentiment for two banking applications, DbankPro and M-BCA, through reviews on the Google Playstore. The method used is CRISP-DM, implementing the "Imbalance Data Handling with SMOTE" technique and LSTM model. The test results show the accuracy of sentiment analysis for M-BCA is 91.07%, while for DbankPro it is 89.82%. The implications of this research emphasize the importance of paying attention to user feedback in the development of digital banking applications to enhance their quality and meet user expectations
Time Effort Prediction Of Agile Software Development Using Machine Learning Techniques Muchamad Bachram Shidiq; Gata, Windu; Kurniawan, Sigit; Saputra, Dedi Dwi; Panggabean, Supriadi
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 2 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i2.57

Abstract

To run a software development project, an effective and efficient project management mechanism is needed to coordinate the activities carried out. The agile method was developed because there are several weaknesses in the classic method that can interfere with the course of the software development process according to user desires.  However, in applying agile methods, time effort estimation cannot be done properly. This can cause project managers to have difficulty preparing resources in software development in scrum projects. For this reason, this research aims to predict the time effort of agile software development using Machine Learning techniques, namely the Decision Tree, Random Forest, Gradient Boosting, and AdaBoost algorithms, as well as the use of feature selection in the form of RRelieff and Principal Component Analysis (PCA) to improve prediction accuracy. The best-performing algorithm uses Gradient Boosting k-fold validation with PCA with an MSE value of 2.895, RMSE 1.701, MAE 0.898, and R2 0.951.
Darunnajah Vote System Application Design Using PHP Programming Language Panggabean, Supriadi; Wahyu Joko Saputro; Faishal Wafiq Zakiy; Tutik Lestari; Ahmad Rifqi
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 2 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i2.61

Abstract

Voting is the most important part of choosing leaders in an organization or institution, especially for those of us who use a democratic system. The election of organizational leaders in Darunnajah is still carried out conventionally, elections still use paper to select organizational leaders which is carried out by recording and counting the name or picture of one of the candidates. Creating the Darunnajah Vote System in the form of a web application for the election of organizational leaders in the Darunnajah environment can speed up the voting process. The web application is built using PHP and MySQL with features of user management, class management, candidate management, and E-Voting. This study aims to build an e-voting system that is expected to provide voting results quickly, and accurately and can be monitored in real-time during the implementation of the leader election. This system development method uses a web application-based SDLC Waterfall model. Testing using the black box method, every feature contained in the Darunnajah Vote System application, namely the Admin Login feature, User Login, User Voting, and User Data Processing features runs normally and functions properly.
Analyzing Student Academic Achievement Using Machine Learning Techniques at Senior High School Darunnajah Jakarta Panggabean, Supriadi; Wahyu Joko Saputro
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 14 No. 1 (2024): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v14i1.81

Abstract

Education provides a very important role in improving the quality of life in society in a country. With a large number of students in each class, it can cause the material to not be delivered properly. Therefore, it is necessary to group students based on their learning ability. The data used was obtained from Senior High School (SMA) Darunnajah Jakarta. Darunnajah High School Jakarta is one of the educational institutions under the auspices of Darunnajah Islamic Boarding School. Data mining techniques with classification methods are proposed to predict student performance in class. The results of student classification can be used as a reference in providing material according to their learning ability. The aim of this research is to ascertain the optimal classification algorithm and pinpoint the key factors influencing students' academic standing. Various classification methods, including logistic regression, KNN, and SVM, were employed in this study. The performance of these models was assessed using diverse metrics such as the f1 score, ROC curve, and performance matrix. Ultimately, the SVM algorithm demonstrated the highest accuracy, achieving an 84% accuracy rate compared to KNN and logistic regression.
Comparative Study of Naive Bayes Data Mining, Decision Tree C4.5 And Fuzzy Decision Tree (ID3) In Analyzing the Financing of Fitness Center Memberships: Case Study PT Fitindo Sehat Sempurna Saputro, Wahyu Joko; Panggabean, Supriadi; Zakiy, Faishal Wafiq
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 6 (2024): Desember 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i6.8176

Abstract

Abstract - The business world is always experiencing rapid changes, so it requires companies to be able to respond to these changes quickly and precisely. PT. Fitindo Sehat Sempurna as a company engaged in fitness services wants to do data mining to predict the smooth financing of its members and strive to increase sustainable sales turnover. One of the classification algorithms that is often used and gets a lot of attention from researchers in predicting problematic financing is Naive Bayes, Decision Tree C4.5 and then tries to compare it with the Fuzzy Decision Tree (ID3). Of all the trials of the three methods, the best results were obtained, namely Naive Bayes with the highest calculation result of accuracy of 85,00% and AUC = 0,960 as the best results. This test uses 80 training data and 20 testing data.Keywords: Financing, Membership, ID3, Fuzzy, Decision Tree, C4.5, Naive Bayes. Abstrak - Dunia bisnis selalu mengalami perubahan yang cepat, sehingga menuntut perusahaan untuk dapat merespon perubahan tersebut dengan cepat dan tepat. PT. Fitindo Sehat Sempurna sebagai perusahaan yang bergerak di bidang jasa kebugaran ingin melakukan data mining untuk memprediksi kelancaran pembiayaan para anggotanya dan berupaya untuk meningkatkan omset penjualan yang berkelanjutan. Salah satu algoritma klasifikasi yang sering digunakan dan mendapat banyak perhatian dari para peneliti dalam memprediksi pembiayaan bermasalah adalah Naive Bayes, Decision Tree C4.5 dan kemudian mencoba membandingkannya dengan Fuzzy Decision Tree (ID3). Dari semua uji coba ketiga metode tersebut, didapatkan hasil terbaik yaitu Naive Bayes dengan hasil perhitungan akurasi tertinggi yaitu 85,00% dan AUC = 0,960 sebagai hasil terbaik. Pengujian ini menggunakan 80 data training dan 20 data testing.Kata kunci: Pembiayaan, Keanggotaan, ID3, Fuzzy, Decision Tree, C4.5, Naive Bayes
Co-Authors Agus Salim Ahmad Rifqi Ali Ahmad Arief Rama Syari Dwiza Riana Faishal Wafiq Zakiy Gata, Windu Idham Idham Mohamad Noor Muchamad Bachram Shidiq Muhammad Ghudafa Taufik Akbar Saputra, Dedi Dwi Saputro, Wahyu Joko Sigit Kurniawan Siska Rahmadan Siska Rahmadani Siti Nur Azizah, Euis Tetra Widianto Tri Agus Setiawan Tutik Lestari Wahyu Joko Saputro Wahyu Joko Saputro Windu Gata Windu Gata Zakiy, Faishal Wafiq