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INDONESIA
SMATIKA
Published by Sekolah Tinggi Informatika dan Komputer Indonesia Malang
ISSN : -     EISSN : -     DOI : -
Core Subject : Education,
Education
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Articles 296 Documents
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Implementasi Metode Topsis Dalam Sistem Pendukung Keputusan Keringanan UKT (Studi Kasus : STIT Madina Sragen) Nor Wahid Hidayad Ulloh; Ulla Delfana Rosiani; Eka Larasati Amalia
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.537

Abstract

Economic distinctions that make it difficult to make UKT payments from each student and college student. There are several students parents who because of economic reasons, are reluctant to make UKT payments. At this point, the introduction of decision-making processes in support of institutional leadership decisions is not new. The criteria for getting UKT waivers are also not arbitrary, but there are special criteria given to the recipients of UKT waivers. Supporting criteria include: Parent's Occupation, GPA Value, Length of Study, Study Status and Family Health. According to the analysis, the results obtained using the topsis method in performing the calculation achieve an 87% accuracy result.
Implementasi Blackbox Testing Pada Aplikasi Real-Time Thermal Video Detection (Studi Kasus Deteksi Demam/Covid-19) Kukuh Yudhistiro; Aditya Galih Sulaksono; Aditya Hidayat Pratama
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.561

Abstract

During the emergence of the Covid-19 pandemic whose vaccines have not been spread evenly, all countries in the world, especially Indonesia have taken several preventive steps to prevent the spread of the virus. One of the initial actions is to detect every person entering and leaving the country through airports or land transportation. This early action was carried out by detecting the body temperature of residents passing in and out of locations such as airports and train stations. The fever detection is generally carried out using a thermal gun in the form of an infrared gun aimed at individuals who pass the inspection. This research discusses a series of tools consisting of a camera with a thermal sensor where the captured data will be processed through software that displays a histogram of the temperature from the chest to the person's head in real time. Each capture result is used as a dataset that can be used for tracing the needs of visitors to public places. In this research, we will discuss functional testing (blackbox) of the application of thermal video detection in case studies of fever detection.
Sistem Informasi Peramalan Obat Alphamol Menggunakan Metode Double Exponential Smoothing Evy Sophia; Jauharul Maknunah; Mohamad Dimas Oktavianda
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.567

Abstract

Sofia Medika Clinic in terms of supply of alphamol drugs every month is always the same, because the clinic has not been able to predict the number of drugs that need to be provided. When the amount of drug inventory is in excess, it will result in fewer drug expiration dates and make the selling price of drugs cheaper. On the other hand, when the amount of drug supply is in short supply, it will have an impact on patient service or buyers who are considered disappointing and have an impact on the clinic. To assist clinics in reducing drug sales errors, a technology is needed in it using forecasting methods. Based on the existing sales data pattern, the forecasting method used is the Double Exponential Smoothing method, because the sales data is a trend with all p-values > 0,05 with the Dicky Fuller test (ADF-test). This study aims to build an Alphamol Drug Forecasting Information System at Sofia Medika Clinic with the Double Exponential Smoothing Method. The results of the alphamol drug sales forecasting application system using the Double Exponential Smoothing Method obtained MAD = 221,0925, MSE = 176693,3, and MAPE = 7,26%. which previously produced a value of 29% so that the results of this application can be used to predict the amount of alphamol drug sales that will be sold in the present and in the future.
Klasifikasi Bumbu Dapur Indonesia Menggunakan Metode K-Nearest Neighbors (K-NN) Suastika Yulia Riska; Lia Farokhah
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.568

Abstract

Seasoning is one of the most important elements in a dish. Indonesian herbs or spices have a very wide variety of types. Mistakes in choosing spices have a big effect on the taste of the dish. Image processing is a branch of science in the field of technology that can be used to recognize image objeks captured by the camera. This study will classify the types of spices that are almost similar, namely ginger, galangal, turmeric and kencur. The classification method used is K-Nearest Neighbor (K-NN). In this study we tested how to split training data and data testing, namely 66.7%: 33.33%, 75%: 25% and 90%: 10%. The sharing of training data and testing data uses 90%: 10% has the greatest average accuracy compared to other distribution methods. The selection of K = 3 or K = 5 has an average accuracy that is almost the same in all methods of split training data and testing data, namely 64.66%: 65%. At K = 1 it has a fairly high accuracy compared to the previous K, which is 73%.
Analisis Future Time Perspective (FTP) dan Kematangan Karir Terhadap Kesiapan Kerja Mahasiswa Sistem Informasi Menghadapi Dunia Kerja Bidang Informatika Rini Agustina; Yoyok Seby Dwanoko
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.571

Abstract

One of the triggers for the high rate of intellectual unemployment is due to poor career planning. Lack of skills and competencies makes students find it difficult to choose a career. After completing a higher education program, in many cases, students are not ready to face competition in the world of work, especially in the field of Information Technology which is constantly updated. This study aims to determine the effect of the future time perspective and career maturity of Information Systems Study Program students on their work readiness in the field of informatics. This study uses a quantitative approach, the sample is a student of the Information Systems Study Program with as many as 150 respondents. The measuring instrument used is the Future time perspective (FTP) scale, the Career Maturity Scale, and the Work Readiness scale. Data were analyzed using multiple linear regression and correlation to determine the effect of each variable. The results of the study showed that the influence of the two variables was 38%. The effective contribution of the Future time perspective to Work Readiness is 5%. Meanwhile, the effective contribution of the Career Maturity variable to Work Readiness is 33%. Thus it can be concluded that the Career Maturity variable has a dominant influence on the Job Readiness variable than the Future time perspective variable. Although the contribution of the Future time perspective variable is small, it provides a significant contribution for students because it provides a new discourse in considering their career readiness.
Perbandingan Hasil Klasifikasi Jenis Daging Menggunakan Ekstraksi Ciri Tekstur Gray Level Co-occurrence Matrices (GLCM) Dan Local Binary Pattern (LBP) Neneng Neneng; Ajeng Savitri Puspaningrum; Ahmad Ari Aldino
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.572

Abstract

Meat has high nutritional value which is widely consumed by humans. The content contained in meat includes protein, vitamins, minerals, fats, and other substances that are needed by the body so that it can carry out activities every. However, unfortunately not all people can distinguish these types of meat, because the texture and color are almost similar. This is also often used by irresponsible meat sellers by mixing these types of meat or with other types of meat to get a big profit. Even though not everyone can consume certain types of meat for reasons of illness. This research was conducted to compare the GLCM and LBP methods for image classification of meat types based on texture analysis. The types of meat images that are classified are goat meat, buffalo meat, and horse meat. Image data is taken manually using a digital camera the Nikon D3200. The image was taken at a distance of 20 cm. Data testing and training was carried out using the Support Vector Machine (SVM) method. The texture characteristics used are ASM, IDM, entropy, contrast, and correlation. The results of the image classification accuracy of goat, buffalo, and horse meat using the GLCM method were 75.6%. While the results of the classification accuracy using the LBP method amounted to 85,6%. Thus, the LBP texture feature extraction method is recommended for classification of meat types using texture characteristics.
Halaman Awal SMATIKA Jurnal Volume 11 Nomor 01, Juni 2021
SMATIKA JURNAL Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

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Abstract

Halaman Depan SMATIKA Jurnal Volume 10 No 2 Desember 2020 Siti Aminah
SMATIKA JURNAL Vol 10 No 02 (2020): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

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Abstract

Perancangan Sistem Pengelolaan Zakat Masjid Jami Al-Muhajirin Berbasis Web Menggunakan Metode Research and Development (R & D) Bagas Prayoga; M. Iwan Wahyudin; Agus Iskandar
SMATIKA JURNAL Vol 11 No 02 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i02.576

Abstract

Technology is increasingly advanced and developing, especially in this modern era, people want things that are practical. This application system is also very much needed in the future in managing zakat at the Jami Al-Muhajirin Mosque and making it easier to pay online. The aim of the author to achieve is to produce a web-based zakat management system at the Jami al-Muhajirin mosque by using the R&D method of application systems in web-based zakat management at the Jami al-Muhajirin mosque to facilitate the management of mosque zakat and can help facilitate the Jami al-Muhajirin mosque committee. -muhajirin in collecting data and making it easier for muzakki to pay online. The function of the R&D method used to create a particular application and the success of the web. The final results of testing zakat payers no longer need to come to the mosque because they can use the website and the committee can make it easier to collect zakat payment reports with the website.
Klasifikasi Sentimen Terhadap Badan Penyelenggara Jaminan Sosial (BPJS) Pada Media Sosial Twitter Menggunakan Naive Bayes Mahmud Yunus; Mochamad Husni; Muhammad Miqdad Mufadhdhal
SMATIKA JURNAL Vol 11 No 02 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i02.577

Abstract

BPJS Kesehatan is listed as the agency that provides insurance financial services with the largest number of public complaints in the Ombudsman in 2019. The number of complaints on the official BPJS Kesehatan twitter account can be an indication of the level of satisfaction and public sentiment towards BPJS Kesehatan services. Twitter can be used to convey the experiences, ideas, complaints, opinions, or facts presented. The Tweet can be either a positive or a negative opinion. To find out, there needs to be an existing data processing process, so that it can be classified as a positive and a negative opinion. The classification method used in this study is the Naive Bayes Classifier. This study aims to see the tendency of the public towards BPJS Kesehatan based on sentiment classifications and to see the level of accuracy of the Naive Bayes Classifier method in classifying BPJS Kesehatan sentiments on Twitter social media. The data used were 780 tweet data from March to May 2020. The results of model testing using the Confusion Matrix resulted in an accurate performance of 86.25%, precision of 84.92%, recall of 87.78%, and f-measure of 86, 37%. As well as the results of testing the data in May 2020, there were 52% of tweets in the positive sentiment category, and 48% of tweets in the negative category

Page 17 of 30 | Total Record : 296

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