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All Journal Pixel : Jurnal Ilmiah Komputer Grafis Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Santika : Jurnal Ilmiah Sains dan Teknologi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Idealis : Indonesia Journal Information System Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Dedication : Jurnal Pengabdian Masyarakat
Winda Apriandari
Universitas Muhammadiyah Sukabumi
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Materials Science & Nanotechnology Other

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Implementasi Azure Cognitive Services dalam Pengembangan Chatbot Layanan Informasi Skripsi Nur Asiah Ramdani; Asriyanik Asriyanik; Winda Apriandari
Pixel :Jurnal Ilmiah Komputer Grafis Vol 15 No 1 (2022): Vol 15 No 1 (2022): Jurnal Ilmiah Komputer Grafis
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v15i1.751

Abstract

The Thesis is a compulsory subject that must be followed by undergraduate students to complete their study period. The Thesis is different from other courses related to the procedures in it. In the Informatics Engineering study program at Muhammadiyah University of Sukabumi, the dissemination of thesis information was spread through 5 different media, but this was not effective because it took a lot of time and made the work repeated. Therefore, to facilitate the dissemination of information, the researchers created a chatbot application that can answer questions about thesis information automatically without human supervision. To produce a smart chatbot, Microsoft Azure Cognitive Services QnA Maker service is used in its manufacture. The chatbots were tested using alpha and beta testing and concluded that making chatbot applications with Azure Cognitive Services QnA Maker made finding thesis information more accurate, effective, and efficient.
An Extreme Programming Approach for Instructor Performance Evaluation System Development Agung Pambudi; Winda Apriandari
Journal of INISTA Vol 5 No 2 (2023): May 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v5i2.1050

Abstract

The aim of this research was to develop an instructor performance evaluation system for Information Technology Training Center (ITTC) of Islamic State University (UIN) Sunan Kalijaga Yogyakarta using Extreme Programming (XP) methodology. The system was designed to evaluate the performance of instructors in the ICT (Information and Communication Technology) Training process based on certain criteria. The XP method was an agile software development approach that emphasizes iterative development, continuous testing, and customer involvement. The proposed system was developed through several iterations that involve continuous feedback from the ITTC management. The development of the system followed the XP process, which was included planning, designing, coding, testing, refactoring, and integrating. Trainees can access the system to evaluate instructors, and the system helped the ICT training management to determine the instructor's performance for future employment contracts. The system has undergone functionality testing, which resulted in a 100% functionality test and 95,5% of usability test. This system was an effective tool for evaluating the performance of ICT training instructors and can be used to determine the effectiveness of training programs. The system's usability and functionality had been tested and proven to be highly effective, making it a valuable resource for ICT training management.
Pengembangan Usaha Mandiri Masyarakat Desa Melalui Badan Usaha Milik Desa Asep Budiman Kusdinar; Winda Apriandari
Dedication : Jurnal Pengabdian Masyarakat Vol 7 No 1 (2023)
Publisher : LPPM Universitas PGRI Argopuro Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31537/dedication.v7i1.1033

Abstract

Usaha mandiri masyarakat Desa merupakan kegiatan usaha yang dilakukan oleh perseorangan ataupun kelompok dan berkesinambungan. Usaha ini meningkatkan potensi dan produktifitas pelaku usaha terhadap popularitas Desa di Lingkungannya. Tujuannya untuk meningkatkan produk usaha yang berkualitas agar daya beli masyarakatnya meningkat. Usaha mandiri tersebut sebelumnya sudah dilakukan berupa produk industri rumahan, paket gula merah, pengadaan pupuk buatan masyarakat Desa, dan jasa pengiriman bahan baku keripik singkong. Cara yang dilakukan untuk mengolah produk tersebut berupa integrasi bahan-bahan olahan menjadi produk jadi yang hasilnya siap untuk dipasarkan. Keberhasilan usaha mandiri tersebut telah tercapai sebesar 85% sedangkan sisanya sebesar 15% melalui pengembangan usaha melalui dukungan pemerintah Desa dalam bentuk Badan Usaha Milik Desa (BUMDes). Dengan demikian, produk usaha mandiri ini berhasil apabila masyarakatnya mau menjual secara luas lewat pedagang eceran maupun lewat media elektronik, media sosial, dan internet.
Prediksi Hasil Pertandingan Liga Serie A Menggunakan Metode Naïve Bayes Ridwan Adi Pratama; winda apriandari; didik indrayana
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 22, No 2 (2023): Agustus 2023
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v22i2.8448

Abstract

Sepak bola adalah olahraga yang sangat populer di seluruh dunia, dengan banyak penggemar yang melakukan prediksi hasil pertandingan. Metode yang digunakan untuk memprediksi hasil pertandingan dapat mempengaruhi akurasi prediksi tersebut. Dalam penelitian ini, dilakukan prediksi hasil pertandingan Liga Serie A menggunakan metode algoritma Naïve Bayes.Penelitian ini terdiri dari beberapa tahap, di antaranya adalah Data Selection, Preprocessing Dataset, Transformation Dataset, Klasifikasi Naïve Bayes, Pengujian dan Evaluasi Model. Data yang digunakan dalam penelitian ini diperoleh melalui web scraping dari situs www.football-data.uk, dan terdiri dari data Liga Serie A dari tahun 2017 hingga 2022. Setelah melalui tahap preprocessing, dataset diubah menjadi bentuk angka menggunakan metode transformation dataset agar dapat digunakan dalam algoritma Naïve Bayes. Kemudian dilakukan klasifikasi menggunakan metode Naïve Bayes untuk memprediksi hasil pertandingan. Hasil pengujian menunjukkan bahwa metode Naïve Bayes berhasil mencapai tingkat akurasi sebesar 75,79% dengan menggunakan data 1900 pertandingan. Empat teratas yaitu Juventus, Inter, Milan dan Napoli diprediksi akan lolos ke Liga Champions. Selanjutnya, model prediksi yang telah dibuat diimplementasikan dalam bentuk aplikasi. Aplikasi ini memungkinkan pengguna untuk melihat prediksi hasil pertandingan Liga Serie A dan menampilkan tampilan visual yang informatif. Dalam kesimpulan, penelitian ini berhasil melakukan prediksi hasil pertandingan Liga Serie A dengan menggunakan metode Naïve Bayes. Hasil pengujian menunjukkan tingkat akurasi yang baik. Penelitian ini memberikan kontribusi dalam pengembangan metode prediksi hasil pertandingan sepak bola dengan menggunakan algoritma Naïve Bayes. Kata Kunci : Prediksi, Serie A, Naïve Bayes, Akurasi, Web scrapping
Expert System for Diagnosing Pests and Diseases of Crystal Guava Plants Using the Certainty Factor Method Deri Kurniawan; Winda Apriandari; Agung Pambudi
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 20, No 2 (2023): SEPTEMBER 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v20i2.2462

Abstract

A guava variety called Jambu Kristal (Crystal Guava) that shows potential to be developed in Indonesia because it is suitable for soil, climate, and weather conditions in Indonesia, as well as increasing market demand. Nevertheless, crystal guava plants remain vulnerable to pests and diseases that can hinder growth and cause losses to farmers. If pest and disease attacks on crystal guava plants are not diagnosed and treated immediately, the consequences can include plant death, damage to the fruit, as well as a significant decrease in production. This research develops an expert system application that aims to assist farmers in diagnosing pests and diseases in Crystal Guava plants. In this research, the Certainty Factor Method is used as a reasoning tool to estimate the level of confidence in diagnosing pests and diseases that attack crystal guava plants. The Certainty Factor algorithm processes the uncertainty value input from the user using a single premise and conclusion to produce a diagnosis value in the form of a percentage. The expert system is supported by 8 knowledge bases that contain information related to pests and diseases in Crystal Guava plants. The built expert system shows that the system is able to diagnose Root Rot Disease with a confidence value of 97.60%.
Classification Of the Effectiveness of Sukabumi Relocation Food Center Policy Using the Naïve Bayes Classifier Algorithm M. Elki Ismuhamdan; Prajoko Prajoko; Winda Apriandari
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 20, No 2 (2023): SEPTEMBER 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v20i2.2459

Abstract

The program that is being discussed in Sukabumi City is the construction and arrangement of Jalan Ir. H. Juanda or “Dago” as a hawker center for the City of Sukabumi accompanied by a policy of relocating street vendors to Jalan Dewi Sartika. The effectiveness of this policy is still questionable because it has an unfavorable impact and creates polemics for various parties and there is no research that measures the efficiency and effectiveness of implementing the street vendor relocation policy. This research was conducted to classify and measure the effectiveness of the relocation policy for hawker centers in Sukabumi City based on the classification of the opinions of the people of Sukabumi City and traders in the relocation area by creating a system that can measure the effectiveness of the policy using the Naïve Bayes Classifier algorithm with the Knowledge Discovery in Database research method. The Naïve Bayes Classifier algorithm is a data mining algorithm that applies Bayes's Theorem [1]. The final result of this research is that from 368 opinion data, 52.45% or 193 opinions are classified as "Effective" and 47.55% or 175 opinions are classified as "Ineffective" with an accuracy value of 97.02%. The policy of relocating hawker centers in Sukabumi City can be concluded as Effective, because the Effective value is greater than the Ineffective value even though it has a very thin difference in value with a very high accuracy value
Implementation Of the Naive Bayes Algorithm for Analysis Sentiment of Alun-Alun as A Public Open Space in Sukabumi Regency Farikh Fadhil; Asriyanik Asriyanik; Winda Apriandari
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 20, No 2 (2023): SEPTEMBER 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v20i2.2434

Abstract

Sukabumi Regency is one of the regencies in West Java that has various facilities and infrastructure, including public open spaces, which serve as beneficial places for the daily activities and needs of the general public. One of these spaces is the town squares, namely Alun-Alun Cisaat, Alun-Alun Palabuhanratu, Alun-Alun Jampang Kulon, Alun-Alun Purabaya, and Alun-Alun Cicurug. However, there are still town squares in Sukabumi Regency that are poorly maintained, resulting in negative articles or opinions from visitors regarding these town squares. Therefore, it is necessary for the local government to undertake development or evaluation to further improve the public open spaces in Sukabumi Regency. Before carrying out the development and evaluation, it is essential to gather information, data, or conduct analysis related to public opinions on these public open spaces. One method is by performing sentiment analysis. This research conducts a public sentiment analysis on the town squares as public open spaces in Sukabumi Regency, utilizing the Naïve Bayes algorithm for sentiment analysis. The data used for analysis were obtained from visitor reviews of these places from the period of 2019 to 2023 on the Google Maps website. A total of 2698 sentiment data points were collected, consisting of 2254 positive sentiment data and 444 negative sentiment data. The algorithm used in the created model achieved an accuracy rate of 92%, precision value of 90%, recall value of 53%, and an F1-score of 67%. The frequency of words obtained from the sentiment analysis revealed the top 5 most frequently mentioned words based on their sentiment class. The top 5 positive sentiment words are excellent, good, clean, hang out, and pleasant. On the other hand, the top 5 negative sentiment words are garbage, dirty, slum, traffic jam, and disorganized. The results of this research, specifically related to sentiment analysis, are expected to assist the local government, especially Regional Office of Land and Spatial Planning in Sukabumi Regency, by providing valuable information as a reference or recommendation for the future development and evaluation of public open spaces in Sukabumi Regency.
ANALISIS SENTIMEN BERBASIS ASPEK TERHADAP ULASAN APLIKASI MYPERTAMINA MENGGUNAKAN SUPPORT VECTOR MACHINE Ikram Maulana; Winda Apriandari; Agung Pambudi
IDEALIS : InDonEsiA journaL Information System Vol 6 No 2 (2023): Jurnal IDEALIS Juli 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v6i2.3022

Abstract

PT. Pertamina (Persero), sebagai BUMN terbesar di bidang minyak dan gas bumi di Indonesia, memiliki tanggung jawab untuk menyalurkan BBM bersubsidi secara tepat sasaran dan sesuai kuota yang ditetapkan oleh pemerintah. Sejak 1 Juli 2022, aplikasi MyPertamina menjadi syarat untuk pembelian BBM Pertalite dan Biosolar. Dengan lebih dari 10 juta unduhan dan peringkat 2,5 di Google Play Store berdasarkan data pada Oktober 2022, penelitian ini bertujuan untuk mengevaluasi aplikasi MyPertamina dengan mengelompokkan ulasan ke dalam dua kelas sentimen dan tiga kelas aspek. Metode yang digunakan dalam penelitian ini adalah Knowledge Discovery in Database (KDD) dengan menerapkan algoritma Support Vector Machine (SVM). Hasil penelitian menunjukkan bahwa MyPertamina dinilai membantu pengguna dalam pembelian BBM, meskipun terdapat kendala yang dirasakan pengguna. Kendala tersebut meliputi kesulitan dalam mendaftar akun dan sering mengalami kegagalan login pada aspek Bug, kerumitan dalam penggunaan pada aspek kegunaan, serta kadang-kadang tidak muncul barcode pada aspek pembayaran. Evaluasi model klasifikasi sentimen dan aspek menghasilkan tingkat akurasi rata-rata sebesar 92% dan 96% secara berturut-turut. Dengan demikian, dapat disimpulkan bahwa model yang telah dikembangkan cukup andal dalam melakukan klasifikasi pada data ulasan aplikasi MyPertamina.
Algoritma Naïve Bayes untuk Rekomendasi Seleksi Peserta Paskibraka Berbasis Website Mohamad Nurizki; Winda Apriandari; Asriyanik Asriyanik
Journal of Information System Research (JOSH) Vol 4 No 4 (2023): Juli 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i4.3574

Abstract

In the series of intensive Paskibraka activies, each individual strives to build strong character. Paskibraka serves as a means to cultivate a sense of love for the homeland. Every year, on the commemoration of the raising ceremony is conducted on August 17th. One important part of the ceremony is the hosting of the red and white flag by Paskibraka member. PASKIBRAKA (Flag Raising Troop) represent the selected new generation of Indonesia through a selection process participated by student from various high school. The PASKIBRAKA selection involves several stages, and to facilitate the selection process, a guideline for activities has been formulated in the Minister of Youth and Sports Regulation (Permenpora) No. 0065 of 2015. The classification appiled utilizes the Naïve Bayes algorithm with the Knowladge Discovery in Databases (KDD) method. The naïve bayes algorithm is a data mining and statistical classification algorithm that applies Bayes’theorem under the assumption of independence between variables. The advantages of the naïve bayes algorithm lie in its scability in handing the number of predictors and data points, its ability to make probability prediction, and its capability to handle both continuous and discrate data. The result of this research have achieved the from of automated classification of the eligibility of Paskibraka participant selection, data mining whether the are aligible or not to become members of Paskibraka in Sukabumi Regency.
Co-Authors Agung Pambudi Agung Pambudi Argia Pranselga Asep Budiman Kusdinar Ashwin Sasongko Asriyanik Asriyanik Asriyanik Asriyanik Deri Kurniawan Didik Indrayana Dinda Joana Laksana Fajar Hikmal Gunawan Farikh Fadhil Gusti Aldy Reynaldy Hary Purnomo Ikram Maulana Iwan Rizal Setiawan M. Elki Ismuhamdan Mohamad Nurizki Nur Asiah Ramdani Prajoko Prajoko Prajoko Ridwan Adi Pratama Santi Saksenai Shilva Imanibillah Syafira Zahara Zakia Nurul Aini