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All Journal Jurnal Ilmiah Teknologi dan Rekayasa PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Intelligent Decision Support System (IDSS) Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Teknologi Informatika dan Komputer Journal of Applied Data Sciences Jurnal Pengabdian Masyarakat Nasional
Aris Gunaryati, Aris
Jurusan Teknik Informatika, Fakultas Teknik Industri Universitas Gunadarma
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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E-Commerce Kedai HP Berbasis Model View Controller (MVC) dengan Metode Scrum Azharandi, Nadhif; Andryana, Septi; Gunaryati, Aris
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 6, No 1 (2022): January-March
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v6i1.379

Abstract

Kedai HP merupakan sebuah website E-Commerce distributor pribadi yang berfokus pada penjualan smartphone dengan merk dan harga yang beragam. Dengan adanya E-Commerce Kedai HP daya beli masyarakat semakin meningkat karena tidak datang perlu datang lansgsung ke toko untuk bertransaksi. Tujuan penelitian ini membuat website distributor online untuk memudahkan masyarakat dalam bertransaksi dan memberi kepraktisan dalam berbelanja. Penelitian ini menggunakan sistem berbasis Model View Controller (MVC) dengan  menggunakan metode Scrum yaitu sebuah metode yang cocok untuk di implementasikan pada pengembangan sistem karena bersifat fleksibel dibandingkan dengan metode waterfall yang bersifat statis. Model View Controller (MVC) salah satu design pattern yang saat ini banyak digunakan sebagian framework untuk melakukan pengembangan aplikasi sehingga E-Commerce Kedai HP dapat menjalankan sistem transaksi dan pelaporan secara otomatis. Pengujian dari penelitian ini menggunakan metode Blackbox Testing yang merupakan teknik pengujian software yang fokus pada spesifikasi fungsional suatu perangkat lunak. Dari hasil pengujiannya menunjukan bahwa fungsional sistem yang telah dikembangkan berfungsi sebagaimana mestinya.
Graph coloring Sistem Pendaftaran dan Proses Penjadwalan Data Instruktur Berbasis Web dengan Algoritma Welch-powell Sopiyan, Muhamad; Fauziah, Fauziah; Gunaryati, Aris; Fitri, Iskandar
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 6, No 1 (2022): January-March
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v6i1.359

Abstract

Many things in this world are implementations of graph coloring, because the models are very useful for broad applications, such as registration and scheduling of web-based instructor data. The purpose of this study is to support the virtual training process by generating training schedules automatically. of the week. There are types of training programs with a duration of 1 hour, 2 hours and 3 hours. Previously the instructor had to register in advance and determine how many hours of training sessions and the availability of an empty schedule. The application of graph coloring can help formulate instructor schedules so that they do not clash with other instructors' schedules. From the results of this study, each instructor who teaches in a week is selected by the system with the total number of time slots in a week is 8x6 = 48 hours. If the total teaching hours of applicants reach 60, 61 or 62 hours, the system will shut down automatically.
Perancangan Sistem Perpustakaan Berbasis Web Supriyadi, Alam; Andryana, Septi; Gunaryati, Aris
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 6, No 3 (2022): July-September
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v6i3.439

Abstract

The research objective is to build a web-based library application. The research method consists of data collection, while the application implementation uses string matching, exact matching, and string matching algorithms. Entity-relationship diagrams are also used in building relationships in the database. Use cases are used as a description of the scope of a system that is built. The conclusion of this study is that; 1) This information facility system is very effective in influencing library admins to look for borrowed books, 2) Providing integration that produces non-digital information in one application, and 3) Librarians can take advantage of web-based automation and manage the circulation of book loans and book returns.
Diagnosis Penyakit Pada Tanaman Sukulen Menggunakan Metode Forward Chaining Berbasis Mobile Android Widi, Dicky Prasetya; Gunaryati, Aris
Jurnal Informatika Vol 11, No 1 (2024): April 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v11i1.21208

Abstract

Pada saat ini perkembangan teknologi sudah sangat pesat, tidak hanya pada bidang informasi, pendidikan, industri tetapi juga pada bidang pertanian. Pesatnya perkembangan teknologi juga dirasakan bersama oleh para petani sukulen untuk mendapatkan informasi tentang tanaman sukulen mereka. Tanaman sukulen banyak dibudidayakan di wilayah perkotaan di Indonesia, namun petani sukulen tidak terlepas dari masalah yang muncul seperti penyakit dan hama yang tiba-tiba menyerang tanaman mereka. Oleh karena itu penulis melakukan pengembangan sistem pakar untuk mendiagnosis penyakit dan hama pada tanaman sukulen menggunakan metode forward chaining untuk menentukan penyakit atau hama pada tanaman sukulen. Penelitian ini dilakukan dengan cara wawancara kepada pakar tanaman sukulen dan studi literatur mengenai gejala-gejala penyakit dan hama pada tanaman sukulen. Data yang sudah dikumpulkan dan dianalisis untuk mengetahui kebutuhan sistem berdasarkan jenis penyakit & hama, jenis gejala, dan kaidah produksi. Untuk tahapan yang terakhir dilakukannya pengujian dengan metode black box dan user acceptance testing untuk memastikan sistem pakar dapat digunakan dengan baik oleh pengguna, dalam hal ini petani sukulen dan masyarakat. Hasil penelitian menunjukkan bahwa aplikasi ini efektif dalam membantu pengguna dan petani sukulen untuk mendiagnosis penyakit pada tanaman sukulen. Hasil pengujian aplikasi menunjukkan bahwa 85,5% responden memberikan penerimaan positif terhadap penerapan aplikasi. At present, technological advancements have progressed rapidly, not only in the fields of information, education, and industry but also in agriculture. The rapid development of technology is also felt collectively by succulent farmers to obtain information about their succulent plants. Succulent plants are widely cultivated in urban areas in Indonesia, but succulent farmers are not exempt from emerging problems such as sudden diseases and pests attacking their plants. Therefore, the author has developed an expert system to diagnose diseases and pests on succulent plants using the forward chaining method to determine diseases or pests on succulent plants. This research was conducted through interviews with succulent plant experts and a literature review on symptoms of diseases and pests in succulent plants. The collected data was analyzed to determine the system requirements based on the types of diseases and pests, symptoms, and production rules. In the final stage, testing was conducted using the black box method and user acceptance testing to ensure that the expert system can be effectively used by users, particularly succulent farmers and the community. The research results indicate that this application is effective in assisting users and succulent farmers in diagnosing diseases in succulent plants. Application testing results show that 85.5% of respondents expressed positive acceptance of the application.
Voice Command-Based IoT on Smart Home Using NodeMCU ESP8266 Microcontroller Shakaramiro, Muhammad Ariel; Gunaryati, Aris; Rahman, Ben
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 1 (2024): March 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i1.8287

Abstract

This research focuses on developing a Smart Home prototype that integrates the Internet of Things (IoT) and voice command using the NodeMCU ESP8266 microcontroller. This system allows users to control household devices such as lights, gates, and fans with voice commands through voice-enabled devices. The prototype utilizes NodeMCU ESP8266 to connect the devices to a WiFi network. The developed voice recognition system can accurately identify voice commands and send instructions to NodeMCU ESP8266 to control the corresponding devices. The test results demonstrate the prototype's efficiency in automating household devices through voice commands. Consequently, users can enhance comfort and energy efficiency within their homes. This research opens opportunities for the development of smarter and user-friendly Smart Home systems in the future. Response testing of the Blynk application showed a 100% success rate, with an average response time of less than ten seconds. WiFi network testing was carried out with the IP Address 192.168.101.137, resulting in good functional performance even in the presence of physical obstacles, and the device can operate well up to a distance of 22 meters.
Diagnosa Hepatitis A Menggunakan Metode Dempster - Shafer Pratiwi, Ridha; Andryana, Septi; Gunaryati, Aris
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 4 No. 1 (2020)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v4i1.156

Abstract

Hepatitis A merupakan penyakit peradangan yang terjadi pada hati, yang disebabkan karena adanya in-feksi oleh virus HAV, selain itu kurangnya perhatian masyarakat terhadap kebersihan lingkungan, makanan dan minuman yang tidak higenis, mahalnya biaya konsultasi, serta hubungan seks yang tidak sehat juga merupakan faktor utama dari berkembangnya penyakit tersebut. Untuk mengatasi permasalahan tersebut, dibuatlah suatu sistem yang dapat membantu masyarakat dalam mendeteksi dini, serta memberikan informasi terkait penyakit hepatitis A yaitu, dengan memanfaatkan sebuah sistem pakar yang menggunakan metode Dempster – Shafer, yang merupakan sebuah metode yang digunakan untuk mencari nilai kepastian dari gejala yang telah diinputkan sebelumnya, dan menghasilkan output berupa hasil diagnosis, penanganan, solusi, dan gejala yang telah dipilih. Penelitian ini dilaksanakan dengan mensimulasikan sistem dari gejala yang dipilih secara acak, sebanyak 100 data uji, dengan didampingi oleh pakar terkait. Sehingga diperoleh hasil akurasi sebesar 92% data yang sesuai dengan pakar dan 8% data tidak sesuai dengan pakar. Dari hasil pengujian tersebut menunjukan bahwa sistem pakar ini telah mampu untuk melakukan diagnosa dini terkait penyakit hepatitis A dengan metode Dempster – Shafer.
Enhancing Sharia Stock Price Forecasting using a Hybrid ARIMA-LSTM with Locally Weighted Scatterplot Smoothing Regression Approach Gunaryati, Aris; Mutiara, Achmad Benny; Puspitodjati, Sulistyo
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.514

Abstract

Predicting Sharia stock prices is complex because it has high volatility and non-linear data patterns. To improve the accuracy of the forecast, the right technique is needed according to the existing data pattern. One of the techniques currently developing is integrating (hybrid) two forecasting models. This study proposes a hybrid autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) model with the locally weighted scatterplot smoothing (lowess) linear regression technique. This model is designed by creating a linear regression between the actual value and the predicted results of the ARIMA and LSTM models using the Lowess technique. The dataset used here is the closing stock prices of four Indonesian Islamic banking companies. The hybrid ARIMA-LSTM model with lowess linear regression significantly outperforms the individual ARIMA and LSTM models because it produces better performance metrics, namely mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), for training and testing datasets. The proposed hybrid model effectively reduces noise, and the model can capture complex patterns in the Sharia stock price dataset, and the prediction results are more accurate. The accuracy values for training data and data testing datasets were respectively 97.6% and 98.3% (BANK. JK), 98.3% and 98.2% (BRIS. JK), 99.4% and 99.5% (BTPN. JK), and 97.7% and 99.3% (PNBS. JK).
KLASIFIKASI SENTIMEN PUBLIK TERHADAP KEBIJAKAN KENDARAAN LISTRIK MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN SUPPORT VECTOR MACHINE Nouval Daffa Ramadhan, Muhammad; Gunaryati, Aris
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13561

Abstract

Perubahan iklim menjadi isu global yang mendesak, dengan emisi gas rumah kaca dan polusi udara berdampak buruk pada kesehatan dan lingkungan. Kendaraan listrik (EV) muncul sebagai solusi efektif untuk mengurangi emisi dan polusi, karena tidak menghasilkan emisi langsung. Penelitian ini bertujuan untuk mengklasifikasikan sentimen publik terhadap kebijakan kendaraan listrik dengan menggunakan algoritma Naïve Bayes dan Support Vector Machine. Data yang digunakan diperoleh melalui proses crawling dari media sosial Twitter, yang kemudian melalui tahapan preprocessing, labeling menggunakan TextBlob, dan weighting menggunakan TF-IDF, model diklasifikasikan ke dalam tiga kategori sentimen positif, negatif, dan netral. Model klasifikasi diuji berdasarkan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa algoritma Support Vector Machine memiliki akurasi yang lebih tinggi dibandingkan Naïve Bayes, dengan nilai masing-masing sebesar 81% dan 76%. Temuan ini mengindikasikan bahwa Support Vector Machine lebih efektif dalam mengklasifikasikan sentimen publik terhadap kebijakan kendaraan listrik. Dengan demikian, penelitian ini diharapkan dapat memberikan wawasan yang lebih mendalam serta meningkatkan pemahaman masyarakat mengenai sentimen publik terhadap kebijakan pemerintah terkait kendaraan listrik
Improving MCDM University Rankings through Statistical Validation Using Spearman’s Correlation and THE Benchmark Andryana, Septi; Mantoro, Teddy; Gunaryati, Aris; Raffliansyah, Alfarizky Esah
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.796

Abstract

The evaluation of higher education institutions is a critical field for informing data-driven policy and institutional benchmarking. A key problem in this area is the lack of transparency and consistency in university rankings, particularly when using Multi-Criteria Decision-Making (MCDM) methods such as MABAC and MAIRCA, with limited research on how weighting techniques affect the reliability and alignment of these rankings with international standards like the Times Higher Education (THE) Rankings. This study proposes the use of MABAC and MAIRCA methods combined with two weighting techniques—Rank Order Centroid (ROC) and Rank Sum (RS)—to assess 20 top Indonesian universities based on five performance indicators: research quality, research environment, teaching, industry, and international outlook. Spearman’s rank correlation is used to compare the MCDM-generated rankings with THE Rankings 2025. The study contributes empirical evidence on the impact of weighting schemes on the consistency and reliability of university rankings and demonstrates that the MAIRCA-ROC method achieves the highest agreement with THE Rankings, with a correlation coefficient of 0.8135 and a p-value of 0.00001. These results validate the use of MCDM methods in higher education evaluation and emphasize the importance of selecting appropriate weighting techniques to develop transparent and robust ranking frameworks that support evidence-based policy decisions.
Analisis Perbandingan Algoritma Pencarian Jenis Tanaman Hias dengan Menggunakan Penerapan Metode Perbandingan Eksponensial Fauziah, F; Gunaryati, Aris; Nurhayati, N; Farahdinna, Frenda; Kaeren, K
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 2 (2023): Edisi Juni
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i2.195

Abstract

The process of searching data manually certainly takes a long time, therefore a system is needed that can speed up the data search process, especially ornamental plant data. In this study, two algorithms were used to compare the optimal data search process according to the type of data being collected. The data used are ornamental plant data. The two algorithms used are Knuth Morris Pratt and Boyer Moore. The process is carried out by comparing text and existing patterns based on the type of character that is carried out in this test and utilizing the exponential comparison method with a value comparison of 109.13 using the Boyer Moore algorithm and 139.19 with the Knuth Morris Pratt algorithm so that the type of Boyer Moore algorithm can be known faster than Knuth Morris Pratt for text searches related to the types of ornamental plants in the trial in this study.
Co-Authors Achmad Benny Mutiara Adang Suhendra Azharandi, Nadhif Caniago, Diana Dewantoro, Danang Efendi, Riyo Farahdinna, Frenda Fauziah Fauziah Fauziah, F Iskandar Fitri, Iskandar Kaeren, K Khansa, Amalia N Nurhayati Nouval Daffa Ramadhan, Muhammad Pratiwi, Ridha Raffliansyah, Alfarizky Esah Rahman, Ben Sari, Putriana Mayang Septi Andryana Setiawan, Muhammad Afif Shakaramiro, Muhammad Ariel Sopiyan, Muhamad Sulistyo Puspitodjati Supriyadi, Alam Supriyadi, Mohamad Didit Susilo, Mohammad Syahputra, Adryan Teddy Mantoro Widi, Dicky Prasetya