Garuda - Garba Rujukan Digital

ANALISIS PEMILIHAN CLUSTER OPTIMAL DALAM SEGMENTASI PELANGGAN TOKO RETAIL Murpratiwi, Santi Ika; Agung Indrawan, I Gusti; Aranta, Arik
Jurnal Pendidikan Teknologi dan Kejuruan Vol 18, No 2 (2021): Edisi Juli 2021
Publisher : Universitas Pendidikan Ganesha

Saat ini pemanfaatan data menjadi fokus dalam bidang pemasaran khususnya untuk menyusun strategi. Agar strategi pemasaran bisa tepat sasaran dibutuhkan segmentasi pelanggan. Data mining khususnya clustering mampu membantu proses segmentasi pelanggan. Dalam penelitian ini, data mining diimplementasikan untuk segmentasi pelanggan UD. XYZ dengan metode K-Means, K-medoids, dan Means.. Tujuan penelitian ini adalah mencari metode dan nilai k terbaik yang dihasilkan dari tiga metode clustering. Penelitian ini menyajikan proses Data Mining dengan menggabungkan model RFM dengan algoritma clustering K-Medoids, X-Means, dan K-Means. Dataset yang telah diimplementasikan ke dalam model RFM digunakan sebagai bahan pengolahan data. Data transaksi dengan jumlah 153.492 diimplementasikan ke dalam model RFM menjadi 10.145 data untuk dilakukan identifikasi pelanggan potensial. Inisialisasi cluster awal pada metode K-Medoids, X-Means, dan K-Means dilakukan secara random. Nilai k dalam penelitian ini diinisialisasi dari 1 sampai 10. Nilai k diimplementasikan secara berulang dan dihitung validasi cluster menggunakan metode David Bouldin Index (DBI) dan jaraj rata-rata cluster dengan centroid. Hasil penelitian menunjukkan K-medoids memiliki nilai validitas yang lebih baik dibandingkan dengan X-Means dan K-Means. Rata-rata nilai DBI yang dihasilkan metode K-Medoids adalah 0,540778. Jumlah cluster terbaik yang dihasilkan adalah 5 cluster, hal ini ditentukan dengan mempertimbangkan jumlah persebaran data pada k = 5 yang menghasilkan nilai sama pada metode K-Medoids, X-Means, dan K-Means. Tingkatan pelanggan yang terbentuk adalah About To Sleep, Customer Needing Attention, Recent Customer, Potential Loyalist, dan Loyal Customers.

Rancang Bangun Aplikasi Transliterasi Aksara Bali Menjadi Huruf Latin Menggunakan Metode Rule Based Pada UTF-16 Berbasis Android Aranta, Arik; Andika, I Gede
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 6 No. 3 (2023): Jurnal RESISTOR Edisi Desember 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v6i3.1426

Balinese script is a script that has been used by Balinese tribes since ancient times, as evidenced by thediscovery of 2,103 ancient lontars using Balinese script in Klungkung, Bali. Currently, Google alreadyhas a virtual keyboard that can be downloaded to a smartphone. This Google keyboard already hasBalinese script mode that the letters was based on Unicode, but it still doesn't have a feature that canread Balinese script into Latin letters. By combining these two problems, a study was designed aboutmaking applications that can preserve Balinese script by utilizing the Balinese script keyboard featureprovided by Google to be transliterated into Latin letters. In this study, a rule based method is used toperform transliteration in order to be able to adjust to the rules of reading Balinese script correctly. It isalso used to provide ID for each Balinese character using hexadecimal based on the UnicodeTransformation Format-16 code for each character. The application was built by implementing of total940 rules and 33.253 words, after testing the application the result obtained from the transliterasionreach 99.4% of succeed from 1104 Balinese script words.

ANALISIS PEMILIHAN CLUSTER OPTIMAL DALAM SEGMENTASI PELANGGAN TOKO RETAIL Murpratiwi, Santi Ika; Agung Indrawan, I Gusti; Aranta, Arik
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 18 No. 2 (2021): Edisi Juli 2021
Publisher : Universitas Pendidikan Ganesha

Saat ini pemanfaatan data menjadi fokus dalam bidang pemasaran khususnya untuk menyusun strategi. Agar strategi pemasaran bisa tepat sasaran dibutuhkan segmentasi pelanggan. Data mining khususnya clustering mampu membantu proses segmentasi pelanggan. Dalam penelitian ini, data mining diimplementasikan untuk segmentasi pelanggan UD. XYZ dengan metode K-Means, K-medoids, dan Means.. Tujuan penelitian ini adalah mencari metode dan nilai k terbaik yang dihasilkan dari tiga metode clustering. Penelitian ini menyajikan proses Data Mining dengan menggabungkan model RFM dengan algoritma clustering K-Medoids, X-Means, dan K-Means. Dataset yang telah diimplementasikan ke dalam model RFM digunakan sebagai bahan pengolahan data. Data transaksi dengan jumlah 153.492 diimplementasikan ke dalam model RFM menjadi 10.145 data untuk dilakukan identifikasi pelanggan potensial. Inisialisasi cluster awal pada metode K-Medoids, X-Means, dan K-Means dilakukan secara random. Nilai k dalam penelitian ini diinisialisasi dari 1 sampai 10. Nilai k diimplementasikan secara berulang dan dihitung validasi cluster menggunakan metode David Bouldin Index (DBI) dan jaraj rata-rata cluster dengan centroid. Hasil penelitian menunjukkan K-medoids memiliki nilai validitas yang lebih baik dibandingkan dengan X-Means dan K-Means. Rata-rata nilai DBI yang dihasilkan metode K-Medoids adalah 0,540778. Jumlah cluster terbaik yang dihasilkan adalah 5 cluster, hal ini ditentukan dengan mempertimbangkan jumlah persebaran data pada k = 5 yang menghasilkan nilai sama pada metode K-Medoids, X-Means, dan K-Means. Tingkatan pelanggan yang terbentuk adalah About To Sleep, Customer Needing Attention, Recent Customer, Potential Loyalist, dan Loyal Customers.

ANALISIS SENTIMEN MASYARAKAT TERHADAP KEBIJAKAN PENERAPAN PPKM DI MEDIA SOSIAL TWITTER DENGAN MENGGUNAKAN METODE XGBOOST Widiarta, I Putu Angga Purnama; Dwiyansaputra, Ramaditia; Aranta, Arik
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 5 No 2 (2023): September 2023
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v5i2.342

Corona Virus Disease (Covid-19) is a virus that causes respiratory infections in humans. Indonesia is a country that has been infected with this virus, the implementation of restrictions on community activities (PPKM) is implemented by the government as a policy to reduce the spread of Covid-19. Pros and cons arise due to the impact of the policy. Therefore, assessing how public opinion or sentiment is towards this policy is important to do. This study aims to implement the XGBoost algorithm in the sentiment classification process. Sentiment analysis targets public opinion on Twitter, the dataset used is 1958 positive tweets and 3980 negative tweets. At the preprocessing stage, case-folding, stopwords removal, tokenizing, and stemming are carried out. Giving weights to terms uses the Term Frequency-Relevance Frequency method to turn each term into a number. In the final stage, classification is carried out by implementing the XGBoost method with optimal hyperparameter scores. K-fold cross validation is used to evaluate model performance. Based on the evaluation results, the best performance was obtained by a model with a hyperparameter value with an n_estimator of 1000, a learning_rate of 0.1, a max_depth of 6, a subsample of 1, a gamma of 0 and utilizing the stem-ming process in preprocessing with an accuracy value of 85.27%. precision of 86.07%, and recall of 85.23%.

IMPLEMENTASI METODE PROTOTYPE DALAM SISTEM ABSENSI SISWA SMK NEGERI 1 SIKUR Tyas, Tiya Suryaning; Afwani, Royana; Murprawati, Santi Ika; Aranta, Arik
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 6 No 1 (2024): March 2024
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v6i1.366

The incorporation of information technology is critically important in various aspects of life, with education being no exception. Technology has demonstrated its efficacy in supporting the operations of numerous institutions, including educational establishments. Nevertheless, despite the swift progress of technology, many institutions, particularly schools, still adhere to traditional systems in their daily operations. This includes the procedure for tracking student attendance, which can result in inefficiencies. This research endeavors to address this issue by conceptualizing, constructing, and implementing a web-based system for managing student attendance, focusing on streamlining the process of recording and handling attendance data. This system utilizes web technology and a database to establish a platform, with CodeIgniter4 serving as the fundamental framework for website development, following the prototype method. The research is carried out at SMKN 1 SIKUR and the system will record student attendance data, which will be stored in the database of SMK N 1 Sikur, and is expected to replace the current method of recording student attendance. The percentage of respondents with a "strongly agree" opinion increased from 36% to 52% after the update to the previous prototype. It is hoped that further development can be undertaken to facilitate direct implementation.

RANCANG BANGUN ALGORITMA KONVERSI SUARA BERBAHASA INDONESIA MENJADI TEKS LATIN BERBAHASA SASAK MENGGUNAKAN METODE DICTIONARY BASED Shabrina, Marwati Maryam; Aranta, Arik; Irmawati, Budi
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 6 No 1 (2024): March 2024
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v6i1.371

As time goes by, the use of the Sasak language among the people of Lombok is decreasing. In fact, the Sasak language is the identity of the island of Lombok which needs to be preserved as a heritage for the younger generation. The increasingly rapid development of technology has encouraged the emergence of innovation in creating various inventions that can facilitate human activities. One innovation that can be developed is speech to text technology. This technology can recognize human voices and then convert them into text. This is of interest to the author in designing a system that implements Google’s speech to text API to translate Indonesian words or sentences into Sasak. The translation from Indonesian to Sasak was carried out by applying a dictionary based system to produce an appropriate translation. The testing process was carried out by translating 25 sentences taken from the Sasak-Indonesian Dictionary and consisting of 117 words. In this research, there were two stages of testing carried out. The first test was carried out to determine the accuracy of the results of the Indonesian translation into Sasak using the dictionary based method. The second test was carried out to determine the accuracy of the Google Speech API in recognizing voice input and then converting it into text. From the first test, the system accuracy results in translating Indonesian to Sasak using the dictionary based method were 100% and the error rate was 0%. Meanwhile, from the second test, the results showed that the system could implement the Google Speech API to translate Indonesian words or sentences into Sasak with an accuracy of 99.14%.

RANCANG BANGUN SISTEM INFORMASI PEMESANAN TIKET TRAVEL BERBASIS WEBSITE MENGGUNAKAN METODE EXTREME PROGRAMMING (STUDI KASUS: FAJRI JAYA TRAVEL) Sansabila, Rosa; Albar, Moh. Ali; Aranta, Arik
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 2 (2025): September 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i2.481

Fajri Jaya Travel is a transportation service provider based in West Nusa Tenggara. In conducting its business activities, the company still uses the manual method, where prospective passengers are required to either visit the ticket agent in person or contact them by phone to book tickets or inquire about schedules, ticket prices, or seat availability. This method is inefficient and time-consuming, especially for people living far from ticket agents or having difficulties accessing information quickly. Furthermore, this approach is susceptible to recording errors, such as incorrect passenger data or duplicate seat numbers. To address this issue, this study aims to develop an online ticket booking system for Fajri Jaya Travel. This system will allow prospective passengers to obtain departure schedules and book tickets through a website, without the need to visit a ticket agent in person and minimizing data entry errors. This system is built using the Bootstrap and Laravel frameworks with the Extreme Programming development method. The system was tested using Black Box Testing to assess functionality and the Mean Opinion Score method to evaluate user satisfaction, resulting in average scores of 4.4 from administrators, 4.0 from drivers, and 4.55 from general users, indicating a high level of satisfaction.

Implementasi Fuzzy C-Means untuk Pengelompokan Daerah berdasarkan Persebaran Penularan Covid-19 Nugraha, Gibran Satya; Dwiyansaputra, Ramaditia; Bimantoro, Fitri; Aranta, Arik
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 1: Februari 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023105796

Peningkatan kasus Covid-19 di Indonesia memberikan rasa khawatir bagi hampir seluruh masyarakat, Dilihat dari persebaran tiap provinsi untuk kasus positif, sembuh, dan meninggal tidak menunjukkan sebuah grafik yang linier. Seperti pada data harian kasus per provinsi di akhir bulan April 2021 dimana kasus positif dan sembuh terbanyak terdapat pada Provinsi DKI Jakarta, untuk kasus meninggal Provinsi Jawa Timur berada di posisi pertama, dan di posisi empat untuk kasus positif dan meninggal. Data persebaran yang abstrak ini membuat pengelompokan persebaran Covid-19 di Indonesia menjadi sukar untuk dilakukan. Penelitian ini mengelompokkan provinsi-provinsi berdasarkan persebaran Covid-19 di Indonesia dengan cara mengimplementasikan metode Fuzzy C-means serta metode Elbow. Fuzzy C-means adalah metode pengelompokan berbasis fuzzy yang dapat melakukan persebaran data pada seluruh cluster berdasarkan derajat keanggotaan yang dimilikinya. Sedangkan untuk menentukan jumlah cluster terbaik akan diimplementasikan metode Elbow. Metode Elbow membandingkan perbandingan hasil sum square error (SSE) dari setiap cluster dan mendapatkan jumlah cluster terbaik dari perubahan nilai SSE yang signifikan atau membentuk siku (elbow). Penggunaan Fuzzy c-means sebagai metode pengelompokan untuk mencari tahu seberapa besar pengaruh yang dimiliki setiap data terhadap masing-masing cluster. Karera metode-metode sebelumnya yang digunakan pada objek yang sama hanya melakukan pengelompokan saja secara tegas, tanpa memperhatikan besarnya pengaruh sebuah data terhadap seluruh cluster. Pengelompokan dilakukan menjadi tiga buah cluster atau kelompok berdasarkan parameter kasus positif, sembuh, dan meninggal Covid-19 per 27 April 2021. Cluster 1 hanya terdiri tiga provinsi yaitu Jawa Barat, Jawa Tengah, dan Jawa Timur. Cluster 2 DKI Jakarta, dan sisanya masuk ke cluster 3. AbstractThe increase in Covid-19 cases in Indonesia raises concerns for all parties, When viewed for the distribution of each province, positive, recovered and dead cases do not show a linear graph. As in the daily data of cases per province at the end of April 2021 where the most positive and recovered cases were in DKI Jakarta Province, while for dead cases, East Java Province was in first position, and in fourth position for positive and dead cases. This abstract distribution data makes it difficult to classify the distribution of Covid-19 in Indonesia. This study will group provinces based on the spread of Covid-19 in Indonesia using the Fuzzy C-means method and the Elbow method. Fuzzy C-means is a fuzzy-based grouping method that allows all data to be members of all clusters formed with their respective degrees of membership. Meanwhile, to determine the best number of clusters, the Elbow method will be implemented. The Elbow method compares the sum square error (SSE) results from each cluster and gets the best number of clusters from a significant change in the SSE value or forms an elbow. The use of Fuzzy c-means as a grouping method to find out how much influence each data has on each cluster. Because the previous methods used on the same object only grouped it explicitly, without paying attention to the effect of one data on the entire cluster. The grouping was carried out into three clusters or groups based on the parameters of positive cases, recovered, and died of Covid-19 as of 27 April 2021. Cluster 1 only consisted of three provinces, namely West Java, Central Java, and East Java. Cluster 2 DKI Jakarta, and the rest go to cluster 3. It takes a grouping test to determine how accurate the results are.

Sosialisasi Pemasaran Digital Bagi Petani dan UMKM di Desa Mujur, Lombok Tengah, NTB: Digital Marketing Socialization for Farmers and UMKM in Desa Mujur,Lombok Tengah, NTB Nugraha, Gibran Satya; Dwiyansaputra, Ramaditia; Bimantoro, Fitri; Aranta, Arik
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 5 No. 1 (2024): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v5i1.1180

Upaya Pemerintah Republik Indonesia dalam mendorong kemandirian desa melalui optimalisasi pemasaran hasil bumi menggarisbawahi pentingnya integrasi strategi pemasaran digital di pedesaan. Pengabdian ini mengeksplorasi kasus Desa Mujur di Pulau Lombok, yang dikenal sebagai "bumi Sasak" dan memiliki potensi sumber daya alam yang melimpah. Dengan mayoritas penduduknya bekerja sebagai petani, Desa Mujur menghadapi tantangan dalam memperluas pasar lokalnya, yang sebagian besar terbatas pada penjualan hasil bumi di pasar atau kerja sama dengan toko dan kios lokal. Pengabdian ini menyoroti pentingnya pemasaran digital sebagai alat untuk meningkatkan potensi pendapatan lokal dengan mencapai konsumen di luar wilayah geografis desa. Temuan dari survei Badan Pusat Statistik pada tahun 2022 menunjukkan bahwa penggunaan platform pesan instan, media sosial, dan marketplace merupakan strategi pemasaran digital yang paling banyak digunakan oleh pedagang online. Pengabdian ini menggaris bawahi bagaimana sosialisasi dan pemanfaatan teknologi digital dapat menjadi faktor krusial dalam era digital saat ini, tidak hanya untuk perusahaan besar tetapi juga untuk UMKM (Usaha Mikro, Kecil, dan Menengah), dalam meningkatkan penjualan dan memperluas pasar dalam lingkungan yang kompetitif. Platform digital seperti media sosial, e-commerce, dan aplikasi mobile menawarkan peluang baru yang belum pernah ada sebelumnya. Proses sosialisasi memungkinkan pelaku usaha memahami dan mengimplementasikan strategi digital yang efektif, termasuk pemasaran digital, SEO (Search Engine Optimizer, dan penggunaan media sosial untuk promosi, serta mengoptimalkan pengelolaan toko online. Oleh karena itu, sosialisasi teknologi dalam penjualan tidak hanya fokus pada adopsi alat baru, tapi juga pada transformasi mindset dan model bisnis, yang esensial untuk pertumbuhan dan keberlangsungan usaha di masa depan.

Early Detection of Asymptomatic Covid-19 Infection with Artificial Neural Network Model Through Voice Recording of Forced Cough Nisa, Aisyah Khairun; Wijaya, I Gede Pasek Suta; Aranta, Arik
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1812

SARS-CoV-2 is a virus that spreads the infection known as COVID-19, or Coronavirus 2019. According to data from the World Health Organization as of March 15, 2021, Indonesia has 1,419,455 cumulative cases and 38,426 cumulative deaths, ranking third among countries in terms of fatalities, behind Iran and India. Because COVID-19 was disseminated through direct contact with respiratory droplets from an infected individual, it spread swiftly and widely. According to the American Centers for Disease Control and Prevention, more than 50% of transmission rates are anticipated from asymptomatic individuals. The antigen tests have an accuracy of results ranging from 80â€“90% and are utilized for early detection of COVID-19. The cost of the antigen test is set to increase as of September 3, 2021, with prices ranging from IDR 99.000 to IDR 109.000; however, researchers are steadfastly searching for the best alternate methods for the early diagnosis of COVID-19. According to MIT News Office, a forced cough recording can identify an asymptomatic COVID-19 infection. Through the vocal recording of a forced cough, this study uses an artificial neural network (ANN) deep learning model to identify asymptomatic COVID-19 patients. The Artificial Neural Network (ANN) can distinguish asymptomatic people from forced cough recordings with an accuracy of up to 98% and a loss value of less than 3% by employing oversampling data. This model can be applied as a free, universal method for the early identification of COVID-19 infection.

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