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Abstrak :
The performance and usability of the input device play an important role in providing better experience for the user. The touchpad is commonly known as a pointing device and is a predominant pointing technology for notebook computers. However, comparative evaluations have established that touchpad performance is poor in comparison with a mouse. The best setting of touchpad is also remaining unknown. Furthermore, there is no research that study about the velocity pattern in touchpad. To solve this drawback, this research attempts to implement Fitts' Law method, merely focused on touchpad. In the design of experiment, touchpad size and position filter are added as new independent variables, along with Control Display Gain, Distance, Width, and Angle, as the wellknown variables in Fitts' Law researches. Two sizes of touchpad are prepared which consist of large (100*60) and small (65*36) sizes. In addition, position filter is set at 2 different levels: 30 and 50, moreover gain setting is set at 3 different levels of fixed gain: 0.5, 1, and 2. For the Fitts' Law Program, 3 different levels of distance (100, 300, and 500 pixel), 3 different levels of target width (10, 40, and 70 pixel), and 8 directions (0, 45, 90, 135, 180, 225, 270, and 315) are applied. Moreover, the dependent variables that are being studied are movement time, error count, movement count, target re-entry count, and peak velocity. In this experiment, 20 participants are recruited and ANOVA Split Plot is used as the method. In total, each participant performed 2592 trial movements (2 touchpad size × 3 position filter × 3 control display gain x 3 distance × 3 target size × 8 moving direction × 3 repetitions). As for the results, touchpad size significantly affects movement time, error count, movement count, and re-entry count. Position filter also significantly affects the re-entry count. The best setting acquired from result shows that filter 50 and gain 2 are better implemented for primary movement, and filter 30 and gain 0.5 are better applied in secondary movement. The result also shows that there is difference in angle for touchpad performance and mouse. The different behavior for touchpad user also differs in touchpad performance indicator. Moreover, clutching behavior on touchpad user makes touchpad velocity graph to be modeled into several primary movement. Furthermore, strong interaction between distance and gain influences Fitts' Law equation to be modified.

Abstrak :
Perkembangan industri telekomunikasi di Indonesia akan menyebabkan pertambahan Base Transceiver System (BTS) yang menjadi komponen vital bagi bisnis telekomunikasi untuk memperluas jaringan. Pertambahan jumlah BTS telekomunikasi dapat memicu terjadinya risiko meningkatnya masalah-masalah operasional dan pemeliharaan yang dihadapi oleh operator. Penulisan ini bertujuan untuk mengidentifikasi risiko-risiko apa saja yang ada dalam bidang operasional dan pemeliharaan BTS telekomunikasi, menentukan hubungan antar risikonya, menganalisis besarnya tiap risiko menggunakan metode Analytic Network Process (ANP), dan merancang strategi penanganan serta pengontrolan risiko tersebut. Hasil identifikasi risiko operasional dan pemeliharaan BTS telekomunikasi adalah sebanyak 45 risiko, yang diklasifikasi menjadi 6 kategori risiko, yakni: personil, peralatan dan perlengkapan, tower dan shelter, finansial, eksternal, dan metode. Dari hasil analisis model ANP, risiko yang termasuk dalam kategori tinggi adalah 8 risiko dengan range bobot 0.020543 sampai 0.103484, dengan validasi model yang menunjukkan hasil yang konsisten, yakni indeks inkonsistensinya kurang dari 0.1. Analisis model tersebut menunjukkan bahwa perusahaan harus lebih memperhatikan dan menangani terjadinya permasalahan di bagian kategori risiko peralatan dan perlengkapan, terutama kerusakan peralatan dan masalah BTS, kategori risiko personil, proses perbaikan, dan kekokohan tower. ......Nowadays, the growth of telecommunication industry in Indonesia has enhanced the number of Base Transceiver System (BTS) as a vital part of their business to expand network. The increased number of BTS will have an impact to raise their operational and maintenance problems. The purposes of this study are to identify operational and maintenance risks in BTS, determine the connection of those risks, analyze risks using Analytic Network Process (ANP) method, and also compose the strategy to treat and control those risks. The results of identifying operational and maintenance risks in BTS are 45 risks, which classified to 6 categories: personnel, device and tools, tower and shelter, financial, external, and method. Therefore, based on ANP model analysis result, 8 risks are included in 'high' risk category with priorities in range 0.020543-0.103484 and inconsistency index below 0.1, which means that model is consistent and valid. This study suggests that companies have to concern more about problems in BTS, devices, personnel, reparation process, and tower strength.

Abstrak :
Traffic accidents are the third largest cause of death according to the World Health Organization. Moreover, driver fatigue is the second largest factor that causes traffic accidents after traffic violations. The purpose of this study is to find out the significance of driver fatigue using physiological, cognitive, and subjective approaches, as well as a comparison of fatigue between male and female drivers. The study involved twelve respondents, which included six male respondents and six female respondents aged 17−25 years old, measured by physiological (blood pressure and heart rate), cognitive (psychomotor vigilance test), and subjective (Karolinska Sleepiness Scale) approaches. The result of this study is that heart rate is the most sensitive variable. However all of the variables in male and female respondents do not have a significant result. There is no big difference in fatigue levels in male and female car drivers. The conclusion of the study is that the approaches could not be a standardized way to measure fatigue for male and female car drivers because of the variation in results.

Abstrak :
Road accident is a leading problem in Indonesia that increases every year. Based on previous studies, mental fatigue is one of the biggest sources of road accident, that is majorly affected by mental workload. Driving duration is one of factors that triggers mental fatigue. Previous literature stated that Electroencephalogram (EEG) measurement is a gold standard to measure fatigue. However, there was limited study that addressing EEG indicators that affected by driving duration, and the previous research still had disagreements regarding the best EEG parameter to measure fatigue. Therefore, this study aimed to evaluate driving duration effect towards EEG fluctuation and determine the best EEG parameter related to fatigue. Seven participants were asked three hours driving in medium fidelity simulator. One-way ANOVA and correlation analysis were performed on the analysis to measure the effect of driving duration towards EEG indicator and determine the correlation of indicator. Receiver Operating Characteristics (ROC) curve was also utilized to determine the best variable that correlates with subjective sleepiness indices. The results showed that in the end of 3 hours driving, there was an increment of delta and theta activities, followed by decrement of alpha and beta activities. In addition, the correlation of all bands were significant, with positive result of alpha-beta band and theta-delta band, and negative result towards each other. Furthermore, results from Receiver Operating Characteristics (ROC) curve showed that RPR of theta, RPR of alpha, and ratio of ?/?+? as the best indicators among others, that had accuracy of high degree (above 85%).

Abstrak :
This study investigates the effect of touchpad size, position filter, and control display gain on user performance. Observations include the behavior of user while using the touchpad to acquire color-changing targets. This study examines the effect of two touchpad sizes, which consist of large (100×60 mm) and small (65×36 mm) sizes, position filters (30, 50), and control-display gains (0.5, 1, 2) on acquiring targets that appeared in eight positions (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°), at three distances (100, 300, 500 pixel) and 3 different levels of target size (10, 40, 70 pixel). As for the results, touchpad size significantly affects movement time, error count, movement count, and re-entry count. Position filter also significantly affects the re-entry count. The different behavior of touchpad user differs significantly regarding to performance measurements. Filter 50 and Gain 2 for primary movement and Filter 30 and Gain 0.5 for secondary movement are the best combinations for participants to achieve optimum performance. Based on Fitts’ Law, the proposed model successfully predicts movement time by adding the effect of CD gain in formulating the task’s difficulty index (R² = 0.8147). The results in this study will be useful for microelectronic companies to increase touchpad performance and to offer suggestions for designing touchpads based on optimal settings. Furthermore, this study also reveals that each type of touchpad features different settings to achieve optimum performance.