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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 472 Documents
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Pengaruh Gamifikasi terhadap Program Loyalitas pada Platform Tokopedia Indonesia Thomas Hardianto; Arta Moro Sundjaja; Yuli Yuli; Giovanka Savina
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.24 KB)

Abstract

The research objective is to develop a conceptual model for evaluating the determinant factors of loyalty program in Tokopedia. The data collection method is literature search. The authors search the literature in Google Scholar using relevant keywords. The authors use e-commerce development in Indonesia, government role in e-commerce development, user behavior, Indonesia e-commerce statistic, gamification, loyalty program as keywords. The authors found and used 45 articles that related with the antecedent of Tokopedia loyalty program. The antecedent of tokopedia loyalty program are gamified loyalty program, reward attractiveness, affective commitment. The mediating variable are playfulness, and attitude toward LP. The dependent variable is loyalty program.
Implementasi Fuzzy Logic Dalam Menentukan Persepsi Masyarakat Pendatang Silky Safira; Wifra Safitri
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The abstract is to be in fully-justified italicized text, at the top of the paper with single column as it is here, below the author information. Use the word “Abstract” as the title, in 10-point Times, boldface type, left relative to the column, initially capitalized. The abstract is to be in 10-point, single-spaced type, and up to 200 words in length. Leave two blank lines after the abstract or list three to five keywords related to the articles, then continued with abstract in bahasa Indonesia.
Sistem Pakar Identifikasi Kerusakan Kulit Wajah untuk Proses Aesthetic and Anti Aging Agung Sugiarto; Neli Nailul Wardah; Andrianto Heri Wibowo
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Face skin is the most sensitive area compared with other parts of the skin. Face skin undergoes various change caused by external environmental influences such as the influence of sunlight, climate, pollution, the use of air conditioners, as well as the use of products or cosmetic that is not appropriate and changes from inside the body such as hormonal changes at puberty, menstruation, pregnancy and the use of birth control pills. The influence of external environment and hormonal changes result in face skin which directly experiences significant changes both in the form of acne and spots and wrinkles so that the skin becomes inflamed. Inflammation is a local reaction on the part of the skin that has an infection. Handling of inflamed skin can be done with several methods such as the use of cream that appropriate to the type of skin or facial treatment that is in accordance with the analysis of skin needs. The objective of this research is to build an expert system of using a suitable cream on damaged face skin. The apllication to developed is expected to help patients and therapists in determining the type of cream that will be used for each skin type and skin damage.
Penerapan Algoritma Topsis untuk Perekrutan Karyawan Divisi HRD pada CV. Semito Mandiri Andriyansyah Andriyansyah; Siswanto Siswanto; Mujito Mujito
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The company implements strict employee recruitment selection for job applicants to suit the company's needs to get quality human resources. The process of selecting prospective employees is done by checking and selection manually by looking at the files sent by applicants. This is of course not only very troublesome but also inefficient and takes a long time, not to mention the possibility of human errors and subjective judgments so that the chosen candidates are not the best candidates. Utilizing a Decision Support System that uses the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Algorithm can help the selection selection problem in the Human Resource Development (HRD) division. So the results of this study are the ranking process with TOPSIS get the average distance between manual results with TOPSIS of 3.5 with a standard deviation of 2.813 and the classification process with Naïve Bayes produces an accuracy of 77.78% and an error of 22.22%, with the error value the results of the classification still have shortcomings in predicting the eligibility of prospective employees.
Penerapan Algoritma Weighted Product untuk Penentuan Pegawai Terbaik Badan LITBANG Ifran Nurkhallam; Siswanto Siswanto
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The Ministry of Home Affairs at the Research and Development Agency (LITBANG) conducts the selection of the best employees to boost employee morale in increasing employee loyalty or loyalty to government agencies and to evaluate the performance of employees from each division. The selection of the best employees has been done periodically or periodically but has not been optimal in its implementation. The Ministry of Home Affairs at the Research and Development Agency found obstacles in determining the selection of the best Employees. Constraints faced are when finding the same final value when the assessment has been carried out and there is a subjective assessment that is assessing someone based on the closeness of the assessment staff so that the Head of Research and Development has difficulty when deciding who the best employee is, this often results in errors in determining the best employee at LITBANG Agency. The application of the Weighted Product (WP) Algorithm is used to determine the best employee at the Ministry of Interior Research and Development Agency. The final result of the system is a report on the best employees based on the Weighted Product algorithm to get the average distance between manual results with Weighted Products of 4.05 with a standard deviation of 3.017 and the classification process with Naïve Bayes produces an accuracy of 66.67% and an error of 33.33%, with the error value, the results of the classification still have shortcomings in predicting the eligibility of the best employees. Applications can assist decision makers in deciding who employees are entitled to become the best employees at the Research and Development Agency.
Penerapan Algoritma Simple Additive Weighting untuk Penentuan Karyawan Terbaik Suprihono Suprihono; Siswanto Siswanto
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

PT Elnusa Petrofin (EPN) provides the best contribution to employees, this award is given in the hope of motivating all employees to work well. PT Elnusa Petrofin (EPN) conducted the process of selecting the best employees, so this will of course require a long time and produce less than the maximum. Sometimes mistakes are made by the leader in relation to the best employees, see the conflict that occurs at PT Elnusa Petrofin (EPN) then an algorithm is requested to help the best employee leaders use the Simple Additive Addition Algorithm (SAW) as a method used to find alternative Simple Algorithms This Additive Weighting (SAW) can determine the best association seen from the ranking system at PT Elnusa Petrofin and the results of the ranking process with Simple Additive Weighting obtain an average result of Simple Additive Weighting (SAW) of 4.8 with a standard deviation of 3.982 and a classification process with Naïve Bayes produces an accuracy of 73.33% and an error of 26.67%, with an error value on the results of the allocations needed to predict the best employee performance.
Aplikasi IOT Mengendalikan Ruang Pelatihan dengan Sensor Suhu DHT-11, Kelembaban, Suara dan Gas MQ-2 Sarmani Sarmani; Siswanto Siswanto
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Work tools, routers, switches and others that are used for training the trainees and store important data of the institution. If the temperature of the workspace is hot, it can cause damage to the hardware in the workspace, and the gas emission limit is higher then it can cause damage to the workspace. How to make a compilation of handling temperature suction outside the food limit can be done responsively. At this time the workspace administrator must fix the temperature in the workspace in stable conditions. This will not be effective and efficient, the Administrator must always be in the workspace. IoT Application for Monitoring and Controlling Web-based Workspaces by using the DHT-11 temperature sensor, humidity, sound and MQ-2 gas can be a solution to connect the condenser in the workspace so that it can work in a conducive manner, and can minimize excessive heat for each participant training in the workspace. In the event of a change in the temperature, humidity, sound and gas changes in the workspace, the system will send notifications to the user via e-mail and automate the process of igniting additional vehicles so as to make the room more stable. With this monitoring system the user is expected to be able to easily supervise the workspace. Thus the temperature, humidity, sound and gas of the workspace will regulate its stability and remain in full control of the Administrator without having to constantly be in the workspace. The Language Program used in developing this system is the Arduino Uno R3 English Program that uses C Language and for its visual display uses the PHP Language Program and MySQL database.
Implementasi Algoritma Profile Matching untuk Pencarian Karyawan Terbaik Tri Shoni Wijaya; Siswanto Siswanto
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The company gives rewards or rewards to employees who get the title as the best employees in the form of money with a certain nominal. To support the performance or enthusiasm of the employees in the marketing department. It is expected that the reward can stimulate the enthusiasm of employees at work. However, when evaluating employees there are obstacles, including subjective judgments and calculation errors often occur in determining who the employee gets the best employee title. By utilizing a Decision Support System that uses the Profile Matching Algorithm. Profile Matching is a decision making mechanism by assuming that there is an ideal level of predictor variables that must be met by the subjects studied, rather than the minimum level that must be met or passed, Profile Matching can help problems in determining the best employees in the marketing department. In this study there are two aspects and within the aspects there are several criteria. The Performance Aspect consists of Target Achievement, Work Quality, Work Responsibilities and Services. The Personality Aspect consists of Attendance, Communication, Attitude, Team Work and Loyalty. So the result of this research is an application or decision support system that produces an output from each employee, so that the management of decision makers can see the value of each employee based on the ranking.
Metode Forward Chaining dalam Sistem Pakar Diagnosis Penyakit pada Tanaman Kelapa Sawit Aghy Gilar Pratama; Andrianto Heri Wibowo; Septia Nurhalimah
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Diagnosis of diseases in plants is needed to determine pests or diseases that attack the plant through the symptoms found. This is done in order to find the best healing solutions for oil palm plants that have been stricken with disease, to minimize crop failure. Therefore we need a computerized expert system to replace the conventional system of diagnosing oil palm plant diseases in order to get a more precise and accurate healing solution without having to wait for the expert. Oil palm plantations are one of the types of plantation crops in Indonesia that occupy important positions and develop rapidly, both those that belong to individuals or companies. This is because of the many plants that produce oil or fat are oil palm with the largest economic value per hectare in the world. Not only that, oil from palm oil is also used for fuel (biodiesel). Palm oil pests and diseases are factors that can interfere with the growth and productivity of these plants. Attacking pests and plant diseases can be seen from the physical symptoms, leaves, stems, roots, and from the palm fruit produced. The lack of knowledge of plantation workers about pests and diseases of oil palm plants and the difficulty in consulting directly with an expert makes it difficult for plantation workers to deal with diseases of oil palm plantations resulting in a lack of crop yields from these plants. From these problems many plantation workers cut down trees in an effort to eradicate pests and diseases of oil palm plants. So there is need for research to build expert system software to diagnose oil palm plant diseases. The inference process to diagnose the symptoms of palm oil pests and diseases and the types of diseases using the forward chaining method.
Data Mining Klasterisasi dengan Algoritme K-Means untuk Pengelompokkan Provinsi Berdasarkan Konsumsi Bahan Bakar Minyak Nasional Arief Wibowo; Indah Rizky Mahartika
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Petroleum is one of the natural resources that play an important role in human life, mainly used as the fuel needed by all levels of society. The distribution of fuel oil (BBM) in Indonesia is carried out by the Downstream Oil and Gas Regulatory Agency (BPH Migas). With the availability of data on fuel consumption in each province, it can be seen that the pattern of fuel consumption in Indonesia is beneficial for regulators in the management of fuel distribution. To find out the pattern of national fuel consumption, we need a model of grouping regions in Indonesia based on the level of fuel consumption in each province. This study analyzes data on national fuel consumption throughout Indonesia using the Data Mining Clustering technique, and the Euclidean Distance measurement method. The final results of this study indicate that the K-Means algorithm can group provinces based on national fuel consumption levels into three clusters with their respective specifications. Modeling results were evaluated using the Davies Bouldin Index (DBI) instrument, with a value of 0.32. The results of testing using DBI approaching 0 indicate that the clusters formed are relatively very good and ideal.

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