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All Journal Jurnal Sistem dan Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer JTH: Journal of Technology and Health Jurnal Penelitian Teknologi Informasi dan Sains Indonesia Bergerak: Jurnal Hasil Kegiatan Pengabdian Masyarakat Wissen: Jurnal Ilmu Sosial dan Humaniora Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Gergorius Kopong Pati
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Health Professions Medicine & Pharmacology Nursing Public Health Social Sciences

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Analisis Perbandingan Metode Sibis Dan Metode Econometric Dalam Pengukuran Kesenjangan Digital Di Sumba Barat Daya Gergorius Kopong Pati; A. Djoko Budiyanto
Jurnal Sistem dan Informatika (JSI) Vol 11 No 2 (2017)
Publisher : Bagian Perpustakaan dan Publikasi Ilmiah - Institut Teknologi dan Bisnis (ITB) STIKOM Bali

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Abstract

Sebagai bahan pertimbangan pemerintahan dalam membangun dan menyusun strategi kebijakan pelayanan publik dalam kaitan dengan teknologi informasi dan komunikasi yang berhubungan dengan kesenjangan digital perlu diadakan pengukuran. Hasil dari pengukuran kesenjangan digital tersebut dimaanfaatkan oleh pemerintah Sumba Barat Daya dalam pengembangan kecamatan di Sumba Barat Daya, serta hasil tersebut sebagai bahan acuan dalam pemerataan akses dan kemampuan teknologi informasi dan komunikasi bagi masyarakat melalui penyediaan infrastruktur, program pelatihan untuk pegembangan sumber daya manusia. Dari permasalahan diatas maka perlu diadakan pengukuran tingkat kesenjangan digital yang terjadi di kecamatan Sumba Barat Daya. Pengukuran kesenjangan digital di Sumba Barat Daya menggunakan metode SIBIS dan Econometric dengan membandingkan berbagai macam indikator yang berbeda dalam pengukuran kesenjangan digital. Pengukuran kesenjangan digital ini menggunakan aspek perilaku penggunaan internet, manfaat penggunaan internet dan demografi. Hasil perbandingan dari berbagai macam indikator dengan menggunakan metode SIBIS dan Econometrik menunjukan bahwa tingkat kesenjangan digital dengan mengunakan metode SIBIS menunjukan masyarakat kecamatan di Sumba Barat Daya berada pada kategori sedang sedangkan metode Econometric berada pada kategori Tinggi sehingga pengukuran kesenjangan digital masyarakat kecamatan di Sumba Barat Daya lebih cocok menggunakan metode SIBIS.
PENGUKURAN KESENJANGAN DIGITAL MASYARAKAT DI KABUPATEN SUMBA BARAT DAYA Gergorius Kopong Pati
Jurnal Teknologi Informasi dan Komputer Vol 8, No 1 (2022): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

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Abstract

ABSTRACTInformation and communication technology (ICT) related with government in developing and formulating public service policy strategies has vast benefits in accessing, managing and having very accurate and fast information. Lack of information technology leads to digital divide, so measurement is necessary. Result of measurement of digital divide can be used as reference by government in distributing information and communication technology access and skill to the society by providing infrastructures, training programs for develop human resources.SIBIS (Statistical Indicators Benchmarking the Information Society) is the result of an action of the European Commission to compare various indicators to measure digital divide. The measurement uses SIBIS GPS (General Population Survey) indicator using aspects of internet usage behavior, internet usage benefit and e-government. The populations were 18 – 59 years old people in four sub-districts and 125 respondents were selected by Proportionate Stratified Random Sampling. The result of the measurement of digital divide showed there was digital divide among Northwest Sumba people, showing lack of socialization and training program, as well as inadequate human resources.Keywords: Digital divide, SIBISABSTRAKTeknologi informasi dan komunikasi(TIK) yang berkaitan dengan pemerintah dalam membangun dan menyusun strategi kebijakan pelayanan publik memiliki manfaat yang luas dalam pengaksesan, pengelolaan serta memiliki informasi yang sangat akurat dan cepat. Kurangnya teknologi informasi mengakibatkan terjadinya kesenjangan digital sehingga perlu dilakukan pengukuran. Hasil dari pengukuran kesenjangan digital tersebut dijadikan bahan acuan dalam pemerataan akses dan kemampuan teknologi informasi dan komunikasi bagi masyarakat melalui penyediaan infrastruktur, program pelatihan untuk pegembangan sumber daya manusia.SIBIS (Statistical Indicators Bechmarking the Information Society) adalah hasil kegiatan komisi eropa (European Commision) yang digunakan dalam membandingkan berbagai macam indikator yang berbeda untuk pengukuran kesenjangan digital. Pengukuran ini menggunakan indikator SIBIS GPS (General Population Survey) dengan menggunakan aspek perilaku penggunaan internet, kegunaan penggunaan internet dan e-government. Populasi dilakukan pada masyarakat diempat kecamatan yang berusia 18 – 59 tahun, dan diambil 125 responden dengan metode Proportionate Stratified Random Sampling.Kata Kunci : Kesenjangan digital, SIBIS
Klasifikasi Data Mining Prediksi Penjualan dengan Metode Appriori: Studi Kasus: Toko Agu Ate Naomi Dada Kodi; Gergorius Kopong Pati; Agustina P. Setiawi
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i3.2405

Abstract

Abstract Databases stored on storage media are rarely used by most of their users and even within a certain period of time the data is deleted because it is considered trash and only fills up the storage media. This assumption is not entirely true, because in fact a large database can provide the information needed for various interests, both for business interests in making decisions and for science and research. The development of information and communication technology in this era often called the millennial, information and communication technology is also increasingly advanced and developing and cannot be avoided. Where the development and progress of information and communication technology is growing very rapidly, such as the need for data processing which is increasing every day and if left alone, the data will be useless. By using the Text Mining technique, the classification method, a sentiment will be known to be positive, neutral or negative. One of the algorithms widely used in sentiment analysis is the Naïve Bayes classification method. This study uses the Naïve Bayes Classifier (NBC) method with tf-idf weighting accompanied by the addition of an emotion icon conversion feature (emoticon) to determine the existing sentiment class from tweets about Agu Ate Store. The results of the study show that the Naïve Bayes method without additional features is able to classify sentiment with an accuracy value of 96.44%, while if the tf-idf weighting feature is added along with the emotion icon conversion, the accuracy value can be increased to 98%.
Analysis of Profit Results From The Use of Plts (Solar Power Plant) in Lolo Wano Village Using the Naive – Bayes Classifier Method Oskar Ana Rato; Gergorius Kopong Pati; Katarina Yunita Riti
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 4 (2024): Desember : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i3.2433

Abstract

The newest renewable energy source in the world and one of the most reasonably priced is solar energy. Because solar energy has so many benefits all year round, it can be a cost-effective energy source when used, especially since it is so abundant globally. to produce electricity by converting sun energy. The equator-based nation of Indonesia boasts an abundance of solar energy resources, with an average daily solar radiation intensity of about 4.8 kwh/m2. However, there is an abundance of solar-based energy sources that can be utilized. Especially in Lolo Wano Village, where the intensity of solar radiation is quite high, it is an option to develop a Solar Power Plant (PLTS) as a solution to electrical energy needs. In order to specifically identify the class of unknown object labels, classification techniques are employed since they are able to identify models that distinguish between different data classes or data ideas. In the meantime, the Naïve Bayes algorithm takes into account multiple factors that will influence a decision's final result in order to forecast future opportunities based on data that has already been collected. The information utilized comes from observations made by the LOLO WANO VILLAGE PLTS Community (PLTS). The data gathered from the satisfaction survey will be divided into two categories: training data and testing data. The testing data's accuracy will be evaluated using the output of the training data model. The classification findings demonstrate that, with the maximum level of accuracy at 87.50%, the Naïve Bayes algorithm is appropriate for gauging student satisfaction with online learning.
Application of the Naive Bayes Method in Predicting the Level of Community Satisfaction with the Performance of the Magho Linyo Village Head Seselia Soli Lede; Gergorius Kopong Pati; Alexander Adis
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i3.2457

Abstract

Village monies are sourced from the State Budget (APBN) and are allocated in accordance with Law Number 6 of 2016 for the purposes of development, coaching, social activities, and community empowerment. The existence of village finances is necessary to support all sources of revenue for the village, and as the government's revenue grows, so too must the village's public service infrastructure. As a result, the sentiment analysis of village officials will be done in this study. The analysis will include the classification of community sentiment using the Naive Bayes technique. To assess each method's accuracy, two will be contrasted. The village administration, as the highest social institution in the community, is crucial in establishing norms, distributing funds, and creating a help-related socialization process. Furthermore, some Pada Eweta village inhabitants may not receive help, which may cause social rivalry amongst locals. Sentiment categorization will be used to classify responses as positive or negative. Based on feedback from visitors, this study seeks to evaluate the validity of the two approaches put to the test and provide insight into the level of service provided by village officials. The accuracy of both methods will be verified by evaluating the outcomes with the RapidMiner tool.
Penerapan Algoritma K-Means Clustering Data Penduduk Miskin Berdasarkan Desa di Kecamatan Tana Righu Arinto Umbu Dasa; Gergorius Kopong Pati; Emirensiana Dappa Ege
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 2 No. 6 (2024): November : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v2i6.245

Abstract

Expert systems are one type of computer technology that is being used by a used in the medical field to assist physicians in patient examinations is expert systems.The goal of this is to improve patient care both now and in the future.system with expertise is an application that replicates how an expert would reason to solve a particular problem or acts similarly to an expert due to its understanding of a knowledge base that has to be processed and its ability to solve problems. An expert system's diagnosis of epilepsy leads to the creation of a system that can offer individuals with the condition a consultation service for the purpose of diagnosing the condition and providing information on treatment options. This is demonstrated by the development of numerous technologies that facilitate the work of numerous parties. One of them is computer-related and uses Expert System Science to assist in the diagnosis of epilepsy. The Certainty Factor approach is employed in this study. Thirteen symptoms and three different forms of epilepsy—general, partial, and secondary—were used in this investigation. The study's findings indicate that, based on the chosen symptoms, the most accurate diagnosis is Partial Primary, Partial Secondary, with a confidence level of 74%, and the most accurate diagnosis is Generalized Epilepsy, with a confidence level of 99%.
Klasifikasi Data Mining dalam Memprediksi Kinerja Karyawan dengan Metode Algoritma C4.5 pada Toko Merpati Simpang Viktor Loja; Gergorius Kopong Pati; Agustin Purnami Setiawi
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i4.393

Abstract

It has been demonstrated that using computers greatly improves our ability to perform our duties. Information services are vital because, while employee performance may still be predicted manually, the process takes a long time. Data mining technologies, on the other hand, make it easier to anticipate employee success for loyal employees. Employee performance evaluation criteria are necessary in order to increase the accuracy of the assessment results, as Toko Merpati Simpang's employee performance assessments cannot be conducted carelessly. Employee performance has to be analyzed and categorized because up until now, manual employee performance evaluations have only used subjective criteria. The C4.5 Algorithm data mining approach is used in this evaluation of employee performance. The degree of accuracy will be ascertained by comparing these two approaches. Positive and negative emotions are the two categories of sentiment. The aim of this study is to ascertain the degree of accuracy of the comparison between the two tested techniques and to offer information on the quality of one of Toko Merpati Simpang's employee performance assessments using visitor sentiment. The test results will be evaluated using the Rapidminer tool to demonstrate the degree of accuracy for both testing approaches. Keywords: ,
Analisis KNN untuk Tempat Rekomendasi Tempat Wisata Sumba Barat Paschal Wungo; Gergorius Kopong Pati; Karolus Wulla Rato
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i4.408

Abstract

The growth of the internet has influenced the tourism industry because the internet makes it easier for individuals to obtain reviews about places to visit and because the internet is a tool used by tourist site managers to assess the quality of their offerings. The increase in the number of tourists of almost two million in just three years in West Sumba is proof of this influence. Social media is a tool that people use to interact with each other online; some people have multiple accounts on platforms such as Instagram, WhatsApp, Facebook, Telegram, Twitter, and so on. Tourists can receive recommendations for tourist attractions based on price and type of trip desired through a tourist attraction recommendation system that uses the KNN algorithm. Three factors were used in this research: activity, type of tourism, and type of price. An accuracy of 63.16% is found in the test results using the KNN algorithm and the Rapid Miner application with a K value of 5. The analysis results show that the K-Nearest Neighbor (K-NN) approach can be used as a guideline for recommending tourist destinations to visitors in West Sumba.
Implementasi Data Mining Prediksi Perminatan Jurusan Siswa pada SMK Negeri 1 Waikabubak dengan Metode Algoritma C4.5 Marten Sudi; Gergorius Kopong Pati; Lidia Lali Momo
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i4.410

Abstract

Admission of new students to an educational institution is an activity that is always carried out every new academic year, where prospective new students always increase from year to year (Muwardah and Pramunendar, 2015). Admission of students can be held from elementary to middle school, from middle school to high school / vocational school. The focus of this research is the registration of new students at SMK. As is known, SMK is a Vocational High School or abbreviated as (SMK) and where there are many majors provided which ultimately makes prospective new students confused about which major is right for them because will take a long time.. Based on C4.5 as a Classification Algorithm: C4.5 is a popular algorithm for building decision trees. It works by dividing a dataset into smaller subsets based on attribute values, thus forming an easy-to-understand tree structure. Classification results using decision trees provide a clear visualization of the decision-making process and the variables that contribute to student choices.
Analysis of Customer Sentiment at Paga Lewu Store Using the Naive Bayes Clasifer Method Gergorius Kopong Pati; Apliana Mata; Fiandro Markus Laki Riti; Apliana Umbu Lele; Kristofel Bili; Ferianus Dappa Ole; Samuel Weri
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 4 (2024): November : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v1i4.558

Abstract

Sentiment Analysis is a technique for extracting text data to obtain information about positive, neutral or negative sentiments. The purpose of sentiment analysis is given by internet users on social media to provide a personal assessment or opinion. Paga Lewu Shop that often gets user sentiment through social media is Paga Lewu Shop. The existence of consumer opinion sentiments about Paga Lewu Shop can be analyzed and utilized to obtain useful information for other customers and the Paga Lewu Shop. By using the Text Mining technique classification method, a sentiment will be known as positive, neutral or negative. One of the algorithms widely used in sentiment analysis is the Naïve Bayes classification method. This study uses the Naïve Bayes Classifier (NBC) method with tf-idf weighting accompanied by the addition of an emotion icon conversion feature (emoticon) to determine the existing sentiment class from tweets about the Paga Lewu Shop. The results of the study show that the Naïve Bayes method without additional features is able to classify sentiment with an accuracy value of 96.44%, while if the tf-idf weighting feature is added along with the conversion of emotion icons, the accuracy value can be increased to 98%.
Co-Authors A. Djoko Budiyanto Agustin Purnami Setiawi Agustina P. Setiawi Alexander Adis Anderias Kedu Lere Antonius L B Hallan Apliana Mata Apliana Umbu Lele Ariance Renda Wano Arinto Umbu Dasa Ayu, Mitra Permata Damianus Ana Mesa Diana Lia Bora Diana Reby Sabawaly Elfrida Susanti Tanggu Emerensiana Dappa Ege Emirensiana Dappa Ege Ferianus Dappa Ole Fiandro Markus Laki Riti Frengkianus Aprianto Kamuri Friska Priskila Wanda Ibrani Bili Imelda Dengi Walu Indriani Diana Baga Karolus Wulla Rato Katarina Yunita Riti Kristofel Bili Lidia Lali Momo Marden Bayo Margareta Dairo Maria F. Hostika Hangga Maria Wilda Malo Marten Sudi Marvedin S.D. Bulu Matius Ngongo Mikael Lede Mesa Naomi Dada Kodi Oscar Desius Dappa Oskar Ana Rato Paschal Wungo Paulina Indriani Mori Uma Paulus Mikku Ate Petrus Andi Kaza Ridwan Andri Prasetio Samuel Weri Sartini Poety Seselia Soli Lede Susanti Kaka Viktor Loja