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INDONESIA
KOMPUTIKA - Jurnal Sistem Komputer
Published by Universitas Komputer Indonesia
ISSN : 22529039     EISSN : 26553198     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Jurnal Ilmiah KOMPUTIKA adalah wadah informasi berupa hasil penelitian, studi kepustakaan, gagasan, aplikasi teori dan kajian analisis kritis di bidang kelimuan bidang Sistem Komputer.
Arjuna Subject : -
Articles 218 Documents
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Pemberian Bantuan Kartu Indonesia Pintar menggunakan Metode Weighted Product Irmayanti, Hani; Gaffar, Abdul Majid
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.9704

Abstract

ABSTRACT – The purpose of this research is to determine which students meet the criteria for receiving assistance from the Indonesia Smart Card program, so that the aid can be targeted appropriately. The Indonesia Smart Card cannot be given to all financially disadvantaged students who meet the criteria, as the quota for the card is very limited. The method used in this study is the Weighted Product method. The Weighted Product method is a decision-making method that uses multiplication to connect attribute values, where each attribute must be raised to the power of the corresponding attribute weight. The results obtained from this study are the ranking of students who meet the predetermined criteria according to the specified quota. The ranking is obtained through the process of determining the criteria first, then determining the values for each alternative, improving the weights of the implemented criteria, calculating the s-vector, calculating the v-vector, and finally ranking. The conclusion of this study is that the student ranking process is in accordance with the available quota and can be carried out transparently, accountably, and objectively. The Student Affairs Office is greatly helped in making decisions, so that aid can be targeted more accurately. Keywords – Indonesia Smart Card; Weighted Product; Decision-making system; Assistance; Ranking
Aplikasi Probe Untuk Penilaian Capaian Pembelajaran Mahasiswa Pada Kurikulum OBE (Outcame-Based Education) Ishaq, Usep Mohamad; Wicaksono, Mochamad Fajar; Nurhayati, Sri
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.9763

Abstract

The purpose of this study was to create a web-based PROBE (OBE measurement) application that can provide information on the results of learning assessments using the OBE (outcome-based education) curriculum to students, and provide convenience to related parties in managing the OBE curriculum in the Computer Systems Study Program. OBE is a teaching approach that influences the learning process starting from curriculum design, learning outcomes, learning methods, and forms of evaluation of learning. Implementation of the OBE curriculum will not work without a system for measuring student learning outcomes. To carry out these measurements, it is necessary to design and build a student learning achievement assessment system through a software application in order to obtain ease of input, information processing, and access to the achievement of each learning outcome in CPL and CPMK. Therefore, the solution given to answer this problem is the need for an OBE application that can provide information on the results of student learning assessments. The contribution of this research is to provide convenience to related parties in viewing student learning achievements, so that it can be used for policies in terms of curriculum revision in Study Programs. The method used in this research is a case study approach where the case studies are taken from curriculum data for the 2020 Computer Systems Study Program. For making applications using the waterfall method, and analysis of functional system requirements using a structured approach. The results of this study indicate that 100% of the functionality of the application is running according to the functional requirements made, and the system has provided information on student achievement scores per academic year.
Perbandingan Kinerja Algoritma Multinomial dan Bernoulli Naïve Bayes dalam Mengklasifikasikan Komentar Cyberbullying Dhuhita, Windha Mega P; Zone, Fritz
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.9767

Abstract

In today's era, amidst the rapid development of technology, many people misuse technology to do unpleasant things to others, including bullying that is done using social media called cyberbullying. Therefore, researchers classify social media comment data to determine whether it includes bullying or not. The purpose of this study is to classify social media comment data, including cyberbullying or not, by first comparing the performance between Naive Bayes Multinomial and Bernoulli algorithms in classifying such comment data. The researchers compared the Naive Bayes Classifier model, Multinomial and Bernoulli, to obtain the best model. The researchers also compared the use of the Bag of Words and TF-IDF feature extraction methods to improve the accuracy of the algorithms used. The results of the study show that the Naive Bayes Multinomial model algorithm obtained higher accuracy and faster average processing time compared to the Bernoulli model. The use of the Bag of Words feature extraction method can also significantly increase accuracy compared to TF-IDF.
Klasifikasi Kematangan Pisang Menggunakan Metode Convolutional Neural Network Hanifah, Afifah Inas; Hermawan, Arief
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.9999

Abstract

ABSTRACT – Bananas are plants from the Southeast Asian region and belong to the genus Musa and the family Musaceae. Grown in tropical and subtropical regions, bananas are one of the agricultural commodities with the largest production compared to other fruits. Indonesia is one of the countries that produce the largest bananas in the world. The yields are then sorted based on the level of ripeness by looking at the color change of the banana skin. However, the process of sorting bananas requires a lot of time and effort due to the large production of bananas. In addition, differences in the assessment of each individual on changes in the color of banana peels result in an unstable or consistent sorting of bananas. Therefore, this study intends to create a ripeness classification system for bananas based on changes in skin color with the aim that the sorting process can be carried out efficiently and accurately. The color variants used range from dominant green for unripe bananas, dominant yellow for ripe bananas and blackish brown spots for overripe bananas. The method used is a Convolutional Neural Network with a self-designed architecture. The results showed that the accuracy reached 88% with a learning rate setting of 0.001 and a maximum epoch limit of 15. Keywords – Classification; Banana Fruit; Convolutional Neural Network; Deep Learning; Computer Vision
Implementasi Metode Weighted Moving Average (WMA) Pada Prediksi Harga Bahan Pokok Ustadatin, Fina; Muqtadir, Asfan; Arifia, Amaludin
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10304

Abstract

Staples are goods or commodities that are needed routinely in everyday life. Staples have an important role in meeting food needs. Availability, price, and accessibility of basic commodities can affect people's welfare. Prices of basic commodities tend to experience price volatility. This makes people uneasy and will affect the level of purchase of each staple. The purpose of this research is to predict the price of staple goods in the Tuban district market, East Java. The method used in this study is the Weighted Moving Average (WMA), to predict the price of materials using data on prices of staple foods that existed previously. This method is used in order to obtain accurate forecasting results. The Weighted Moving Average method is suitable for predicting the price of basic commodities, because it is able to provide predictions using existing data, namely previous data and can future prices. The results of this study are that the highest MAPE value is 0.3 for the staple ingredient premium rice, and the lowest MAPE value is 5.3 for the staple ingredient red chili. Keywords – Basic commodities; Forecasting; Weighted Moving Average.
Klasifikasi Pemenuhan Pilar Sanitasi Puskesmas Menggunakan Metode Naive Bayes Syam, Muhammad Farhan; Hayati, Lilis Nur; Syafie, Lukman
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10336

Abstract

Sanitation is an attempt to maintain the cleanliness and condition of the surrounding environment. In fulfilling the sanitation pillar in each region, of course we also need the role of health agencies to trigger and provide education. In the village where the scope of the Bontomangape Health Center is located, it is known that the fulfillment of the sanitation pillar is still uneven. Based on this, the author intends to classify the fulfillment of the sanitation pillars of the puskesmas using the Naive Bayes method so that the results of this classification can be used as a benchmark for villages that need to be prioritized by sanitation workers. The classification results obtained were 55 implemented and 20 not implemented for Bontomangape village, 70 implemented and 5 not implemented for Campagaya village, 60 implemented and 15 not implemented for Kalenna village, 45 implemented and 30 not implemented for Parambambe village, 52 implemented and 23 not implemented implemented for Parangmata village, 64 implemented and 11 not implemented for Parasangangberu village, and 57 implemented and 18 implemented for Pattinoang village. The classification results obtained an average accuracy value of 95,81%, a precision value of 94,78% and a recall value of 100%. Keywords – Sanitation; Health; Puskesmas; Classification; Naive Bayes
Analisis Cluster Kualitas Pemuda di Indonesia pada Tahun 2022 dengan Agglomerative Hierarchical dan K-Means Novaldi, Jeremia; Wijayanto, Arie Wahyu
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10348

Abstract

Youth is the generation that will hold the future of Indonesia. According to BPS, a quarter of Indonesia's population are youth. Thus, the government needs an overview of the current quality of youth to formulate appropriate policies for each region. This study aims to classify provinces in Indonesia based on youth data using agglomerative hierarchical and K-Means. According to the value of the internal validation and stability index, the agglomerative hierarchical, using Ward's method, with 2 clusters was chosen as the best clustering method. This method produces 2 clusters consisting of 11 and 23 provinces respectively. In general, Cluster 1 contains provinces with better youth quality, where the average youth schooling years, the percentage of youth with internet access, the percentage of youth with health insurance are higher than Cluster 2 despite having a higher unemployment rate. In contrast, Cluster 2 has a higher average score on the Youth Sickness Rate, the percentage of youth with first marriage age 16 – 18 years, and the percentage of young women who give birth to babies with LBW. Keywords – Clustering; Hierarchical; K-Means; SDGs; Youth
Klasifikasi Rentang Usia Dan Gender Dengan Deteksi Suara Menggunakan Metode Deep Learning Algoritma CNN (Convolutional Neural Network) Karenina, Vita; Erinsyah, Moh Fiqih; Wibowo, Dega Surono
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10516

Abstract

ABSTRACT – In this research, we delve into the identification of human voices based kata.on gender by leveraging the differences in vocal characteristics between males and females. In addition to differences in vocal tract size, factors such as length, thickness, and vocal cord stiffness also play a role in producing differences in the fundamental frequency of voice between the two genders. The fundamental frequency of voice becomes one of the indicators used in acoustic analysis for gender classification based on voice. In the automatic classification of voices, sound processing techniques and machine learning are pivotal in system development. The method of gender recognition based on voice involves acoustic analysis using voice features such as fundamental frequency, formants, duration, intensity, and intonation patterns. The research yielded an accuracy of 92% through modeling using CNN on audio data, and the testing results were quite satisfactory in terms of classification. This model's results have been implemented into a Flask API, serving as a connection or backend for an application. The application takes the form of a movie recommendation system developed using the Flutter framework. Consequently, within the movie application, there is voice clustering or classification of user voices to provide film recommendations within the application Keywords – Deep Learning, Voice Recognition, Audio Classification, CNN, Gender
Alat Pengolah Limbah Rumah Tangga Menjadi Kompos Berbasis Mikrokontroler Khakim, Lukmanul; Budihartono, Eko
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10616

Abstract

Households are the largest contributor to waste, various types of waste are generated, ranging from organic, non-organic waste and so on. If each household produces 2 kg of waste every day, and the waste is immediately disposed of in a temporary landfill (TPS), then a very large amount of waste is buried in the TPS. Therefore, a tool is needed that functions to process waste that can be recycled into compost, namely waste or food waste classified as organic waste. The tool in question consists of a nema 17 stepper motor as a cutter and stirrer for garbage to mix with the soil, a YL-69 sensor as a soil moisture detector, a DS18B20 sensor as a soil temperature detector and two mini pumps as a water supply and EM4. From the results of this study, YL-69 detects soil moisture of 17% to 86%, meaning that soil moisture increases, so the stepper will be active to stir the soil and organic waste. Furthermore, DS18B20 detects soil temperatures of 25°C to 34°C, meaning that when the temperature is between 30°C to 34°C, the composting process takes place, the water supply and EM4 stop automatically. Keywords – Organic Waste; Compost; Microcontroller, DS18B20, YL-69.
Prediksi Harga Cabai Rawit di Provinsi Jawa Timur Menggunakan Metode Fuzzy Time Series Model Lee Komaria, Vida; Maidah, Nova El; Furqon, Muhammad Ariful
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10644

Abstract

ABSTRACT - East Java is the province with the most significant amount of chili pepper production in Indonesia based on data from BPS in 2021 which is around 41.75. Chili pepper is a commodity that high price fluctuations that will impact several parties, so a mechanism is needed to predict the price of chili pepper to become a consideration in decision making. Lee's fuzzy time series method can be used to predict time series stationary or non-stationary data. The research was conducted using historical data on the price of red and green chili peppers in East Java Province from April 2017 to February 2023 with a weekly data period of 307 data. The Z1 and Z2 values used to get the smallest error results are Z1 = 950 and Z2=400 for red chili peppers while for green chili peppers values the Z1 and Z2=100. The error value of forecasting red chili pepper prices is MAE = 4,469.04 RMSE = 6,138.64 MAPE = 13.09% (good MAPE value category) and the error value for green chili pepper is MAE = 1,486.15 RMSE = 2,211.06 and MAPE = 6.72% (very good MAPE value category). Keywords – forecasting; Lee’s fuzzy time series; chili pepper price; MAPE; Python

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