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Kegiatan menonton film merupakan salah satu cara sederhana untuk menghibur diri dari rasa gundah gulana ataupun melepas rasa lelah setelah melakukan aktivitas sehari-hari. Akan tetapi, karena berbagai alasan terkadang seseorang tidak ada waktu untuk menonton film di bioskop. Dengan bantuan media internet, berbagai macam aplikasi nonton film android sangat mudah dicari. Hanya bermodalkan smartphone saja para penonton film dapat streaming berbagai macam jenis film di mana saja dan kapan saja mereka inginkan. Akan tetapi, karena banyaknya pilihan aplikasi nonton film android yang bisa digunakan, terkadang seseorang bingung memilihnya. Untuk itu, diperlukan suatu sistem pendukung keputusan yang dapat digunakan para pengguna sebagai alat bantu pengambilan keputusan untuk memilih dengan berbagai macam kriteria yang ada. Salah satu metode yang digunakan adalah metode Analytical Hierarchy Process (AHP). AHP melakukan perankingan dengan melalui penjumlahan antara vector bobot dengan matrik keputusan dengan tujuan agar hasil yang diberikan lebih baik dalam menentukan alternatif yang akan dipilih. Berdasarkan hasil penelitian yang dilakukan oleh 36 sampel responden didapatkan kriteria konten menjadi prioritas pertama pengguna untuk memilih aplikasi nonton film android dengan nilai bobot sebesar 0,224. Sedangkan Netflix menjadi alternatif dengan prioritas pertama keputusan pengguna dalam memilih aplikasi nonton film android dengan nilai bobot sebesar 0,352.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 394 Documents

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SENTIMENT ANALYSIS ON THE PERMENDIKBUD CONCERN PREVENTION AND TREATMENT OF SEXUAL VIOLENCE IN HIGHER EDUCATIONAL ENVIRONMENTS USING SUPPORT VECTOR MACHINE (SVM) Reinhard Alfaries Saemani; Nina Setiyawati
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 8 No 1 (2022): JITK Issue August 2022
Publisher : LPPM Nusa Mandiri

Social media is no longer a foreign thing for people in today's technological era, one of the social media that is often used is Twitter. Twitter is used to communicate with other people and Twitter users can also give each other opinions on an issue. By involving 1252 Tweets, this study aimed to use the Support Vector Machine (SVM) algorithm on Tweet data. The processes carried out in this research are crawling, cleaning, translate, labeling, tokenizing, stop words, stemming, SVM classification. .The results showed that the accuracy level of using the SVM algorithm after the param grid was 80.3% using the parameter C = 10; gamma = 0.1; and kernel = rbf as a benchmark in the classification process. This shows that the classification process using the SVM algorithm is quite accurate.

PACKAGE RECEIVER BOX BASED ON IOT USING FUZZY MAMDANI AND MOBILE APPLICATION Ilham Firman Firman Ashari; Arimbi Ayuningtyas
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 8 No 1 (2022): JITK Issue August 2022
Publisher : LPPM Nusa Mandiri

The development of information technology is currently growing, where now everything has been transformed digitally. Consumers today to shop no longer need to come to the market. Consumers shop through e-commerce applications and just wait for the goods between the couriers from the expedition to arrive at their doorstep. Based on a survey conducted on March 10, 2021, with 100 respondents, it was concluded that 62% of the problems experienced were the process of receiving packages and security risks during package delivery, where the courier did not find the owner of the package at home. Answering the IUI problem requires an IoT-based package receiving box that helps make it easier for couriers to send goods and helps package owners to monitor packages that have been delivered by couriers. This package recipient box is accompanied by an ESP32 Cam camera module to scan the QR code receipt number, ESP8266 helps connectivity and android-based mobile applications with a firebase real-time database to make it easier for package recipients to monitor packages. In helping to facilitate decision making, Mamdani fuzzy logic is used. From the research experiment, it was found that the system can carry out the package storage process with an average time of 11 seconds and the time required to update to firebase is around an average of ±3 seconds.

THE DECISION MAKING METHOD FOR AWARDING SCHOLARSHIPS TO STUDENTS USING COMPOSITE PERFORMANCE INDEX ALGORITHM Budy Satria; Acihmah Sidauruk; Muhammad Tofa Nurcholis; Raditya Wardhana; Bister Purba
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Higher education in Indonesia has several programs to help reduce the burden on students, one of which is through a scholarship program. Scholarships given can be obtained with the terms and conditions that apply at each university. Mitra Gama Institute of Technology is one of the private universities in the province of Riau which always runs a scholarship aid program. The problem that has been happening so far is that the procedures carried out are still using a document checking system without involving a weighting system and the right criteria and time constraints have always been an obstacle in determining scholarship recipients. This research was conducted as a solution to create an innovation in the form of making a computerized decision support system using criteria and weight values so that scholarship recipients are on target. Composite performance index is the method used in this study. The purpose of this research is to create a decision support system for the selection of scholarship recipients to be more systematic and time efficient in the process. There are 5 alternatives used and 4 criteria, namely parents' income, GPA, electricity consumption and semester. The results of the research carried out were obtained the 5 highest composite index values, namely MHS4 with a value of 200.00, MHS1 with a value of 134.14, MHS5 with a value of 120.00, MHS3 with a value of 87.00 and MHS2 with a value of 85.71.

APPLICATION OF THE K-NEAREST NEIGHBOR (KNN) ALGORITHM IN SENTIMENT ANALYSIS OF THE OVO E-WALLET APPLICATION Siti Masturoh; Risca Lusiana Pratiwi; M Rangga Ramadhan Saelan; Ummu Radiyah
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Abstract— The OVO application can be downloaded on the Android platform via Google Play, Google play has a review feature on the application product to be downloaded, so that the review can be viewed or accessed by anyone, With these reviews, potential users of the application will see how important it is to consider using an application, problems regarding reviews or sentiment analysis of applications processed using text mining. The purpose of this study is to provide information to prospective OVO application users before using the application which can be seen from the results of giving reviews based on rating or stars (*) in the OVO application review column on Google Play and the authors categorize them into 3 classes, the first class ( 1 to 5 stars, second class (1 and 5 stars) third class by providing labeling grouping (1&2 stars are negative labels, 3 stars are neutral labels and 4&5 stars are positive labels) testing using the k-nearest neighbor method by finding the value of k from the k value of 1-10 to get the highest accuracy value, in order to obtain the highest accuracy value of 84.86% in the 2nd class test and giving a value of k 1 which means that the 1st and 5th star tests get positive values so that they can give a good impression to prospective application users OVO

SENTIMENT ANALYSIS OF ONLINE GOJEK TRANSPORTATION SERVICES ON TWITTER USING THE NAÏVE BAYES METHOD Muhammad Fahmi; Yuyun Yuningsih; Ari Puspita
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Abstract— Social media is the most accessed internet content by internet users in Indonesia. This is not surprising, given the many benefits that social media provides, one of which is the benefit of self-expression. Self-expression can include many things, including emotional openness, which is the openness of a person in conveying the emotions he is feeling. Along with the development of social media, emotional disclosure is ubiquitous in social media, one of which is social media Twitter. With the development of information technology, means of transportation are also developing with the existence of online transportation services. Currently, the use of online transportation services has become a necessity, so it is necessary to conduct a sentiment analysis on online transportation services to find out how the public responds to these online transportation services. The purpose of this study is to analyze community responses by analyzing data in the form of tweets and then classifying them into positive, negative, and neutral classes using the Naïve Bayes method because the error rate obtained is lower when the dataset is large, besides that the accuracy of Naive Bayes and the speed is higher. high when applied to a larger dataset. The results of this study indicate that the neutral sentiment level of public tweets is greater than the level of positive sentiment and negative sentiment with an accuracy of 25.00%.

A COMPARISON OF DIFFERENT KERNEL FUNCTIONS OF SVM CLASSIFICATION METHOD FOR SPAM DETECTION AAIN Eka Karyawati; Komang Dhiyo Yonatha Wijaya; I Wayan Supriana
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Today, the use of e-mail, especially for formal online communication, is still often done. There is one common problem faced by e-mail users, which is the frequent receiving of spam messages. Spam messages are generally in the form of advertising or promotional messages in bulk to everyone. Of course this will cause inconvenience for people who receive the SPAM message. SPAM e-mails can be interpreted as junk messages or junk mail. So that spam has the nature of sending electronic messages repeatedly to the owner of the e-mail. This is abuse of the messaging system. One way to solve the spam problem is to identify spam messages for automatic message filtering. Several machine learning based methods are used to classify spam messages. In this study, a comparison was made between several kernel functions (i.e., linear, degree 1 polynomial, degree 2 polynomial, degree 3 polynomial, and RBF) of the SVM method to get the best SVM model in identifying spam messages. The evaluation results based on the Kaggle 1100 dataset showed that the best model were the SVM model with a linear kernel function and a degree 1 polynomial, where both models returned Precision = 0.99, Recall = 0.99, and F1-Score = 0.98. On the other hand, the RBF kernel produced lower performance in terms of Precision, Recall, and F1-Score of 0.95, 0.95, and 0.94, respectively.

NON-CASH FOOD ASSISTANCE PROGRAM BENEFICIARIES BASED ON COPRAS AND CODAS Dwi Marisa Midyanti; Syamsul Bahri; Hafizhah Insani Midyanti
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Determination of recipients of the Non-Cash Food Assistance Program (BPNT) is a matter that causes problems if it is not carried out in an objective, transparent, and targeted manner. Previous studies on BPNT were based on a specific method, which did not use a negative trend in the criteria. In this study, the Multi-Criteria Decision Making (MCDM) approach was used to recommend the recipients of the BPNT program. Two MCDM models were used in this study, COPRAS and CODAS methods. Spearman's rank correlation method was used to determine the best model and measure the degree of similarity between the results obtained from different models. Spearman rank correlation shows that COPRAS and CODAS have a strong positive correlation of 0.89899. The combined COPRAS-CODAS ranking model produces a very strong positive correlation value of 0.9744 for both methods, so the model is used for recommendations for BPNT program recipients.

ERFORMANCE ANALYSIS OF ALEXNET CONVOLUTIONAL NEURAL NETWORK (CNN) ARCHITECTURE WITH IMAGE OBJECTS OF RICE PLANT LEAVES Adi Fajaryanto Cobantoro; Fauzan Masykur; Kelik Sussolaikah
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Rice is a staple food consumed by Indonesian people, even 75% of the world's population consumes rice and it is mostly found in Asia. Rice derived from pounded rice is a staple food so it can be consumed. In the process of planting rice, pests and diseases are not spared so that it can affect crop yields. Pest and disease attacks need fast, accurate and precise handling so that crop failures. In this paper, we will discuss the classification of leaf diseases of rice plants using the Convolutional Neural Network (CNNN) algorithm, especially the Alexnet architecture. There are 4 types of disease, namely Brown spot, Leafblast, Hispa and Healthy. Models built based on the Alexnet architecture may have differences in the level of accuracy and loss compared to other architectures due to the different stages in the sequential model formation. The dataset used is public data from Kaggle consisting of 4 classes with a total of 1,600 images. In each class the dataset is divided for training, testing and validation datasets with a ratio of 70:20:10. As for tools in the process of training datasets using Google Colab from Google. After going through the stages of the research, the research results obtained are accuracy worth 99,22%, mean average precision worth 0,24 and loss worth 0,05.

EFFECTIVE BREAST CANCER DETECTION USING NOVEL DEEP LEARNING ALGORITHM Irawadi Buyung; Agus Qomaruddin Munir; Putra Wanda
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Ultrasound is one of the most common screening tools for breast cancer detection. However, the lack of qualified radiologists causes the diagnosis process to become a challenging task. Deep learning's promising achievement in various computer vision problems inspires us to apply the technology to medical image recognition problems. We propose a detection model based on the Rapid-CNN to detect breast cancer quickly and accurately. We conduct this experiment by collecting breast cancer datasets, pre-processing, training models, and evaluating the model performance. This model can detect breast cancer with bounding boxes based on the experiment result. In this model, it is possible to detect the bounding box that is more than what it should be, so we applied NMS to eliminate the prediction of the bounding box that is less precise to increase accuracy.

IMPLEMENTATION OF THE SIMPLE MULTI-ATTRIBUTE RATING TECHNIQUE METHOD IN DSS SELECTION OF EXTRACURRICULAR ACTIVITIES Suratun Suratun; Novita Br Ginting; Frieyadie Frieyadie; Fitria Rachmawati; Wisnu Indra Giri
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Extracurricular activities at SMAN 1 Cibungbulang are a means of exploring student competencies. Currently, students can choose extracurriculars without considering their interests and talents. It creates problems for extracurricular coaches because it is challenging to explore student competencies. In this study, the Simple Multi-Attribute Rating Technique (SMART) method was implemented and implemented in a decision support system to overcome this problem. This study used four alternatives: Basketball, Volly, Aikido, and Futsal. At the same time, the criteria are interests, talents, schedules, and achievements. The type of criteria used is benefit criteria. The decision support system is designed using object-oriented design and built on a web-based basis. The decision support system is access by every user registered on the system.

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