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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Riau Journal of Computer Science Produktif : Jurnal Ilmiah Pendidikan Teknologi Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Jurnal Teknologi dan Informasi Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal JATI (Jurnal Mahasiswa Teknik Informatika) Aksara: Jurnal Ilmu Pendidikan Nonformal Jurnal Teknologi Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) J-Intech (Journal of Information and Technology) Jurnal Teknologi Sistem Informasi Teknologika Jurnal Informatika Teknologi dan Sains (Jinteks) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer RISTEC : Research in Information Systems and Technology
Ismi Kaniawulan, Ismi
Program Studi Informatika STT Wastukancana Jalan Raya Cikopak No. 53 Sadang Purwakarta Jawa Barat
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences Other

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ANALISIS KESUKSESAN APLIKASI E-COMMERCE TOKOPEDIA MENGGUNAKAN MODEL DELONE AND MCLEAN Ayu Yunia; Ismi Kaniawulan; H. Dayan Singasatia
Jurnal Informatika Teknologi dan Sains Vol 4 No 3 (2022): EDISI 13
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (428.242 KB) | DOI: 10.51401/jinteks.v4i3.1947

Abstract

Abstrak: Tokopedia merupakan salah satu perusahaan E-Commerce atau aplikasi berbelanja online yang menawarkan beragam jenis produk. Permasalahan dalam penggunaan aplikasi Tokopedia sekalipun memberikan kemudahan dalam berbelaja online, tetapi masih mengalami kendala yang yaitu semakin beratnya aplikasi selalu meminta update ulang, sering dibatalkan secara tiba-tiba oleh penjual, pengambilan dana saat transaksi batal sangat lama, selalu loading, ekspedisi yang lama. Tujuan dari penelitian ini adalah untuk mengetahui faktor apa saja yang mempengaruhi kesuksesan aplikasi Tokopedia. Model yang digunakan penulis untuk menganalisis kesuksean aplikasi Tokopedia yaitu menggunakan Delone And Mclean dan menggunakan 5 variabel atau konstruk, Metode yang digunakan yaitu metode kuantitatif, objek penelitian yaitu pengguna aplikasi Tokopedia di purwakarta. Hasil pengolahan data menggunakan SPSS, Structural Equation Modeling (SEM) dengan mengunakan tools AMOS 24.0. Hasil dari penelitian ini yaitu kualitas sistem (System Quality) berpengaruh signifikan terhadap kepuasan pengguna (User Satisfaction) dan kepuasan pengguna (User Satisfaction) berpengaruh signifikan terhadap manfaat-manfaat bersih (net benefit).  
ANALISIS KESUKSESAN APLIKASI BRIMO DENGAN PENDEKATAN MODEL DELONE AND MCLEAN Lusiana Marselina; Ismi Kaniawulan; H. Dayan Singasatia
Jurnal Informatika Teknologi dan Sains Vol 4 No 3 (2022): EDISI 13
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (308.72 KB) | DOI: 10.51401/jinteks.v4i3.1951

Abstract

Bank Rakyat Indonesia (BRI) is one of the largest state-owned banks in Indonesia. Bank BRI provides a Mobile Banking facility called "BRImo". Problems in the BRImo Application even though it provides convenience in online transactions, there are still some users who experience problems using the BRImo application. Such as difficulties in using the BRImo Application, difficulties in registering for BRImo, unable to login, and sometimes users are often blocked. The complaint is an inconvenience in using the BRImo Application so that it can reduce the level of user trust. The purpose of this study is to determine the level of success of the BRImo application and which variables affect user satisfaction. The research methodology uses quantitative methods and this study uses 5 variables from the DeLone and McLean method, namely: System Quality, Information Quality, Service Quality, User Satisfaction, and Net Benefits. The results of this study are System Quality, Information Quality has a significant effect on user satisfaction and user satisfaction has a significant effect on net benefits.
SENTIMENT ANALYSIS OF INTERNET SERVICE PROVIDERS USING NAÏVE BAYES BASED ON PARTICLE SWARM OPTIMIZATION Anugrah Anugrah; Teguh Iman Hermanto; Ismi Kaniawulan
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (976.823 KB) | DOI: 10.34288/jri.v4i4.408

Abstract

Twitter is a social media application that is widely used. Where as many as 18.45 million users in Indonesia, Twitter users can send and read messages with a maximum of 280 characters displayed. Many opinions and reviews uploaded by users via tweets on social media are experienced in everyday life. Lately, comments about internet service providers in the covid-19 pandemic have been widely reviewed by Twitter users. Problems about internet providers through words often uploaded include internet provider complaints related to network quality, package prices, user satisfaction, and others. This study aims to classify Twitter users' tweets against internet service providers in Indonesia by analyzing the sentiments of 3 internet service providers, namely with the keywords Biznet, first media, and Indihome, using the Naïve Bayes algorithm and optimization with Particle Swarm Optimization. This research is also helpful in helping to become a measure where prospective new users will see the quality of an internet service provider in Indonesia through tweets and then divide the opinion into positive and negative. The results of Biznet's research using Naïve Bayes produce an accuracy of 77.94%, and after optimization, it becomes 81.62%. First media using Naïve Bayes produces 91.39% accuracy, and after optimization, it becomes 92.88%. Indihome using Naïve Bayes produces an accuracy of 85.78%, and after optimization, it becomes 87.48%. It can be concluded that the Naïve Bayes algorithm is a good algorithm for classification, and optimization using Particle Swarm Optimization has an effect on increasing accuracy results
Analisis Prediksi Mood Genre Musik Pop Menggunakan Algoritma K-Means dan C4.5 Lia Nurhalimah; Teguh Iman Hermanto; Ismi Kaniawulan
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4597

Abstract

Spotify is a music streaming platform that has a variety of diverse features and is always updated in terms of the latest music. The features in spotify have an interesting thing for users to enjoy music more optimally both in listening to songs based on songs, most popular artists and genres. Research on classifying songs based on mood by using energy and valence in a song is often done, especially in western pop songs. In every thought music has emotional energy that radiates and is strongly related to human psychology. The problem with spotify is that there is no feature to listen to songs based on mood. If pop songs are categorized by mood, it will be easier for people to listen to pop songs and choose the appropriate one based on mood. In this study, pop music data will be grouped based on 4 categories of Thayer's mood models using the k-means and c4.5 algorithms. The purpose of this study is to analyze the mood prediction of the pop music genre using the k-means and c4.5 algorithms. The research methodology used is SEMMA, the stages in Semma are sample, explore, modify, model and assess. The attributes used are danceability, energy, tempo and valence. From these attributes, data clustering is made using the k-means algorithm using RapidMiner. Then visualized using Power BI. The results of the research from cluster data are grouped into moods consisting of angry, sad, cheerful and happy. The most abundant mood is in the cheerful mood. Then evaluate the assess using the calculation of the confusion matrix which produces an accuracy rate of 91.9%..
PENGARUH KUALITAS SISTEM KUALITAS INFORMASI KUALITAS LAYANAN TERHADAP KEPUASAN PENGGUNA SERTA MINAT NENGGUNAKNA BJB DIGI Dina Nurlina; Ismi Kaniawulan; Dayan Singasatia
Jurnal Informatika Teknologi dan Sains Vol 4 No 3 (2022): EDISI 13
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (279.223 KB) | DOI: 10.51401/jinteks.v4i3.1950

Abstract

PT Bank Pembangunan Daerah Jawa Barat dan Banten, Tbk merilis layanan digital atau mobile banking. Adanya bjb digi diharapkan dapat mpermudah aktifitas nasabah dari manual ke digital. Beberapa permasalahan yang dirasakan oleh pengguna bjb digi dilingkungan Dinas Pendidikan Provinsi Jawa Barat seperti aplikasi sering error dan selalu meminta ganti pin. Penelitian ini bertujuan untuk mengetahui faktor-faktor apasaja yang mempengaruhi kesuksesan aplikasi bjb digi di Dinas Pendidikan Provinsi Jawa Barat menggunakan model Delone and McLean  dan dijadikan bahan evaluasi untuk meningkatkan performance aplikasi. Jenis penelitian menggunakan deskriptif kuantitatif. Metode sampling menggunakan Probability Sampling dengan Purposive Sampling. Hasil penelitian terdapat hubungan positif dan signifikan antara kualitas sistem (SQ) kualitas layanan (SQL) terhadap kepuasan pengguna (US) tidak terdapat hubungan positif dan signifikan antara Kualitas Layanan (SQL) terhadap Kepuasan Pengguna (US) dan minat pengguna (ITU).
DESIGN OF CONTROL AND MONITORING SYSTEMS ELECTRONIC EQUIPMENT ENERGY IN CLASSROOMS WEB-BASED Rizky Kurnia Putra; Minarto - -; Ismi Kaniawulan
RISTEC : Research in Information Systems and Technology Vol 3, No 2 (2022): Research in Information Systems and Technology
Publisher : Institut Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (401.339 KB) | DOI: 10.31980/ristec.v3i2.2773

Abstract

Classroom is a place that use by student to learn. Each classroom equipped by electrical equipment and tool including 4 lamps and 2 fans. When learning activities is over in some classroom, lamps and fans still on. The cause of this condition is due to manual control, the result is electricity to be wasteful. As a result, electricity supply is run out before one month use and it can obstruct the learning activities if the power goes out. The aim of the research is to build a system that able to controls electricity equipment in the classroom and make a monitoring power consume remotely so can be effective and efficient. The system design is use prototype method that is a design software technic, while in designing web, with Data Flow Diagram (DFD) and Entity Relationship Diagram (ERD). Control design and monitoring use Raspberry Pi 3 B+ as microcontroller and web as interface user media. Relay connected with raspberry pi through General Purpose Input Output (GPIO) as automatic switch. USB Converter serial as interface for communicating raspberry pi with PZEM-004T module as current, voltage and power reader. The result of the study Can control and monitor the use of power consume in electrical equipment remotely web based. The system is completed by daily report of power consume and warning notification on the web when kWh almost running out. This research is useful in preventing wasting electricity and running out of electricity while learning is in progress
Design Of Sunlight, Humidity, And Temperature Measurement Systems With Data Acquisition For Iot-Based Solar Panel Placement Satrio Widianto Utomo; Minarto Minarto; Ismi Kaniawulan
RISTEC : Research in Information Systems and Technology Vol 4, No 1 (2023): Riset Sistem dan Teknologi Informasi
Publisher : Institut Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/ristec.v4i1.3227

Abstract

The Internet of Things (IoT) is a concept aimed at expanding the benefits of continuous internet connectivity. IoT can be utilized for monitoring the intensity of light, temperature, and air humidity in the surroundings to determine suitable locations for the placement of solar panels. Solar panels are made of semiconductor materials capable of converting solar energy into electricity. The primary issue with using solar panels is that the power output they produce depends on the intensity of light captured by the solar panel. Additionally, the temperature and air humidity around the solar panel also influence its performance. The objective of this research is to create a system for measuring the intensity of sunlight, humidity, and temperature for the placement of IoT-based solar panels using LDR and DHT 11 sensors. The development of this system involves the use of the Prototyping Method. The device's design incorporates the NodeMCU ESP32 microcontroller, and monitoring is conducted through a smartphone using the Blynk application. The LDR and DHT 11 sensors are connected to the NodeMCU ESP32's GPIO as data receivers. A WiFi network is used to transmit intensity of light, temperature, and humidity data from the NodeMCU ESP32 to the smartphone, where it is displayed through the Blynk application. This research is beneficial for identifying the most suitable locations for solar panel placement. Keywords : IOT, Solar panel, Monitoring, NodeMCU ESP32, Blynk
ANALISIS SENTIMEN PENGGUNA APLIKASI JAMSOSTEK MOBILE (JMO) PADA APPSTORE MENGGUNAKAN METODE NAIVE BAYES Karin Kusuma Dewi; Ismi Kaniawulan; Candra Dewi Lestari
Simtek : jurnal sistem informasi dan teknik komputer Vol. 8 No. 2 (2023): Oktober 2023
Publisher : STMIK Catur Sakti Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51876/simtek.v8i2.286

Abstract

The use of Jamsostek Mobile has problems that often occur, namely failure to update data on the JMO application, digital cards that do not appear on the JMO application, data update failures and access failures. To overcome this, BPJS participants are faced with BPJS branches or companies. This is an obstacle that should be overcome through optimizing regulations from the BPJS so that there are no complaints from the public regarding this matter. Jamsostek Mobile is an application implemented by BPJS Ketenagakerjaan to make it easier for users to carry out JHT simulations, check JHT balances, check details for JHT contributions and pension benefits, and make JHT claims. This application can be accessed on the App Store and Playstore. The implementation of the application turned out to generate several comments or reviews from users both in the App Store and Play Store. This study aims to analyze sentiment from user reviews on the App Store with the stages of Scraping, Labeling, Cleaning, Preprocessing Text, Class Naive Bayes, TF-IDF, Evaluation, Visualization using Google Collaboratory tools From the results of research on the sentiment analysis of users of the Jamsostek Mobile application on the AppStore platform, which totaled 2001 data and had passed the preprocessing text stage consisting of filtering, tokenization, transformation and classification using the Naïve Bayes algorithm and evaluation of data with a confusion matrix using Google Collaboratory, it can be interpreted that the results from reviews of the use of negative JMO applications with a proportion of 96% in accuracy (accuracy), 96% in value precision, and a success rate (recall) of 100%. This value indicates that the naïve Bayes classification algorithm is considered quite good in processing review data, because the proportion of accuracy is 96%. Based on this value, it proves that the sentiment or reviews of JMO application users on the App Store platform are negative. Keywords: Sentimen Analysis, Naive Bayes, App Store, Jamsostek Mobile, Google Collaboratory
SENTIMENT ANALYSIS OF INTERNET SERVICE PROVIDERS USING NAÏVE BAYES BASED ON PARTICLE SWARM OPTIMIZATION Anugrah Anugrah; Teguh Iman Hermanto; Ismi Kaniawulan
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i4.117

Abstract

Twitter is a social media application that is widely used. Where as many as 18.45 million users in Indonesia, Twitter users can send and read messages with a maximum of 280 characters displayed. Many opinions and reviews uploaded by users via tweets on social media are experienced in everyday life. Lately, comments about internet service providers in the covid-19 pandemic have been widely reviewed by Twitter users. Problems about internet providers through words often uploaded include internet provider complaints related to network quality, package prices, user satisfaction, and others. This study aims to classify Twitter users' tweets against internet service providers in Indonesia by analyzing the sentiments of 3 internet service providers, namely with the keywords Biznet, first media, and Indihome, using the Naïve Bayes algorithm and optimization with Particle Swarm Optimization. This research is also helpful in helping to become a measure where prospective new users will see the quality of an internet service provider in Indonesia through tweets and then divide the opinion into positive and negative. The results of Biznet's research using Naïve Bayes produce an accuracy of 77.94%, and after optimization, it becomes 81.62%. First media using Naïve Bayes produces 91.39% accuracy, and after optimization, it becomes 92.88%. Indihome using Naïve Bayes produces an accuracy of 85.78%, and after optimization, it becomes 87.48%. It can be concluded that the Naïve Bayes algorithm is a good algorithm for classification, and optimization using Particle Swarm Optimization has an effect on increasing accuracy results.
ANALISIS PENERIMAAN FITUR SHOPEE PAYLATER PADA APLIKASI SHOPEE MENGGUNAKAN TECHNOLOGY ACCEPTANCE MODEL (TAM) Fachry Nurfaidzi; Ismi Kaniawulan; Dayan Singasatia
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 5 No 4 (2023): EDISI 18
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v5i4.3262

Abstract

Commercial organizations or companies must use e-commerce to remain competitive on a worldwide scale. Shopee is the most popular e-commerce, the features provided are related to the payment system, is the SPaylater feature. The paylater that is widely used throughout 2021 is Shopee Paylater as much as 78.4%. Applying the Technology Acceptance Model (TAM) method with four constructs namely Perceived usefulness, Perceived ease of use, Attitude to use, Actual system use, and one external variable namely Trust, this study aims to find out what influences the acceptance of the Spaylater feature in the Shopee application. Utilizing the structural equation model (SEM) as a hypothesis test. The findings from this study found a significant positive effect between Trust on Perceived Ease of Use and Perceived Usefulness. Then found a significant positive effect between Perceived Ease of Use, Perceived Usefulness on Attitude Toward Using and Attiude Toward Using a significant positive effect on Actual System Use.
Co-Authors Andi Mahendra Anugrah Anugrah Arafat, Doni Arismawaty Putri, Rosma Atnadhiaz, Dival Alifial Ayu Yunia Ayunitasari, Fina Bagus Yuliandre, Muhammad Candra Dewi Lestari Dayan Singasatia Dede Irmayanti Defriani, Meriska Defryan Tri Gusman Dewi Lestari, Candra Dina Nurlina Egi Maulana Yusuf Fachry Nurfaidzi Guruh Sindu Praputra Haryani, Rani Hermanto, Teguh Iman Irsan Jaelani Jatira Julianti, Amelia Karin Kusuma Dewi Kurnia Putra, Rizky Kurnia Widi, Wanda Lia Nurhalimah Lusiana Marselina M Rafi Muttaqin Mawar Wiliyanti Minarto Minarto - - Minarto Minarto Mochammad Imam Sulistyo Sarjowo Muhammad Rafi Muttaqin Mutiara Andayani Komara Muttaqin, M Rafi Nugraha Fatoni, Irvan Nur Anggraeni, Cindy Nurhayati, Delisa Nurlatipah, Siti Nurul Hasanah Purnama, Erga Rangga Resmi, Mochzen Gito Resmi, Mohzen Gito Riani, Ayi Riswan Abdusalam Riswan Rizal Riva'i, Muhamad Rizky Kurnia Putra Rizqi, Putri Nuraeni Rizqullah, Naufal Salsabil, Salsabil Satrio Widianto Utomo Sri Andar Muni, Lise Supriadi Supriadi Suryana Suryana Syamsu Yusuf Teguh Iman Hermanto Teguh Iman Hermanto Teguh Iman Hermanto Tika Dewi Astuti Ulhaq, Dhiya Undamayanti, Erina Wahyudi, Dikdik Yulinawati, Yulinawati