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INDONESIA
TIN: TERAPAN INFORMATIKA NUSANTARA
ISSN : -     EISSN : 27227987     DOI : -
Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 582 Documents
Analisis Kualitas Layanan Pada Akun Instagram Sebagai Media Informasi Bagi Siswa/i dengan Metode E Servqual Septia G, Andi; Mustuka U, Ersa; Divara A, Audry; Borroek, Maria Rosario
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4881

Abstract

The development of information technology in Indonesia is increasing rapidly from day to day. One of the effects of the development of information technology is that it can absorb more positive things, users can adapt and get the information needed by society. Instagram is a photography-based social networking service. Instagram allows users to take photos, videos and add filters to add an interesting impression to the photos. Primarily, Instagram is more focused on smartphone devices such as Android and iOS. The research aims to analyze the quality of service on the YADIKA Vocational School Jambi City Inatagram account as an information medium from the e-servqual variable. Using the e-servqual method, the variables used are Compesation, Contact, Efficiency, Fullfillment, Privacy, Responsiveness, System Availability. The data collection technique used is by distributing questionnaires or questionnaires. The data statistical methods used are descriptive statistics and Partial Least Square (PLS) with the SmartPLS version 3.0 program. The results of this researcher are from 7 E-Servqual variables, 4 which significantly influence the Service Quality on the Instagram account of SMK YADIKA JAMBI CITY, namely Efficiency, Privacy, Compensation, Contact and 3 variables which do not influence the Service Quality of the Instagram account of SMK YADIKA JAMBI CITY, namely Fullfillment, System Availability, Responsiveness.
Perbandingan Algoritma Decision Tree dan Support Vector Machine Dalam Pemilihan Calon Mahasiswa Penerima KIP-K Kanaka, Nayaka Al Syahreal; Heriansyah, Rudi; Puspasari, Shinta
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4902

Abstract

KIP Kuliah is tuition assistance from the government for high school / equivalent graduates who have good academic potential but have economic limitations. There are many things that should be considered by universities before selecting prospective students who receive KIP Lecture so that selection can be done using machine learning and classification algorithms. In this research, two machine learning algorithms will be used including: Decision Tree and Support Vector Machine (SVM). Furthermore, these two algorithms will be tested and compared the final results. Both algorithms have different results. The highest level of accuracy, precision, recall, and F1 score is 100%. This value can be achieved by the Decision Tree algorithm because the dataset used is suitable for it to solve. Therefore, the Decision Tree algorithm is recommended to be used in selecting KIP College student candidates.
Implementasi Algoritma C4.5 Untuk Mengukur Tingkat Kepuasan Mahasiswa yang Berlangganan Wifi Indihome Kiswara, Qodrat; Safii, M.; Andani, Sundari Retno; Lubis, Muhammad Ridwan; Renaldi, Renaldi
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4918

Abstract

The urgency of research on satisfaction levels is closely related to the success and desires of a business or organization. Without a good understanding of customer satisfaction, a company or organization may lose market share, face declining sales, or even face failure. Therefore, this research must be carried out regularly and continuously. The purpose of this research is to determine the level of customer satisfaction and to determine the dominant service quality that influences the quality of service provided by PT Telkom Indihome to customers. In this research, researchers used the C4.5 Algorithm data mining technique. The research data source used was by making observations and distributing questionnaires to customers of PT Telkom Pematangsiantar City. In this case, researchers used assessment attributes, namely service quality, accessibility and product quality. This research is expected to provide information and input to PT Telkom Indihome in the form of evaluations in improving network quality. The results of the research conducted by the author obtained the following conclusion, namely that Data Mining with the C4.5 Algorithm can classify the measurement of satisfaction levels of STIKOM Tunas Bangsa students who subscribe to Indihome WiFi. The accuracy results obtained by this research were 75.00% with the average student who subscribed to Indihome WiFi stating that they were satisfied.
Peran Komunikasi Interpersonal Keluarga dalam Menggali Potensi Individu Berkebutuhan Khusus untuk Mandiri dan Berdaya Setyaningtyas, Emilya; Yulianti, Wulan; Hery, Della Melianie
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4943

Abstract

The Chairperson of the National Commission on Disability revealed that there is still a negative stigma towards individuals with special needs. This is reflected in several incidents where individuals with special needs experienced rejection and inappropriate treatment. Twenty-three cases of special protection of children with special needs were reported to the Indonesian Child Protection Commission (KPAI). Handling individuals with special needs has its challenges, especially when entering adulthood, where parents have an essential role as educators, managers, and mentors. Interpersonal communication is one form of communication that is important to use within the family. Individuals with special needs often have difficulty processing language literally and face barriers in speaking and communicating. As the closest party, the family should be able to apply interpersonal communication well with people with special needs, but many cases still occur. This study aims to review the role of family interpersonal communication in developing the potential of individuals with special needs to be independent and productive. The approach used in this research is qualitative with descriptive methods by collecting data through in-depth interviews and focus group discussions (FGDs). The findings in this study show that all dimensions of the role of interpersonal communication have been implemented by families, who are the primary key to developing their children's potential as individuals with special needs to be independent and productive. The results showed that it is undeniable that, as humans, family members can also have frustrations and even need special handling to be ready to have a family as individuals with special needs. All family members help each other and have a harmonious relationship, and a sense of perseverance is formed from the collaboration of fellow families who experience similar experiences. Social media can be a medium for individuals with special needs to show their talents as independent individuals.
Analisis Sentimen Jogja Darurat Sampah di Twitter menggunakan Ekstraksi Fitur Model Word2Vec dan Convolutional Neural Network Yusanto, Yoga; Akbar, Mutaqin
TIN: Terapan Informatika Nusantara Vol 4 No 10 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i10.4952

Abstract

Due to a waste emergency, the Special Region of Yogyakarta has garnered public attention and sparked discussions. Numerous community groups express their opinions through various social media platforms, especially Twitter. It's undeniable that Twitter is currently one of the places for freely expressing opinions. Therefore, sentiment analysis plays a crucial role in efforts to categorize public opinions on something trending or viral into three categories: positive, negative, and neutral. In this study, the dataset was obtained using scraping techniques and the tweetscraper tool from the APIFY actor web.harvester/easy-twitter-search-scraper. The method employed in this analysis is the Convolutional Neural Network (CNN) classification method using Word2Vec model extraction. The study involves 505 tweets in Bahasa Indonesia with the hashtags #JogjaDaruratSampah (#JogjaDaruratSampah) and #TPSTPiyungan as data. Out of these, 381 tweets are utilized as training data, and the remaining 124 tweets are used as test data. The highest accuracy in testing the training data was achieved in the 19th epoch with a 90% accuracy rate. It can be concluded from the testing process that this study can identify positive, negative, and neutral sentiments with an accuracy of 53%. The sentiment analysis results indicate a significant amount of negative tweets, accounting for 49.7% of the total 505 tweets.
AR-FootIN 4.0 : Aplikasi Pengenalan Teknologi Industri 4.0 Pada Bidang Alas Kaki Berbasis Mobile Augmented Reality Prananda, Alifia Revan; Marwanto, Marwanto; Frannita, Eka Legya; Hidayat, Anwar
TIN: Terapan Informatika Nusantara Vol 4 No 10 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i10.4956

Abstract

Rapid development of technology gave a positive impact on the footwear industry. The emergence of various types of technology as part of the industrial revolution 4.0 has greatly helped various types of work in industry. However, technology also need to be supported by good quality resource. Knowledge regarding how to use and maintain these technologies is needed so that the benefits of these technologies can be utilized. An alternative way is by developing good quality of human resource to being proficient in using technology. Furthermore, cultivating technological literacy is also one of the essential factors. Regarding to this situation, we proposed research that aims to develop the AR-FootIN 4.0 application as a learning media for introducing industry 4.0 in the footwear sector. This learning media is developed by employing mobile augmented reality. The proposed learning media is developed by using the SDLC method. The resulted learning media is then evaluated by conducting two types of evaluation, which are expert evaluation and user evaluation. The results of expert evaluation and user evaluation obtain a percentage of 93.33% and 86% respectively, which means that the feasibility of the application to support the technological literacy process in the footwear industry is very good.
Klasifikasi Dialek Bahasa Inggris British dan Amerika menggunakan Support Vector Machine Kuswandaru, Kuswandaru; Akbar, Mutaqin
TIN: Terapan Informatika Nusantara Vol 4 No 10 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i10.4965

Abstract

English has become an international language used in various fields, including education, business, and tourism. Indonesia, having become a member of the AEC (Asean Economic Community), makes it increasingly important for Indonesian society, especially the younger generation, to master English proficiently and accurately. English, as an international language, encompasses numerous dialects, such as British and American dialects. This research is motivated by the issue that differences between British and American English dialects can affect understanding and communication in educational, business, and everyday life contexts. Identifying and classifying dialects in English speech is crucial to aid both native and non-native speakers in better understanding communication contexts. This study aims to develop a classification method using the Support Vector Machine (SVM) algorithm to distinguish between British and American English dialects in speech. By leveraging SVM, this research will attempt to identify linguistic features that differentiate between these dialects, such as intonation, vowels, consonants, and rhythm patterns obtained from sound feature extraction using Mel Frequency Cepstral Coefficients (MFCC). In this model training phase, a dataset comprising 720 speech samples collected from various text-to-speech service provider websites is utilized to represent both dialects. Subsequently, the trained model is tested using 24 test data collected from original recordings of several individuals to evaluate its accuracy. The results of this research yield an accuracy rate of 91.6% on the model with a configuration of Cost value 1, gamma 0.001, and polynomial kernel. From these results, it can be concluded that this model exhibits a sufficiently high accuracy, with 2 misclassifications out of 24 test data.
Klasifikasi Keterlambatan Pembayaran Sumbangan Pembinaan Pendidikan Menggunakan Algoritma Naïve Bayes dan Support Vector Machine Umar, Huzaifah; Kusumawati, R.; Imamudin, M.; Rohman, Moh. Ainur
TIN: Terapan Informatika Nusantara Vol 4 No 11 (2024): April 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i11.4969

Abstract

Payment delinquency of SPP is a commonly occurring issue in school. It affects the salary of teachers and staffs alongside school’s various development program. The study aims to classify payment delinquencies using Naïve Bayes and Support Vector Machine. Research methode is Cross-Industry Standard Process for Data Mining (CRISP-DM). Method testing was carried out with 5 trials. Based on the test results, the average performance of Naïve Bayes is accuracy (62,88%), precision (65,27%), recall (77,42%) dan f1-score (70,75%). Meanwhile, the average performance of the Support Vector Machine is accuracy 63,51%), precision (62,25%), recall (94,48%) dan f1-score (75,04%).
Faktor Penghambat Penggunaan Tracer Pada Unit Penyimpanan Berkas Rekam Medis Pasien Rawat Jalan di Rumah Sakit Putri, Sartika Maulida; Sarah, Siti; Anita, Julia; Khatimah, Cut Husnul
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4991

Abstract

Medical record tracers are a replacement for medical records that will be removed from storage for any purpose, usually made of strong and colored material. Factors that cause delays in the use of tracers in storage rooms include the lack of staff with educational backgrounds in medical records, the absence of special officers in the storage department and the non-implementation of SOPs regarding the use of tracers. The aim of this research is to determine the factors inhibiting the use of tracers in the outpatient medical record storage unit at Bhayangkara Hospital Banda Aceh in 2023. This research was conducted in the outpatient storage room at Bhayangkara Hospital Banda Aceh, 15-20 May 2023. This type of research is Descriptive Qualitative. The population of this study consisted of 9 medical records officers. The research sample consisted of 3 people specifically for outpatient medical records officers using Purposive Sampling Technique. The results of the research show that in the use of tracers in the outpatient medical record file storage unit, the human resource factor is in the "insufficient" category, the facilities and infrastructure factor is in the "incomplete" category, the cost factor is in the "not available" category, the equipment and machine factor is in the "not available" category. available” and the raw material factor is in the “incomplete” category. Meanwhile, the factors inhibiting the use of Tracer in storing outpatient medical record files are in the "existing" category. It is recommended to add tracer printing equipment in the form of a printer in the storage room, adding officers who have medical records degrees so that they can carry out outpatient storage properly.
Sistem Pendukung Keputusan Rekomendasi Program Ekskul Disekolah Menegah Kejuruan dengan Metode AHP dan TOPSIS Tanjung, Erti Belastari; Zufria, Ilka; Armansyah, Armansyah
TIN: Terapan Informatika Nusantara Vol 4 No 10 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i10.5011

Abstract

Extracurricular activities are vital for developing students' personalities, talents, and abilities beyond the standard curriculum. However, a lack of effective information dissemination about extracurricular activities poses a challenge. To address this issue, a decision support system using Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods is needed, along with increasing students' awareness of the importance of extracurricular activities. This research aims to recommend extracurricular programs to students in vocational high schools. Specific issues include developing a literature review, designing a user-friendly system, tools for web-based decision support system development, and implementing AHP and TOPSIS methods for extracurricular recommendation systems. The research will be conducted at SMK Muhammadiyah 9 Medan, focusing on 93 selected Class X students. Recommendation criteria will include intelligence level, interests, concentration, memory, commitment, willingness, creativity, health history, and parental consent, based on the results of students' psychological tests. The AHP method will be used for criteria weighting, and TOPSIS will rank recommended extracurricular programs based on priority values. The research aims to provide 9 recommended extracurricular programs tailored to students' interests and talents, enhance researchers' skills in implementing AHP and TOPSIS methods, improve extracurricular program management efficiency, and increase student satisfaction with extracurricular activities. The decision support system developed in this research will benefit researchers, school administrators, and students, improving program management and student participation in extracurricular activities.The implementation results of extracurricular recommendations using the AHP and TOPSIS methods achieved an accuracy of 74%. Changes in accuracy may be influenced by the criteria used and inputted, as well as the minimum extracurricular activities inputted by the user.

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